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D3.3 - Insights from simulation experiments on combined cellular satellite UAS communication

DeliverableID [D3.3]

ProjectAcronym DroC2om

Grant: 763601 Call: H2020-SESAR-2016-1 Topic: RPAS-05 DataLink Consortium coordinator: AAU Edition date: [30 June 2019] Edition: [01.00] Template Edition: 02.00.00

EXPLORATORY RESEARCH

EDITION [01.00]

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Authoring & Approval

Authors of the document

Name/Beneficiary Position/Title Date

Jeroen Wigard / NBL Project TM 30/05/2019

István Z. Kovács / NBL WP4 lead 30/05/2019

Matthieu Clergeaud / TAS Contributor 03/06/2019

Reviewers internal to the project


Troels Sørensen /AAU Project lead 30/06/2019

Nicolas van Wambeke /TAS WP2 lead 30/06/2019

Approved for submission to the SJU By - Representatives of beneficiaries involved in the project


Nicolas van Wambeke TAS 30/06/2019

Troels Sørensen AAU 30/06/2019

Jeroen Wigard NBL 30/06/2019

Rejected By - Representatives of beneficiaries involved in the project


D3.3 - INSIGHTS FROM SIMULATION EXPERIMENTS ON COMBINED CELLULAR SATELLITE UAS COMMUNICATION

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Document History

Edition Date Status Author Justification

00.10 06/11/2018 DRAFT Jeroen W. Early ToC

00.5 27/05/2019 DRAFT Jeroen W. Added most of cellular content, except results

0.6 03/06/2019 DRAFT Matthieu C. Satellite modelling

0.9 19/06/2019 FINAL DRAFT Jeroen W Version for internal review

01.00 30/06/2019 FINAL Final version submitted to EC

Dissemination level: Public

Copyright Statement:

© – 2018 – Thales Alenia Space, Aalborg University, Nokia Bell Labs, atesio GmbH. All rights reserved. Licensed to the SESAR Joint Undertaking under conditions.

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DroC2om DRONE CRITICAL COMMUNICATIONS

This technical deliverable is part of a project that has received funding from the SESAR Joint Undertaking under grant agreement No 763601 under European Union’s Horizon 2020 research and innovation programme

1.

Abstract

In this Deliverable D3.3 the insights of the simulation experiments, which are targeting to be used in the demonstrator, are described and explained. Results for cellular only, satellite only and the combined hybrid access system are included, and several features and parameters are varied to show the main effects and behaviours for C2 link performance in selected reference scenarios. A short description of the main assumptions and modelling of the main features is also included.

In conclusion, Deliverable D3.3 has addressed the gains from different features and combinations. It is shown that while cellular C2 link provides low delay, it needs interference mitigation to provide good link stability. Satellite systems on the other hand, have less link failures and therefore per se better link stability compared to the cellular system, but suffer from longer delays. The combination of both systems through hybrid access provides overall reliability improvements: satellite adds to C2 link stability and cellular adds lower delay.

1 The opinions expressed herein reflect the author’s view only. Under no circumstances shall the SESAR Joint

Undertaking be responsible for any use that may be made of the information contained herein.


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Table of Contents

Abstract ................................................................................................................................... 4

1 Introduction ............................................................................................................... 8

1.1 Purpose and Scope ........................................................................................................ 8

1.2 Technical contributions .................................................................................................. 9

1.3 Abbreviations, terminology and definitions .................................................................. 10

2 Simulation model ..................................................................................................... 15

2.1 Overview ..................................................................................................................... 15

2.2 Cellular network modelling .......................................................................................... 16

2.3 Satellite modelling ....................................................................................................... 20

2.4 Hybrid Access modelling .............................................................................................. 24

3 Results ..................................................................................................................... 26

3.1 Reference results ......................................................................................................... 26

3.2 Hybrid access results ................................................................................................... 44

4 Summary and conclusions ........................................................................................ 50

5 References ............................................................................................................... 51

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List of Tables Table 1: Abbreviations ........................................................................................................................... 13

Table 2: Terminology and definitions .................................................................................................... 14

Table 3 Reference settings .................................................................................................................... 27

Table 4 Number of handovers, RLF and mean delays in DL and UL vs HOHysteresis ........................... 34

Table 5 Main output KPIs for the three different load levels ................................................................ 34

Table 6 Main output KPIs for the number of muted cells in the downlink (reference scenario) ......... 35

Table 7 Main output KPIs for the reference scenario and for a different number of beams on the drone ..................................................................................................................................................... 36

Table 8 Main satellite network parameters used for the reference scenario ...................................... 38

Table 9 Main data link parameters used for the reference scenario .................................................... 38

Table 10 Delay and reliability for the cellular, satellite and hybrid system. ......................................... 45

Table 11 Delay and reliability for the cellular, satellite and hybrid system (high load in the cellular system) .................................................................................................................................................. 47

Table 12 Delay and reliability for the cellular, satellite and hybrid system (high load in the cellular system) .................................................................................................................................................. 49

List of Figures Figure 1 Architecture for the overall simulation environment [5], with the focus of the current chapter encircled in red. ....................................................................................................................... 15

Figure 2 High Level overview of the modelling ..................................................................................... 16

Figure 3 Example antenna pattern for 6 beams case, assuming that the pattern is symmetric around the main lobe (at 0 degrees). ................................................................................................................ 20

Figure 4 Satellite Network Simulator block diagram ............................................................................. 22

Figure 5 Illustration of the hybrid access scheme which has been used in the simulations ................ 25

Figure 6: Route of flight of the demonstration scenario and basis for the results in this section. ....... 26

Figure 7: Serving cell RSRP in dBm vs time, experienced by the drone. .............................................. 28

Figure 8: Drone UL Power in dBm vs time. ............................................................................................ 29

Figure 9: DL interference in dBm vs time, experienced by the drone. ................................................. 29

Figure 10: DL SINR dB vs time, experienced by the drone . .................................................................. 30

Figure 11: CDF of the downlink (DL) and uplink (UL) SINR dB for the reference scenario .................... 30


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Figure 12: Occurrence of RLF vs time, experienced by the drone; a RLF is indicated by the value 1, and 0 means no RLF . .................................................................................................................................... 31

Figure 13: Mean delay (per second) vs time, experienced by the drone in downlink (DL) and uplink (UL). ....................................................................................................................................................... 32

Figure 14: Mean delay (per second) vs the first part of the route, experienced by the drone in downlink (DL) and uplink (UL). .............................................................................................................. 32

Figure 15: CDF of the delay per packet in downlink (DL) and uplink (UL) ............................................. 33

Figure 16: CDF (zoomed in to the values below 100 ms) of the delay per packet in downlink (DL) and uplink (UL) ............................................................................................................................................. 33

Figure 17 CDF of DL SINR for the reference scenario and for different number of cells muted. ......... 35

Figure 18 Coverage configuration with two overlapping spot beams, west and east of the reference scenario. ................................................................................................................................................ 38

Figure 19 Forward SNR versus time along the reference trajectory ..................................................... 39

Figure 20 Return SNR versus time along the reference trajectory ....................................................... 39

Figure 21 Forward Packet Error Rate versus time along the reference trajectory ............................... 40

Figure 22 Return Packet Error Rate versus time along the reference trajectory .................................. 41

Figure 23 Overview of the Network Capacity Simulation Tool ............................................................. 42

Figure 24 Cumulative Distribution function of the Forward Delay ....................................................... 42

Figure 25 Cumulative Distribution function of the Return Delay .......................................................... 43

Figure 26 CDF of the downlink delay for the cellular, satellite and hybrid access system (reference scenario) ................................................................................................................................................ 45

Figure 27 CDF of the uplink delay for the cellular, satellite and hybrid access system (reference scenario) ................................................................................................................................................ 45

Figure 28 cdf of the downlink delay for the cellular, satellite and hybrid access system (high load in the cellular system) ............................................................................................................................... 46

Figure 29 cdf of the uplink delay for the cellular, satellite and hybrid access system high load in the cellular system) ..................................................................................................................................... 47

Figure 30 cdf of the downlink delay for the cellular, satellite and hybrid access system (6 antenna beams at the drone in the cellular system) ........................................................................................... 48

Figure 31 cdf of the uplink delay for the cellular, satellite and hybrid access system (6 antenna beams at the drone in the cellular system) ...................................................................................................... 48

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1 Introduction

1.1 Purpose and Scope

The target of this deliverable is to provide insight in the combined cellular – satellite drone communication through simulation experiments. The different overall concepts for this combined communication can be found in D4.3. In this document, we will mainly focus on the hybrid access scheme, which was also experimentally demonstrated for the case of two cellular LTE systems [1], and the basis for the demonstrator in the DroC2om project.

The work has been carried out in close collaboration with, and receiving input from, Work package 4. The system requirements and scenarios detailed in Deliverable D2.3 [2] have been used whenever possible. The propagation models derived based on the experimental work described in Deliverable D5.1 and Deliverable 5.2 [3] [4] have been incorporated in the simulation tool used for the performance evaluations.


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1.2 Technical contributions

The work documented in this Deliverable D3.3 has contributed to the following technical DroC2om areas:

o Description of the modelling related to the results generation, which is used for the demo for both satellite and cellular system – Chapter 2.

o Simulation results related to the cellular network and their explanation against the variation of the main parameters, for example network load, and similarly impact of features like beam steering and inter-cell interference control (ICIC) on the performance – Section 3.1.

o Simulation results related to the satellite network and their explanation against the variation of the main parameters, for example network load – Section 3.1.

o Simulation results related to the combine cellular - satellite network and their explanation against the variation of the main parameters, for example network load – Section 3.2.

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1.3 Abbreviations, terminology and definitions

Abbreviation Explanation

3G 3GPP UMTS 3rd

generation cellular systems

3GPP 3rd

Generation Partnership Project (cellular systems)

4G 3GPP UMTS-LTE (E-UTRAN) 4th

generation cellular systems (aka LTE)

5G 3GPP 5th

generation cellular systems

5GC 3GPP 5G Core Network

5G NR 3GPP 5th

generation New Radio cellular systems

AERO Asymmetric Extended Route Optimization

AF Application Function (5G)

AFRMS Airborne Flight and Radio Management System

AMF Access and Mobility Management Function (5G)

ANS Air Navigation Services

AS Access Stratum (communication protocol)

ATM Air Traffic Management (manned and unmanned)

ATS Air Traffic Services

AUSF Authentication Server Function (5G)

AV Aerial Vehicle(3GPP) or Drone (SJU)

BBF Broadband Forum

BVLOS Beyond Visual Line-Of-Sight

C2 (C&C) Command and Control

CN Core Network (3GPP)

CM Connection Management

D&A (DAA) Detect and Avoid

DL Downlink radio communication, Forward link (FWD): Network/Satellite -to- UA

DN Data Network e.g. operator services, Internet access or 3rd party services

DTM Drone Traffic Management

EASA European Aviation Safety Agency

eNodeB (eNB) E-UTRAN Node B (base station)

FDD Frequency Division Duplex

FWD Forward (link). Equivalent to DL. This terminology is preferred in the satellite case, since the Forward link is actually composed of consecutive uplink (gateway to satellite) and downlink (satellite to drone).

gNB 5G Node B

HCPE Hybrid-access Consumer Premises Equipment


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HAG Hybrid-access Gateway

HDLGW Hybrid (multilink) DataLink Gateway. Same as Multi-Link Gateway (MLGW)

HDLUE Hybrid (multilink) DataLink User Equipment. Same as Multi-Link Adaptor (MLA)

ICAO International Civil Aviation Organization

IP Internet Protocol

IPv4 IP version 4

IPv6 IP version 6

JARUS Joint Authorities for Rulemaking of Unmanned Systems

KPI Key Performance Indicator

LEO Low Earth Orbit

L2 Layer 2 communication protocols

LA Link adaptation (radio)

LISP A Multi-Homing and Mobility Solutions for ATN using IPv6

LOS Radio Line-Of-Sight

LTE 3GPP UMTS Long Term Evolution (Release 8-9)

LTE-A, LTE-Advanced 3GPP UMTS Long Term Evolution Advanced (Release 10-15)

GBR Guaranteed Bit Rate

gNodeB (gNB) Next generation NodeB (5G)

gNB-CU gNB Central Unit

gNB-DU gNB Distributed Unit

GRE Generic Routing Encapsulation

HA Hybrid Access (BBF)

HAG Hybrid Access Gateway. A logical function in the operator network implementing the network side mechanisms for simultaneous use of both e.g. SAT and 3GPP access networks

HCPE Hybrid Customer Premises Equipment (CPE). CPE enhanced to support the access side mechanisms for simultaneous use of both e.g. SAT and 3GPP access

HO Radio hand-over (serving cell change)

IETF Internet Engineering Task Force

MAC Medium Access Control layer (communication protocol)

MEO Medium Earth Orbit

MLA MultiLink Adaptor

MLGW MultiLink Gateway

MME Mobility Management Entity (4G)

MPTCP Multipath TCP

NAS Non-access Stratum (communication protocol)

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N3IWF Non-3GPP InterWorking Function (5G)

NEF Network Exposure Function (5G)

NG Next Generation (5G)

NLOS Radio Non-Line-Of-Sight

NRF NF Repository Function (5G)

NSSF Network Slice Selection Function (5G)

OWD One-way delay

PCF Policy Control Function (5G)

PDCP Packet Data Convergence Protocol (communication protocol, 3GPP)

P-GW Packet Data Network Gateway (4G)

PHY Physical layer (communication protocol)

PiC Pilot in Command

PRB Physical Resource Block

QCI QoS Class Identifier

QoS Quality of Service

Qout (DL) Serving Signal Quality Outage

QUIC Quick UPD Internet Connections

RAN Radio Access Network

RLC Radio Link Control layer (communication protocol)

RLF Radio Link Failure

RMa Rural Macro (3GPP scenario)

RTN Return (link). Equivalent to UL. This terminology is preferred in the satellite case, since the Return link is actually composed of consecutive uplink (drone to satellite) and downlink (satellite to gateway).

RTT Round Trip Time

RPAS Remotely Piloted Aircraft System: Equivalent to UAS

RRC Radio Resource Control layer (communication protocol)

RRM Radio Resource Management

SAT Satellite System/Network

S(at)GW Satellite Gateway

SATPL Satellite Transparent payload (supported by Platform)

SEPP Security Edge Protection Proxy (5G)

SDAP Service Data Adaptation Protocol (5G)

SESAR JU Single European Sky Air traffic management Research Joint Undertaking

SFRMS Satellite Flight and Radio Management System


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S-GW Serving Gateway (4G)

SoA State-Of-the-Art (literature, solution, concept)

SMF Session Management Function (5G)

TCP Transmission Control Protocol

TR Technical Report

UA Unmanned Aerial/Aircraft

UAS Unmanned Aerial/Aircraft System, including UAV, ground control, and communication link

UAV Unmanned Aerial Vehicle

UDM Unified Data Management (5G)

UDP User Datagram Protocol

UDR Unified Data Repository (5G)

UDSF Unstructured Data Storage Function (5G)

UE User Equipment (3GPP 4G/5G)

UL Uplink radio communication, Reverse link: UA -to- Network/Satellite

UMa Urban Macro (3GPP scenario)

UPF User Plane Function (5G)

U-Space See Table 2

VLOS Visual Line-Of-Sight

VPN Virtual Private Network

Table 1: Abbreviations

Term Explanation

C2, C2 DataLink, UAS DataLink

“Command and Control” Link, a data link established between the remote “Pilot in Command” (PiC) and the vehicle it is controlling. This link is used to exchange data necessary for the Aviate, Navigate, Communicate functions of the airborne platform and is different from the “Payload Communication” link that is used to carry data related to the mission of the vehicle from a customer point of view.

C-plane Control plane radio communication protocols; control messages, data packets used to manage the user plane (U-plane)

Drone UAV with private or commercial application, operating in the EASA Open or Specific category.

Hybrid Access The coordinated and simultaneous use of two heterogeneous access paths (e.g., LTE and SAT).

Hybrid Access path Network connectivity instance between HCPE and HAG over a given access network; SAT or 3GPP.

Hybrid Access session

A logical construct that represents the aggregate of network connectivity for a Hybrid Access subscriber at the HAG. It represents all traffic associated with a subscriber by a given service provider, with the exception of Hybrid Access bypass traffic, and provides a context for policy enforcement.

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Payload The term payload designates the equipment that is hosted on a physical aerial/airborne platform for the purpose of performing the mission.

The term payload can be used in reference to a UAV Payload (i.e. the equipment on board the UAV that are used for the UAV to perform its mission, e.g. sensors or cameras used to examine a given geographical area).

The term payload can be used in reference to a Satellite Payload (i.e. the equipment on board a satellite that is used for the satellite to perform its mission, e.g. a transparent signal repeater in a telecommunication satellite or an optical equipment in an earth observation satellite).

Radio adaptation Adaptation and configuration mechanisms on the PHYsical layer and Medium Access Control layer

Radio capacity The transmission (DL and UL) radio resources available in the radio system.

Radio link The DL or UL radio transmission link

Radio mobility UE changing the serving radio cell (base station, eNB, satellite) due to physical movement, radio channel changes, or explicit commands from the serving cell.

U-plane User plane radio communication protocols; payload end-user data packets

U-Space A set of new services and specific procedures designed to support safe, efficient and secure access to airspace for large number of drones.

Alternatively, refers to the node(s) in a communications network where these services and procedures are implemented.

Table 2: Terminology and definitions


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2 Simulation model

In this section, we provide an overview of the simulation model emphasized by the red circle in Figure 1, and shown in the context of the overall simulation environment [5]. In [5] also the details of how the different aspects are explained.

Figure 1 Architecture for the overall simulation environment [5], with the focus of the current chapter encircled in red.

2.1 Overview

The high-level overview is shown in Figure 2. It follows the description from D3.2, and the following components can be seen:

Cellular network simulator with its input and output. This is further detailed in Section 2.2.

Satellite network simulator with its input and output parameters. This is further detailed in Section 2.3.

Hybrid Access Functionality, which is referred to in D3.2 as “evaluation of combined link performance”, uses output from the Cellular and Satellite network simulator as input, and provides the overall combined output, based on the setting given as input. This is further described in Section 2.4

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Figure 2 High Level overview of the modelling

2.2 Cellular network modelling

As described in D3.2 [5], the propagation between the drone and base stations is an input, but also the uplink interference and downlink base station load in terms of resource load, expressed in Physical Resource Blocks (PRB) are input parameters here. A PRB is representing the minimum time-frequency unit a resource can be divided into. In the following two subsections the different outputs KPI are described together with the main assumptions and methodology. Note that the modelling and assumptions are based on the studies and analysis from [6].

2.2.1 Output KPIs

DL_Interference. This represent the downlink interference and is calculated based on the propagation input. The propagation input together with the transmit power of the base station is converted to the Reference Signal Received Power (RSRP). The 30 strongest cells (and hence RSRP values) are available per drone, where one is the serving cell. The remaining 29 are used as potential interferers. The total interference is calculated as the sum power, weighting each contribution with the relative percentage DL load in the corresponding cell (average interference model).

DL_SINR_dB. This is the downlink signal to interference ratio (SINR). The interference is explained above (DLInterference), whereas the signal is based on the RSRP of the selected serving cell (for serving cell selection modelling, see Section 2.2.2).

Cellular NetworkSimulator

SatelliteNetworkSimulator

Hybrid Access Functionality

Cellular inputs Satellite inputs

Cellular output KPIs Satellite output KPIs

Combined Output KPIs


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UL_SINR_dB. Uplink signal to interference ratio for the serving cell. The uplink interference is provided as an input parameter, while signal level is simply calculated from the transmitted power (based on power control as explained further down in the section) and knowledge of the DL RSRP. This means that the DL and UL path loss are assumed to be the same, which is reasonable when the distance between uplink and downlink frequency is low, i.e. when the same frequency band is used for downlink and uplink communication. This is normally the case in Frequency Duplex Division (FDD) systems.

Number of HO. The number of handovers is calculated based on serving cell changes and is therefore very correlated with the way handover is performed. Due to the time-discrete simulation approach, one time step contains only one set of RSRP measurements, hence the value will be zero or one per time step. For details in the handover procedure, see the description below.

Number of Radio Link Failures (RLF). This is a critical parameter, as it means the drone loses all connectivity. It is assumed that an RLF happens when the DL_SINR is below -8 dB [7]. As one timestep only contains one set of measurements, the value will be zero or one per timestep. Consequences of an RLF can be :

o If RLF-mode = 1 is used, the packets during the RLF are discarded and they are added to the DL packet errors and UL packet errors for the duration of the RLF (RLFduration).

o If RLF-mode = 2 is used, packets are delayed. It is assumed that the packets are delayed until RLFduration expires and then all delayed packets are received in one go.

Note that RLFduration is a parameter, which in the simulations is set to a constant value.

DL_throughput_kbps. This is based on the Shannon mapping from [8] , which estimates the throughput based on bandwidth and SINR with the following assumptions:

o Bandwidth efficiency = 0.9

o System efficiency (Eta) = 0.9

o SINR offset (SNR_eff) = 2 dB

Overall these parameters represent the efficiency of a receiver to decode the signal correctly. Output is the downlink throughput in bps, which in the tool is converted to kbps.

UL_throughput_kbps. Similar to the downlink, this is based on the Shannon mapping from [8], with the following assumptions:

o Bandwidth efficiency = 0.9

o System efficiency (Eta) = 0.9

o SINR offset (SNR_eff) = 1 dB (better receiver than in the downlink)

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Output is the uplink throughput in bps, which in the tool is converted to kbps.

DL_packet_error. This is the packet error rate due to not being able to provide the required throughput, calculated as2:

where experienced throughput is the actual throughput (see DL_throughput above) within the timestep, and required throughput is the throughput requirement; ‘min’ is the minimum of the two argument values.

UL_packet_error. Similar the DL packet error, but in the uplink direction.

DL_packet_delay_array. A timestep can contain more than one packet. For instance, if a timestep lasts 500ms and inter-arrival time between packets is 100 ms, then one simulation timestep will contain 5 packets. The delay is calculated for every single packet. The delay per packet in the downlink is calculated as follows in ms:

where

o is the one-way delay between the base station, or Radio Access Network (RAN), and the U-space. This is modelled as a lognormal distribution with constant mean delay and a constant standard deviation. It is modelled truncated such that the actual value cannot become negative. For this distribution is that it is expected that to ensure high reliability, good transport link will exist between the U-space and the relevant RAN gateway.

o is the one-way delay between RAN and the drone, which is calculated as follows:

where TransmissionTime is the time it takes for the packet to be transmitted given the throughput which is achieved, ProcessingTime is an constant input parameter (processing_delay_ms) , and RetransmissionTime is the time a retransmission takes (retransmission_delay_ms) at the occurrence of a block error. The latter happens with a certain probability, corresponding to the block error rate at the physical layer(L1 BLER).

o is added only in case there is a handover during a timestep. In that case, the delay is added to all packets during the corresponding timestep. The value is based

2 The definition here refers to the packet error rate as seen from higher layer protocols (e.g. IP layer) and not

the physical/medium access control layer block error rate (BLER) used as part of the underlying link adaptation; the latter is controlled by retransmissions at the physical - medium access control layer in order to target a 10% BLER.


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on a minimum handover delay (min_HO_delay), plus an exponentially distributed delay with mean mu_HO_delay_ms.

o is added only after an RLF happens. After an RLF it is assumed the connection is down for the duration of RLF_duration. If RLFmode=2, the packets are delayed with the corresponding time interval, i.e. they are sent right after RLF-duration expires. If RLFmode=1, the packets are discarded, and the value of the delay will be set to NaN to indicate that there is no proper delay value.

packet_delay_array. The uplink packet latency is calculated as for the downlink. All parameters are the same, but transmission time is calculated based on the uplink throughput.

2.2.2 Feature modelling

The modelling above reflects the basic underlying cellular system performance. It was already shown in deliverable D4.1 [6] that certain mechanism, or features, are required to improve the cellular C2 link performance. In case these features are activated in the simulations, some of the calculations in the previous section are modified. Here we focus on three effective features previously investigated in D4.1, namely beam selection uplink power control, and Inter-Cell Interference Control.

Serving cell selection and handover: The serving cell is based on the received signal strength, measured through the RSRP. A handover is triggered when a neighbouring cell becomes better than the serving cell by an offset, known as HOhysteresis (also called A3 handover trigger in standardization)3. In case of the possibility of multiple antenna beams on the drone, the RSRP of the different cells, weighted by the beam pattern, is compared, and the beam, and corresponding cell, which results from the maximum power level is selected.

Power control: Power control regulates the transmit power of the drone in the uplink. It follows the following standard LTE/LTE-A power control algorithm, expressed in dBm:

where P0 and α are input parameters, PL is the path loss (calculated based on the received DL RSRP), and PRBs is the number of PRBs. The latter is fixed to 6 PRBs, based on the fact that C2 is a low bitrate channel and hence with low radio resource consumption.

ICIC: Inter-Cell Interference Control controls how many cells are to be muted through the parameter sim_conf.ICIC. If this number is larger than zero, the strongest sim.conf.ICIC interferers are muted. The strongest cells are determined by the DL RSRP values. The inclusion of ICIC only affects the calculation of the total interference.

Beam selection: A drone can be configured with a number of beams. If the number is one, an omnidirectional antenna is assumed. For more than one antenna, an antenna pattern needs to be

3 No time windows, e.g. “Time to Trigger” are modelled, as the timesteps in the simulator are too large to

evaluate the impact

EDITION [01.00]

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provided; as explained previously, the beam pattern weights the RSRP received from different cells. Figure 3 shows an example of the beam pattern for the case where 6 beams is assumed. The pattern relates to the horizontal (2D) plane and will be the same for all 6 beams. For the simulations, we ignore any variation of the pattern in elevation, so that the pattern effect is independent of a cell’s direct line of sight inclination to the horizontal plane4. The beam orientation in the horizontal plane is such that the first beam points in the direction of flight and the remaining are equally spaced circumferentially.

Figure 3 Example antenna pattern for 6 beams case, assuming that the pattern is symmetric around the main lobe (at 0 degrees).

2.3 Satellite modelling

The modelling approach for the satellite part is quite different from the cellular one. This was introduced in Deliverable D3.2 [5] and D4.2 [9], but the following paragraphs give more details on the assumptions, model inputs, computational features and outputs.

2.3.1 Assumptions

The main assumption is that the satellite network considered in this study is dedicated to the provision of drone communications. As a consequence, the network capacity is not shared with other (mobile or fixed) users. Hence, a particular modelling was needed to simulate the behaviour of potential other network users. Instead, different levels of simultaneous drone communications were

4 Essentially this implies that the drone is flying not too high, and not too close to base stations, as well as the

UAV is subjected to very small pitch and roll rotations.


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generated to simulate different levels of the network load. The second main assumption is that the satellite network is at a primary level of deployment. A geostationary satellite network is then taken into account, providing all drones with a time-independent C2 link service coverage. Realistically in a first step, this initial deployment would use a limited number of spot beams to cover the European sky. Specifically, emphasis is put on a reference scenario with only 2 spot beams purposely overlap within the region of the considered use case.

2.3.2 Model inputs

Following these assumptions, the main input data needed by the satellite network simulator are, as described in Deliverable D3.2 [5]:

the number of drones

the time-stamped locations of the drones

the data packet sizes and times of arrival

the satellite trajectory: here, the satellite is at a fixed geostationary orbital position of 5° East

The simulations also rely on the local database of the Earth surface, delimiting the boundaries of the land with respect to the water areas such as sea, lakes or fjords. This database is not directly accessed by the satellite network simulator, but instead, the type of ground (land or water) is provided as an input attribute of the drone locations. In a more elaborated version of the simulator, more categories of the land cover could be used.

The drone locations, when generated with a sufficiently low time step (i.e. high resolution), were also used to compute the drone velocities, as this parameter is taken into account in the link performance model. In the geostationary satellite configuration, only the drone velocities contribute to the relative emitter-to-receiver velocity, and therefore results in a limited Doppler effect. When using a Low-Earth-Orbit (LEO) or Medium-Earth-Orbit (MEO) satellite network, however – besides the network management to handle the complexity of coverage cells moving in time – the Doppler range can be higher, depending on the additional relative velocity of the satellite.

2.3.1 Model overview

Figure 4 gives an overview of the satellite network simulator.

The JSON input scenario files described in D3.2 [5] are shown on top. Additionally, the “Land cover map” and the “Satellite trajectory” have been marked with dashed-line since they are not directly provided as inputs to the satellite simulator but are stored in a database or provided as constant values.

The blue containers represent the simulator processing blocks, a first one at the drone side, and a second one at the network level.

In the bottom part, the KPI output block collects the KPI performance indicators coming from each subpart of the simulator and generates an Output file using the JSON format described in D3.2 [5].

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Network

Drone

Satellite connectivity

UAV trajectories

Geo-routine

Scenario info

positions,velocities,

anglessurface type

MultipathLoS

positions

C/N0Performance as f (Multipath, LoS)

Multipath conditions

Beam Capacity Model

SNR, PER

KPIDelay,

Throughput

Output file

Beam selection

serving beam

Classes of traffic

data packets

UAV Link Requirements

Land cover mapSatellite « trajectory »

Figure 4 Satellite Network Simulator block diagram

More details about the features of this performance module are given in Section 2.3.3.

2.3.2 Output KPIs

Below is a list of indicators provided as outputs by the satellite performance simulation module. Indicators are prefixed with FWD (Forward link) or RTN (Return link), depending on the direction of the signal (see Table 2: Terminology and definitions).

FWD SNR. This indicator corresponds to the Signal-to-Noise ratio of the Forward Link, at the input of the drone satcom transceiver. It concerns the signal transmitted by the satellite payload to the drone and takes into account a reference satellite transmit power, the satellite reference transmitting antenna gain, the propagation losses and the drone antenna gain-to-noise temperature model.

FWD PER. This indicator corresponds to the Forward Packet Error Rate estimation, based on the Forward signal-to-noise ratio at the drone receiver input and the higher-level simulation parameters, such as the environment type, the relative drone velocity, or degradation due to multipath propagation.


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RTN SNR. This indicator corresponds to the Signal-to-Noise ratio received at the input of the satellite antenna. It takes into account the drone transmit power, the propagation losses and the satellite reception antenna gain-to-noise temperature model.

RTN PER. This indicator corresponds to the Return Packet Error Rate estimation, based on the RTN signal-to-noise ratio and the higher-level simulation parameters, such as the environment type, the relative drone velocity, or degradation due to multipath propagation.

Throughput. This indicator gives the data rate the drone UE can reach (both FWD and RTN directions). By system design, the achievable throughput for one drone is directly related to the packet generation. As described in Deliverable D4.2 [9], resource allocation management is such that a drone uses dedicated channels on the forward and the return link. In the selected reference scenario a single class of traffic (no priority rules applied) with constant payload length and a deterministic packet arrival was used.

FWD Delay. This indicator gives the Satellite Gateway to drone latency induced by the network resource allocation management (time slot allocation) described in D4.2 [9]. The simulation model takes into account the 300-ms multi-frame structure, and the presence of other users in the Time Slot Time Plan (TSTP) within the spot beam used by the considered drone UE. Priority rules due to different classes of traffic will not be applied in the reference scenario. An additional delay due to RF propagation is also added.

RTN Delay. This indicator gives the drone-to-satellite-gateway latency induced by the network resource allocation management (time slot allocation) described in D4.2 [9]. The simulation model takes into account the 300-ms multiframe structure, the usage of time slots used for Forward link (Half Duplex). Priority rules due to different classes of traffic will not be applied in the reference scenario. An additional delay due to RF propagation is also added.

2.3.3 Performance modelling

Most of the drone features have been modelled in Deliverable D3.1 [10]. Mainly, it consists in:

Considering a drone antenna with a constant omnidirectional gain of 5 dBi. The model behind is actually a switchable antenna composed with several elements: only one of the eight elements is used at a given instant, and it chosen using algorithms to detect the direction-of-arrival of the signal in space. For now, no improvement using analog or digital beamforming algorithms is modelled. The satellite antenna is accommodated on the top of the aircraft body to limit the impact of multipath propagation and to avoid the blockage of Line-of-sight signals, usually coming from positive elevation angles.

The attitude of the drone is considered almost unchanged during the whole simulated flight. No flight model was applied to the drone :the drone flies in a horizontal plane throughout the whole simulation. From a satellite point-of-view, this will lead to very small changes in satellite elevation angle. In a more realistic approach, however, the potential multipath channel fading due to the ground reflection needs to be taken into account (see the 2-tap propagation model described in [10]), so that the drone antenna is not spatially filtering this secondary signal from the ground.

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In Figure 4, the “geo-routine” basically computes geometrical properties due to the relative drone-satellite position and velocity; these properties feed the two-tap model in order to compute the signal propagation conditions and deduce the Signal-To Noise Ratio and the Packet Error Rate for both the forward (downlink) and return (uplink) directions.

On the network side, the following features may affect the simulation:

Serving beam selection: The serving beam is the one offering the best propagation conditions at each given time step. In the frame of WP3, the SNR estimate of each serving beam is considered a sufficient quantity to actualise the serving beam for a given drone.

Spot beam handover: Handovers occur whenever the serving beam changes. They are performed in a ‘make-before-break’ seamless fashion, so that no additional delay is to be accounted for. In practice, serving beam algorithms would have to be developed to model more realistic handovers, for instance using the intended flight trajectory (or flight plan), to avoid multiple handovers in a short period of time.

Service class priority rules: Although one of the main features of satellite network described in D4.2 [9], this one was not used in the frame of WP3 simulations, in order to make a clearer analysis on the hybridisation results.

2.4 Hybrid Access modelling

Several schemes to combine the satellite and cellular link are described in [11]. In the simulations, one of the schemes is considered, which we refer to as hybrid access. Main motivation is that the scheme is simple. It relies simply on duplication of the packets and sending them through 2 different paths, i.e. one satellite path and one cellular path. Obviously this costs more capacity than a single path, but considering the C2 link is a low bit rate link, this is acceptable. At the same time the scheme does not require large changed on transmitter or receiver side, while the scheme otherwise relies on existing mechanisms and protocols. It can also easily be combined with other features, like for instance the interference mitigation mechanisms which were presented in the cellular part. The scheme is explained with the use of the simplified example shown in Figure 5.

The scheme follows the following principles:

all packets are being sent over the satellite and over the cellular link, so all packets are bicasted.

At the receiver side (the UE), the first received correct version of a packet is stored and any later arriving versions are ignored.

In the simplified fictious example below this means that the first two packets (numbered 1 and 2) are taken from the cellular link: The first packet arrives earlier through the cellular link than through the satellite link (t=0.1 vs t=0.2); the second packet fails through the satellite link, but is received correctly through the cellular link. For the last two packets (numbered 3 and 4), the satellite link is faster (t=0.6 vs t=0.7 for packet number 3 and t=0.9 vs t=1.1 for packet number 4) and they are therefore selected. The mechanism to distinguish between the packets has been described in Deliverable D4.3 [11].


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Figure 5 Illustration of the hybrid access scheme which has been used in the simulations

The main output KPI, among the previously described, is the delay per packet, calculated from the delay KPIs of the satellite and cellular link, respectively(described earlier in this section).

UE

Satellite

Cellular1, t=0.1 1, t=0.2

2, t=0.4 2, t=0.4

3, t=0.7 3, t=0.6

4, t=1.1 4, t=0.9

U-space

1, t=0.1

2, t=0.4

3, t=0.6

4, t=0.9

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3 Results

3.1 Reference results

3.1.1 Cellular only

In this section, the results of the cellular C2 link are described. The results shown here are based on the demonstration scenario, a flight from the north part of Germany to Bornholm, Denmark, as described in Deliverable D3.2 [5]. The route can be seen in Figure 6.

Figure 6: Route of flight of the demonstration scenario and basis for the results in this section.

Publicly available data of real-world base stations of the cellular networks is used, as described in [5]. This document also contains the parameters used, like down tilt of the antennas and so on.

The C2 traffic is characterized by regular packet arrivals in uplink and downlink, as specified in Table 3. Note that the values chosen are of the same magnitude as the values used in [12]. Furthermore, the parameters in Table 3 have been used for the


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demonstration simulations. We will refer to the combination of the demonstration scenario with these parameters as the reference scenario.

Table 3 Reference settings

Parameter Value

Reference Network Load 30%

Beams 1, i.e omnidirectional

ICIC off

Power control α 1

Power control P0 -88 dBm/PRB

BTS transmit power 46 dBm

Bandwidth 10 MHz

Frequency band 800 MHz

RAN – U-space one way delay Lognormal distribution with 5 ms mean and 1 ms standard deviation

BLER target for link adaptation 10%

Physical layer retransmission delay 8 ms

Processing delay per packet (in UE and RAN)

4 ms

Handover delay 10 ms + exponential distribution with average of 15 ms.

Min RLF duration 1 s.

RLF mode 2 (packets delayed)

Timestep 1 s

HO hysteresis 2 dB

Packet arrivals DL: 21 packets of 100 B per sec (17 kbps)

UL: 9 packets of 100 B (7 kbps)

The following figures show the detailed performance for the reference scenario. A short description is given of the behaviour of the different performance metrics. Afterwards, we show the impact of the different settings and features by focusing on the KPIs where the differences appear.

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Figure 7 shows the serving cell RSRP over time for the DRONE. It represents how well the drone is connected to its base station. The reporting range of RSRP is between -44 dBm and – 140 dBm in the 3GPP specifications and all values we are seeing are showing excellent received signal strength. This can be explained due to the LOS conditions to the serving cell, as we are flying at 100 m, and at that height, the earth curvature does not block the signal, which matched earlier findings reported in [3]. The figure shows also that the part over the sea (from around time step 03:00 to time step 07:00) is giving worse, but still good, performance. This is simply because the distance to the serving cells, which are located on land, are getting larger. The peak at the start and end are caused by the fact that the location of the drone is very close to the cellular base stations.

Figure 7: Serving cell RSRP in dBm vs time, experienced by the drone.

Figure 8 shows the UL power the UE is using, which is as expected the inverse of the RSRP, shown before. Note that the UE reaches its maximum power (+23 dBm) in the part of the route over the sea. Figure 9 shows similarly the downlink interference experienced by the DRONE. The values shown are extremely high compared to ground users. The reasons is the LOS to the interfering cells, as well as serving in Figure 7, and the load those cells are having. Also, in this plot, the area over the sea (from around time step 03:00 to time step 07:00) can clearly be recognized, as the interference drops due to the increased distance to the interfering cells. The combination of Figure 7 and Figure 9 leads to the DL SINR, which is shown in Figure 10. The same data is plotted as a CDF in Figure 11, where also the UL SINR data is included. It can be seen that the uplink SINR is slightly better than the DL SINR, due to the uplink traffic model of the terrestrial traffic. From this figure it can be easily seen that there is more than 1% of values below -8 dB, i.e. the threshold for RLFs. RLFs are illustrated in Figure 12 as a function of time. Most of the RLFs appear over the sea area. There are 639 RLF, corresponding to 2.4% of all samples in the full flight.


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Figure 8: Drone UL Power in dBm vs time.

Figure 9: DL interference in dBm vs time, experienced by the drone.

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Figure 10: DL SINR dB vs time, experienced by the drone .

Figure 11: CDF of the downlink (DL) and uplink (UL) SINR dB for the reference scenario


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Figure 12: Occurrence of RLF vs time, experienced by the drone; a RLF is indicated by the value 1, and 0 means no RLF .

Figure 13 shows the traces of the downlink and uplink average delay per second. There are values close to a second, which matches the RLF, and a lot of values in the lower end of the scale. Figure 14 shows a zoomed in version of the first part of the route. Again, two levels can be seen. The higher values around 40-50 ms correspond to handover occurrences.

Figure 15 and Figure 16 show the cdf of the delays per packet. Figure 15 is a zoomed in version to see how the distribution looks in detail. The peaks of uplink and downlink is slightly different due to different inter-arrival times of the packets. The values overall are very similar, due to the same distributions being used. The only difference between UL and DL directions is the experienced throughput, but as the packets are so small, this has no impact on the delay. The horizontal plateau around 0.4 is caused by the minimum handover delay. Note that only 90% reliability can be achieved when the latency target is 50 ms.

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Figure 13: Mean delay (per second) vs time, experienced by the drone in downlink (DL) and uplink (UL).

Figure 14: Mean delay (per second) vs the first part of the route, experienced by the drone in downlink (DL) and uplink (UL).


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Figure 15: CDF of the delay per packet in downlink (DL) and uplink (UL)

Figure 16: CDF (zoomed in to the values below 100 ms) of the delay per packet in downlink (DL) and uplink (UL)

It can be concluded from the numbers that main contributors to the latencies are handovers and radio link failures. There is a trade-off between handovers and RLF, as if we want to lower the number of handovers, it means we keep being connected to cells with low radio quality for longer time, which increases the risk of a RLF. This can be controlled with the HOHysteresis, which is the amount a new cell needs to be better in

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terms of RSRP before a handover is made. Table 4 shows the trade-off for the reference scenario. It can be seen that it is optimal from an average delay point of view to use a low hysteresis, as the RLF delay is much more impacting than the HO delay, while if we want to lower the number of handovers, it is better to use a larger HOHysteresis

Table 4 Number of handovers, RLF and mean delays in DL and UL vs HOHysteresis

0 dB 2 dB 4 dB 6 dB

HO per sec 0.73 0.51 0.28 0.12

RLF per sec 0.011 0.024 0.095 0.176

Mean DL delay (ms)

39 47 108 184

Mean UL delay (ms)

39 45 102 173

We return now to the reference scenario and use 2 dB as HO hysteresis and vary the load to double load and half the load, corresponding to 60% and 15% resource utilisation. The main results can be seen in Table 5.

As it can be seen, 99.9% reliability can only be achieved for the low load case. For high load cases, interference mitigation techniques are needed.

Table 5 Main output KPIs for the three different load levels

Low load (15%) Medium load (30%) High load (60%)

RLF per sec 0.001 0.024 0.283

Mean DL delay (ms) 25 47 293

Mean UL delay (ms) 25 45 275

Reliability5 within 50 ms

92,5% 90.3% 66,6%

Reliability within 100 ms

99,6% 97,3% 71,5%


99,9% 97,6% 71,7%

5 Reliability here is the probability of correct reception.


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99,9% 97,6% 71,7%

For that reason, we will now look at inter-cell interference coordination (ICIC) mitigation. Results will focus on downlink only, as ICIC works only in the downlink. We assume here that outage comes only from the downlink, which is reasonable given that the uplink load in cellular networks is typically significantly lower than in the downlink. Table 6 and Figure 17 show the results. The reliability can be improved by muting cells: however in order to get significant improvements, one needs to mute many cells (green curve in Figure 17).

Figure 17 CDF of DL SINR for the reference scenario and for different number of cells muted.

Table 6 Main output KPIs for the number of muted cells in the downlink (reference scenario)

Reference

(30% load)

ICIC (1 cell)

ICIC (2 cells)

ICIC (3 cells)

ICIC (5 cells)

ICIC (10 cells)

ICIC (20 cells)

RLF per sec

0.024 0.019 0.013 0.0094 0.0047 0.0006 0

Mean DL delay (ms)

47 42 37 33 28 24 24

Mean UL delay

45 40 36 32 28 24 24

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(ms)

Reliability within 50

ms

90.3% 90,9% 91,3% 91,8% 92,2% 92,6% 92,6%


97,3% 97,9% 98,4% 98,8% 99,3% 99,7% 99,7%


97,6% 98,1% 98,7% 99,1% 99,5% 99,9% 100%


97,6% 98,1% 98.7% 99,1% 99,5% 99,9% 100%

Table 7 finally shows the results for interference mitigation using drone beam selection. The results show that the reliability is improved by using beams. However, the improvement is smaller than expected. The reason for this is that especially over the sea area, the gains are small due to the interference typically coming from the same direction as the desired signal. In this case, the interference doesn’t get suppressed when we point the beam in the direction of the desired signal. Beamforming works best with interferers distributed in all directions.

Table 7 Main output KPIs for the reference scenario and for a different number of beams on the drone

Reference (omnidirectional)

4 beams 6 beams

RLF per sec 0.024 0.016 0.0124

Mean DL delay (ms)

47 35 33

Mean UL delay (ms)

45 34 33


90.3% 91,6% 91,6%


ms

97,3% 98,6 98,8


97,6% 98,8 99,0


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ms


ms

97,6% 98,9 99,0

The overall conclusions that can be made from the evaluation of cellular C2 link performance are:

- The cellular network with 30% load by itself cannot provide 99.9% reliability within a 50 ms packet delay constraint.

- At low network load (15%), 99.9% reliability can be achieved for a 200 ms delay constraint.

- Similarly, for the reference load (30%), muting 10 cells leads to 99.9% reliability within 200 ms.

- The gain from beam steering at the drone is lower than expected, as the interfering cells are mainly coming from the direction of the serving cell

3.1.2 Satellite only

This section gives an insight on the results obtained with the satellite performance simulation module described in Section 2.3. The results are provided for the same particular drone trajectory as in the previous section within the satellite coverage. The multi-beam configuration of the satellite transmit/receive antenna is shown in Figure 18, where the scenario region has been circled in red. The dark lines represent the –3dB boundaries of the beam patterns, configured so that they overlap in the region-of-interest.

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Figure 18 Coverage configuration with two overlapping spot beams, west and east of the reference scenario.

Table 8 gives an overview of the main parameters for the satellite configuration, while Table 9 focuses more on the data link properties.

Satellite parameter Value

Satellite fixed coordinates 0°N latitude

5°E longitude

35786000 meters

Satellite Beam 1 centre coordinates ~51.293°N

~5.621°E

Satellite Beam 2 centre coordinates ~62.759°N

~24.046°E

Edge-of-coverage beam EIRP 52 dBW

Frequency 5060 MHz

Medium Access MF-TDMA

Table 8 Main satellite network parameters used for the reference scenario

Data link parameter Value

Forward (or DL) throughput per drone

17 kbps (21 packets of 100 B per sec)

Return (or UL) throughput per drone

7 kbps (9 packets of 100 B per sec)

Target Packet Error Rate (UL or DL) 10-3

FWD Bandwidth per spot beam 600 kHz

RTN Bandwidth per drone 50 kHz

Table 9 Main data link parameters used for the reference scenario

Results on the SNR and the PER

The signal-to-noise ratio computed by the satellite performance simulation module along the trajectory is shown in Figure 19 for the forward link, and in Figure 20 for the return link.


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Figure 19 Forward SNR versus time along the reference trajectory

Figure 20 Return SNR versus time along the reference trajectory

The SNR remains within an interval of ± 0.5 dB. This variation is mainly due to the small variation of the satellite gain in direction of the drone; seen from the satellite, the area where the drone flies remains within a tight portion of the gain pattern, leading to a slight change in terms of received power level. The left part of the curve (SNR decreasing) is directly correlated to the fact that the drone is moving towards the edge-of-coverage of the western spot beam.

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After a duration of fight of about 1 hour, the SNR increases again, because the drone has entered the eastern satellite spot beam, flying in direction of the centre of the beam. Even if the satellite-to-drone distance becomes larger as the drone flies from Germany to Denmark, inducing higher path losses, the spot beam configuration is such that a slight increase in SNR can still be observed.

Results on the Packet Error Rate

The Packet Error Rate computed by the satellite performance simulation module along the trajectory is shown in Figure 21 for the forward link, and in Figure 22 for the return link.

Figure 21 Forward Packet Error Rate versus time along the reference trajectory

The packet error rate is highly correlated to the SNR value shown above (the higher the SNR, the lower the error rate). The Packet Error Rate depicted here is based on a set of reference PHY layer performance results taking into account the relative position and speed of the drone with respect to the satellite, referred to as ‘Performance as f(Multipath, LoS) in Figure 4. No strong impact is observed in this scenario and the link performances remain at relatively constant level, below the set PER target.


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Figure 22 Return Packet Error Rate versus time along the reference trajectory

In both cases (FWD and RTN), the SNR and PER remain relatively constant with respect to the drone trajectory. Those results are essentially explained by the static nature of the geostationary satellite system; from the satellite point-of-view, the drone is at an almost constant range, in rather constant conditions. The main differentiating factor, hence, is the satellite beam antenna pattern. In our scenario, there is only one switchover between Beam 1 and Beam 2 within the encircled area in Figure 18).

Delay Distribution

The packet delays were estimated using a network simulator module referred to as ‘Beam Capacity model’ in Figure 4, and whose behaviour is explained in Figure 23 (extracted from Deliverable D4.2 [9]).

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Figure 23 Overview of the Network Capacity Simulation Tool

The adaptation of the Beam Capacity model was performed to compute single packet statistics based on the link traffic requirements chosen in the frame of Work Package 3. The C2-M, C2-A, Pilot and DAA classes shown in Figure 23 were replaced by a single traffic generator that complies with the link parameters listed in Table 9.

Figure 24 and Figure 25 show the Cumulative Distribution Function for the Forward link delays and Return link delays, respectively.

Figure 24 Cumulative Distribution function of the Forward Delay

Figure 24 Cumulative Distribution function of the Forward Delay


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Figure 25 Cumulative Distribution function of the Return Delay

The delay distributions shown above were obtained using a satellite network load of 48%.

The staircase shape of the CDF of the forward and return delays are explained by the contribution of

Fixed valued for the time-slot start time (60 ms)

A variation of the additional propagation delay under the quantization level of the network-level results.

The maximum forward drone communications delay is 660 ms, which corresponds to twice the multi-frame structure duration. The interpretation is that, due to network usage, the considered drone could not always be assigned a dedicated FWD channel during the first 60 to 360 ms, but using an extra multi-frame is sufficient.

Concerning the return link, most communications (90%) occurred within the first multiframe (<360 ms), but in some cases the drone had to wait for the next multi-frame: when this occurred the early time slots were used, and the maximum return delay observed was slightly above 400 ms

The overall conclusions that can be made from the evaluation of satellite C2 link performance are

Regarding the satellite link, and taking into account the assumptions described in section 2.3.1, the overall conclusion is that the performance is rather independent of the drone trajectory, and necessarily suffers higher latency than cellular network communication due to the high altitude of the geostationary satellite. The benefit, on the other hand, comes from the constant uniform coverage, which was indeed one of the main targets in developing the satellite system architecture concept in [9].

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3.2 Hybrid access results

In this section, the results of the hybrid access between the satellite system and the cellular system are presented. The results for three combinations are shown:

The reference cellular system (see Table 3) and the reference satellite system (Table 8), which corresponds to the scenario which is most realistic as the cellular network load is in line which network loads during busy hour.

The cellular system at high load (other parameters remain the same) and the reference satellite system (Table 8). This is included to see what the impact is of adding a satellite link to very highly loaded cellular network.

The cellular system at normal load with 6 antenna beams at the drone (the remaining parameters as in the reference scenario) and the reference satellite system (Table 8). This is included to show the effect of having an cellular network with interference mitigation combined with a satellite link and to check if there still is a gain left.

3.2.1 Reference cellular system and reference satellite system

For this section the parameters in Table 3 are used for the cellular system and ones in Table 8 and Table 9 for the satellite system.

Figure 26 and Figure 27 show the CDF of the downlink and uplink delay respectively, while the reliability numbers are shown in Table 10.

It can be seen that while the cellular network provides better delay values than the satellite system for the majority of values, the tails are longer, as a result of the impact from radio link failures. At the same time, it can be seen that the hybrid system provides the best of the 2 systems. The hybrid system eliminates all RLF and brings down the average delays in both systems. Overall, reliability is improved by about 1%, but only if the delay constraint is relaxed beyond the 200 ms constraint.


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Figure 26 CDF of the downlink delay for the cellular, satellite and hybrid access system (reference scenario)

Figure 27 CDF of the uplink delay for the cellular, satellite and hybrid access system (reference scenario)

Table 10 Delay and reliability for the cellular, satellite and hybrid system.

Cellular alone Satellite system Hybrid access

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(30% load) alone

RLF per sec 0.024 0.00028 0.000



Reliability within 50 ms 90.3% 0 % 90,3%

Reliability within 100 ms 97,3% 0% 97,3%


Reliability within 500 ms 97,6% 47,6% 98.7%

3.2.2 Cellular system at high load and reference satellite system

With the same setup as in the previous subsection, we investigate the high load case by increasing the load of the cellular system to 60%. Similar to the previous section, we show the delay distribution for downlink and uplink in Figure 28 and Figure 29, respectively, while a summary of the results can be seen in Table 11. Similar conclusions as in the previous section can be drawn: The hybrid system removes all RLF, improves the average delays and increase reliability only for very relaxed delay constraints.

Figure 28 cdf of the downlink delay for the cellular, satellite and hybrid access system (high load in the cellular system)


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Figure 29 cdf of the uplink delay for the cellular, satellite and hybrid access system high load in the cellular system)

Table 11 Delay and reliability for the cellular, satellite and hybrid system (high load in the cellular system)

Cellular alone

(60% load)

Satellite system alone

Hybrid access

RLF per sec 0.283 0.00028 0.000



Reliability within 50 ms 66,6% 0 % 66,6%



Reliability within 500 ms 71,7% 47,6% 83.5%

3.2.3 Cellular system with 6 antenna beams and reference satellite system

In this section we add 6 beams on the drone for the cellular system, while we set the load to normal again (30%). We keep the satellite system as it was in the previous sections. Figure 30 and Figure 31

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show again the cdfs of the delays, while Table 12 summarizes the main KPIs. Again, similar conclusions can be drawn: RLF are removed by the hybrid approach and delays decrease.

Figure 30 cdf of the downlink delay for the cellular, satellite and hybrid access system (6 antenna beams at the drone in the cellular system)

Figure 31 cdf of the uplink delay for the cellular, satellite and hybrid access system (6 antenna beams at the drone in the cellular system)


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Table 12 Delay and reliability for the cellular, satellite and hybrid system (high load in the cellular system)

Cellular alone

(60% load)

Satellite system alone

Hybrid access

RLF per sec 0.0124 0.00028 0.000



Reliability within 50 ms 91,6% 0 % 91,6%

Reliability within 100 ms 98,8 0% 98,8%

Reliability within 200 ms 99,0 0% 99,0%

Reliability within 500 ms 99,0 47,6% 99,4%

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4 Summary and conclusions

The target of this deliverable is to provide insight in the combined cellular – satellite UAV communication through simulation experiments. The document contains a description of how the cellular, satellite and hybrid access scheme is modelled, the simulated key performance indicators, and the performance results. The latter are the basis for the demonstrator of the DroC2om project.

The work has been carried out in close collaboration with, and receiving input from, WP4. The system requirements and scenarios detailed in Deliverable D2.3 [2] have been used whenever possible. The propagation models derived based on the experimental work described in Deliverable D5.1 and Deliverable 5.2 [3] [4] have been incorporated in the simulation tool used for the performance evaluations.

The performance of the cellular part shows that the cellular network without any additional features, at 30% load, cannot provide 99.9% reliability for a 50 ms packet delay constraint. However, at lower load levels (15%), 99.9% reliability can be achieved for 200 ms packet delay. At the reference load of 30%, muting 10 cells with the ICIC feature leads to 99.9% reliability for 200 ms packet delay constraint. The gain from beam selection at the drone, on the other hand, is lower than the gain potential outlined in previous deliverables. This is mainly due to the specifics of the investigated reference scenario, in which the interfering cells are mostly in the same direction as the serving cell, hence very limited spatial separation and filtering between desired and interfering signals.

Regarding the satellite link, the overall conclusion is that the performance is rather independent of the drone trajectory. This was indeed one of the main targets in developing a satellite system architecture concept, where the availability of the service is key. Delays are in general longer than for the cellular system, but the number of C2 link failures is lower. The use of a geostationary satellite is probably the best answer to provide a network with a wide coverage with lower complexity.

Combining both cellular and satellite system in the hybrid access approach leads to the best of both worlds: the RLFs are removed, whereas the average delays decrease. Typically, the delay distribution follows the cellular delay distribution, except for the tails, which are cut with the help of the satellite system. This leads to the conclusion that the hybrid system leads to a more stable system with lower delays than any of the two systems on itself can provide. The results also show that the strict reliability of 99,9% within 50 ms is hard to achieve in the considered scenarios. However the 50 ms is used as a challenging target, which may not be required in reality, especially not over a sea area which is considered in the scenario. At larger delay values, like 200 ms, it has been shown that the reliability of 99,9% can be achieved.


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5 References

[1] Drone control over public LTE, https://www.youtube.com/watch?v=twsDFQqS7vU&t=11s, Youtube, 10.7.2018.

[2] SESAR 2020-763601, »DROCOM deliverable D2.3 Scenarios and Requirements,« 2018.

[3] SESAR 2020-763601 DROC2OM deliverable, “D5.1 - Preliminary report of first drone flight campaign,” March 2018.

[4] SESAR 2020-763601, »DROCOM deliverable D5.2 Final Measurements«.

[5] SESAR 2020-763601 DROC2OM deliverable, “D3.2 - Reference Scenario,” August 2018.

[6] SESAR 2020-763601 DROC2OM deliverable, “D4.1 - Cellular LTE/5G system concepts to provide optimal support for both terrestrial communications and high reliability UAS data links,” May 2018.

[7] 3GPP, »Evolved Universal Terrestrial Radio Access (E-UTRA); Mobility enhancements,« 3GPP, 2012.

[8] P. Mogensen, W. Na, I. Z. Kovacs, F. Frederiksen, A. Pokhariyal, K. I. Pedersen, T. Kolding, K. Hugl og M. Kuusela, »LTE Capacity Compared to the Shannon Bound,« i IEEE 65th Vehicular Technology Conference - VTC2007-Spring, 2007.

[9] SESAR 2020-763601 DROC2OM deliverable, “D4.2 - Satellite system concepts solutions for high reliability UAS data links,” October 2018.

[10] SESAR 2020-763601 DROC2OM deliverable, “D3.1 - Models for combined cellular-satellite UAS communication,” March 2018.

[11] SESAR 2020-763601 DROC2OM deliverable, “D4.3 - Integrated cellular-satellite inter-system design solutions for high reliability UAS data links,” June 2019.

[12] 3GPP Technical Specification Group Radio Network, “TR36.777 - Enhanced LTE support for aerial vehicles (Release 15),” 2018.

[13] Alcatel Lucent, »The LTE Network Architecture – A comprehensive tutorial,« 2013.

[14] ITU-R, »Characteristics of unmanned aircraft systems and spectrum requirements to support their safe operation in non-segregated airspace,« 2009.

[15] F. Templin, »Asymmetric Extended Route Optimization (AERO),« Interdomain Routing Working Group, 2018.

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[16] N. Leymann, C. Heidemann, M. Wassermann, X. Xue og D. Zhang, »GRE Notifications for Hybrid Access,« Interdomain Routing Working Group, 2014.

[17] H. Rasmussen, K. Mortensen, R. Mogensen og C. Markmøller, »Ultra Reliable LTE with Multiple Internet Interfaces,« Aalborg University, 2017.

[18] 3GPP TSG-RAN WG2 Meeting #99bis, »R2-1711462 - Mobility enhancements for Aerial vehicles – finite buffer scenario results,« 2017.

[19] World Radio Conference (WRC), »Regulatory provisions related to earth stations on board unmanned aircraft which operate with geostationary-satellite networks in the fixed-satellite service in certain frequency bands not subject to a Plan of Appendices 30, 30A and 30B for the control and non-payload communications of unmanned aircraft systems in non-segregated airspaces,« 2015.

[20] SESAR 2020-763601 DROC2OM deliverable, “D2.1 - Scenarios and requirements,” March 2018.

[21] International Civil Aviation Organization (ICAO), “LISP - A Multi-Homing and Mobility Solution for ATN using IPv6,” 2014.

[22] SESAR 2020-763601 DROC2OM, “Technical Annex,” September 2017.

[23] J. Stańczak, I. Z. Kovács, D. Koziol, J. Wigard, R. Amorim and H. C. Nguyen, “Mobility Challenges for Unmanned Aerial Vehicles Connected to Cellular LTE Networks,” in IEEE 87th Vehicular Technology Conference, 2018.

[24] J. Wigard, R. Amorim, H. C. Nguyen, I. Z. Kovács and P. E. Mogensen, “Method for Detection of Airborne UEs Based on LTE Radio Measurements,” in 2017 IEEE 28th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2017.

[25] K.-J. Grinnemo and A. Brunstrom, “A First Study on Using MPTCP to Reduce Latency for Cloud Based Mobile Applications,” in IEEE Symposium on Computers and Communication (ISCC), 2015.

[26] R. J. Kerczewski, “Spectrum for UAS Control and Non-Payload Communications,” in ICNS Conference, 2013.

[27] R. J. Kerczewski and J. H. Griner, “Control and Non-payload communications links for integrated unmanned aircraft operations,” in NASA Conference, 2012.

[28] H. C. Nguyen, R. Amorim, J. Wigard, I. Z. Kovács, T. B. Sørensen and P. E. Mogensen, “How to Ensure Reliable Connectivity for Aerial Vehicles Over Cellular Networks,” IEEE Access, vol. 6, pp. 12304-12317, March 2018.

[29] R. Amorim, H. Nguyen, P. Mogensen, I. Z. Kovács, J. Wigard and T. B. Sørensen, “Radio Channel Modeling for UAV Communication Over Cellular Networks,” IEEE Wireless Communications Letters, vol. 6, no. 4, pp. 514-517, August 2017.

[30] R. Amorim, J. Wigard, H. C. Nguyen, I. Z. Kovács and P. E. Mogensen, “Machine-Learning Identification of Airborne UAV-UEs Based on LTE Radio Measurements,” in Globecom,


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Singapore, 2017.

[31] V. Fernandez-Lopez, K. I. Pedersen, J. Steiner, B. Soret and P. E. Mogensen, “Interference Management with Successive Cancellation for Dense Small Cell Networks,” in IEEE Vehicular Technology Conference (VTC) Spring, 2016.

[32] R. Amorim, P. Mogensen, T. Sørensen, I. Z. Kovacs and J. Wigard, “Measurements and Modeling for UAVs Connected to Cellular Networks,” in IEEE 85th Vehicular Technology Conference, 2017.

[33] 3GPP Technical Specification Group Services and System Aspects, “TS23.401 - General Packet Radio Service (GPRS) Enhancements for Evolved Universal Terrestrial Radio Access Network (E-UTRAN) access,” 2017.

[34] 3GPP Technical Specification Group Services and System Aspects, “TS38.401 - NG-RAN; Architecture description (Release 15),” 2017.

[35] Broadband Forum (BBF), “TR-384 - Hybrid Access Broadband Network Architecture,” 2016.

[36] 3GPP Technical Specification Group Services and System Aspects, »TR23.793 - Study on Access Traffic Steering, Switching and Splitting support in the 5G system architecture (Release 16),« 2018.

[37] 3GPP Technical Specification Group Services and System Aspects, “TS23.402 - Architecture enhancements for non-3GPP accesses (Release 15),” 2017.

[38] 3GPP Technical Specification Group Radio Network, “TR38.811 - Enhanced Study on New radio (NR) to support non terrestrial networks (Release 15),” 2018.

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