Savo G. GlisicUniversity of Oulu

savo.glisic@ee.oulu.fi

Adaptive/ReconfigurableWireless Communications

informationsource

sourceencoder

{1, 2, …, q}

discrete memoryless source

encryptor channelencoder

datamodulator

spreadspectrum

modulator

channel &network

receiverfrontend

spreadspectrum

despreader

channelestimation

Spreading codegenerator

receive diversity

decryptorsourcedecoder

informationsink

transmit diversity(multiple access)

DatademodulatorMU MLSE

Transceiver configurationcontrol

poweramplification

(powerlimitation)

channeldecoder

Higher layers

Adaptive segments of the system

• adaptive coding, modulation& equalization• power control• time/space/frequency domainspace-time coding/multi-carrier/OFDM

• intertechnology adaptation/roamingTDMA/CDMA/ad hock networks/UWB• minimum complexity/power consumption• bit rate /packet length• adaptive access control/Kalman filter/Fuzzy logic• routing/• source coding/• reconfigurable network architecture/ad - hock network/clustering/node mobility & activity

active networks /operators

PSTNPSTN PLMNPLMN

IP NetworkIP Network PrivateNetworkPrivate

NetworkIMT-2000Network

IMT-2000Network

IMT-2000Access

IMT-2000Access

BRANAccess

BRANAccess

MobileTerminalsMobile

Terminals

TDMA IS 136UMTS WCDMAup to 2MBit/scdma2000

802.112.4GHz (ISM)FHSS & DSSS5GHz

OFDM > 10Mbit/sHiperlan 25Mb(indoor)Hiperaccess(Wider area)Hiperlink 155MbSpace-time-frequency coding

Recofigurabity range

System Architecture for Maintaining QoS in mobile wireless System Architecture for Maintaining QoS in mobile wireless Multimedia NetworkingMultimedia Networking

Compression andPayload Control

Quality of ServiceManager

Quality of ServiceMeasurement

VC/RoutingTable

ConnectionManager

Error Controland

Frame Length

LinkController

ModemController

ChannelModel

Estimator

Processing Gainand

EqualizerCoefficients

ChannelEstimator

Set QoS Level

Set QoS Level

Update QoS Level

Update QoS Level

Adaptive Link Control

Adaptive Physical Layer

Processing Gain SpreadCode

CSI: SIR, CIR, fm

ReactiveApplication

Network

AdaptiveRadio

Scalable Codec

CompressionRadio

Block-Diagram

On-LineEstimation

PNGenerators

ReconfigurableBlock 1

ReconfigurableBlock 2

On-LineEstimation

Control andReconfiguration

Management

Control andReconfiguration

ManagementCorrelator

M

I/Q Baseband Signals

On-Line Estimates

PN Seq.

Qr

Qr

FPGA’s

DSP’s

Block-diagram of DSP/FPGA software radio implementation.

Reconfigurable ASIC Digital Communications

Data rate 125 Msymbols/sec

Green Wireless Network Concept

• Focus on human well-being and environmental concerns (reducing EM pollution) while preserving high-performance for the wireless network operation

• Give space for introducing new additional radio systems without health risk

• Should be incorporated in any future wireless networks, therefore referred to as All Generation (AG) networks

Environment-Friendly or Green Wireless Network (GWN)

• reduces inter cell interference (63%>5%) in FDD and • cross frame interference in TDD mode

Space/Rate Adaptive CLSP/DS-CDMA PRN

rm

r0

• Compensate the near-far effects and TPC • difficulty of datagram packet transmissions • under changing channel conditions;• Enhance the system performance and coverage;• Increase the energy-efficiency of mobile terminals;• Reduce inter-cell interference

Centralized Unslotted CLSP/DS-CDMA PRN

Allow MS operating with much lower max. power and reduce EM pollution.

System Parameters

Pt=P

Er=PT0

(rm=2-m/ξ)

r0=1(ring#)distance

rM r1

a) Adaptive System

Pt=Prξ

Tm=2-mT0

(Rm=2mR0)

Tm=T

Er=PT0

r0=1(ring#)log-distance

rM r1

b) Traditional System

• Mobile transmitter power is kept at a normalized level depending on mobile-location space resolution, which is based on propagation attenuation;

• Dynamic range of TPC is closer to 0 instead of e.g. approaching 80[dB] in traditional system that improve TPC resulting in smaller standard derivation of log-normal SINR;

• Transmission bit-rate in [kbps] and duration in [ms] compensate each other resulting in the same bit-energy given a constant packet-length in [bit];

• Higher bit-rate CDMA transmissions tends to need smaller SINR;

• Adaptive system is expected to have better multiplexing gain;

System Parameters (Cont.)

• Radio transmission of the mobile is not allowed in the user's direction: restriction angleα [o]

• The restricted-zone problem (with Pr=α [o]/360) can be resolved by:

– using receiving antenna (omni-directional) also for transmitting when the nearest hub enters the restricted zone;

– advising user to change holding position with control signal;

– redirecting the mobile to connect to othe hub which is not in the restricted zone though farther away;

directivity of receiving antenna

directivity of transmitting antenna

Attenna Patterns of the Mobile's

users directionα

Two-State HMM and Performance Analysis

HMM of System Load State

• Taking into account the impacts of TPC inaccuracy characterized by log-normal SINR, spatial user distributions and channel attenuation;

• Based on the stochastic Knapsack approximation of multi-rate loss network model;

• Mean of log-normal SINR is set the same regardless of bit-rates, also its standard deviation regardless of systems that is not to take advantages of the fixed system in performance comparison

Throughput-Delay Characteristics (1)

0 5 10 15 20 25 30 35 400

0.5

1

1.5

2

2.5

System Throughput

Nor

mal

ized

Ave

rage

Pac

ket D

elay

fixed system adaptive sys. with 1-D uni. SUDadaptive sys. with 2-D uni. SUD

• Performance of the adaptive system is sensitive to Spatial User Distribution (SUD) that affects offered traffic patterns;

• That more users are put closer to the hub can boost up the rate, and reduce the time of transmissions resulting in better throughput-delay tradeoffs

• This is more desirable if the advantages of less required SINR for higher bit-rate and less dynamic range of TPC are taken into account

Effects of Spatial User Distribution (SUD)

Throughput-Delay Characteristics (2)

0 5 10 15 20 25 30 35 400

0.5

1

1.5

2

2.5

System Throughput

Nor

mal

ized

Ave

rage

Pac

ket D

elay

fixed system adaptive sys. with atten. exponent=2adaptive sys. with atten. exponent=3adaptive sys. with atten. exponent=4

L=2560[bit], 2-D uni. SUD, Peb=5e-4

• Performance of the adaptive system is sensitive to attenuation path-loss exponent that affects offered traffic patterns, thus in the same way as of SUD;

• However, SUD is changing more dynamically

Effects of Radio Propagation Attenuation

Throughput-Delay Characteristics

0 5 10 15 20 25 30 35 400

0.5

1

1.5

2

2.5

3

3.5

4

4.5

System Throughput

Nor

mal

ized

Ave

rage

Pac

ket D

elay

fixed sys. with Peb=5e-4 adaptive sys. with Peb=5e-4fixed sys. with Peb=1e-3 adaptive sys. with Peb=1e-3

L=2560[bit], atten. exponent=3, 2-D uni. SUD

• Effects of bad channel conditions due to fading are investigated with introduction of Peb as BER in bad channel state of HMM;

• Performance of the adaptive system is more stable.

Effects of Bad Channel Conditions due to Fading

Throughput-Delay Characteristics

0 5 10 15 20 25 30 35 400

0.5

1

1.5

2

2.5

3

3.5

4

4.5

System Throughput

Nor

mal

ized

Ave

rage

Pac

ket D

elay

fixed sys. L=2560[bit] adaptive sys. L=2560[bit]fixed sys. L=5120[bit] adaptive sys. L=5120[bit]

2-D uni. SUD, atten. exponent=3, Peb=5e-4

• Performance of the adaptive system is also more stable under effects of packet-length in [bit];

• Smaller packet-length makes better system throughput-delay characteristics, but heavier load factor of the protocol overhead as well;

• This serves as the basis for optimum or adaptive packet-length problems subject to optimal systemgoodputEffects of Packet-Length

Conclusions

• The space/rate adaptive CLSP/DS-CDMA PRN system not only can accommodate the GWN concept but also outperforms the fixed counterpart in throughput-delay given the same coverage, offered traffic load and link-quality requirements

• The rate/space adaptive scheme also increases the robustness against the uncertainty of radio channel

PRNNinterference

predictor

Fuzzy/Neuralaccess probability

controller(FAPC/NAPC)

Fuzzyperformance

indicator

PV(n+1)PD(n+1)

LV(n)RC(n)U(n)

DD(n)

Is(n)

( )1~ +nIs

A(n)

Fuzzy/Neural Congestion Controller

A pipeline recurrent neural network (PRNN)

A DS-CDMA/FRMA cellular system with the fuzzy/neural congestion controller.

fuzzy/neural adaptive congestion controller

The rule structure for the fuzzy performance indicatorRule LV RC U DD A1 Hi Lt Sm Lg A12 Hi Lt La Lg A13 Hi Lt Sm Sh A14 Hi Lt La Sh A25 Lo Lt Sm Lg A26 Lo Lt La Lg A37 Lo Lt Sm Sh A38 Lo Lt La Sh A49 Lo Bg Sm Sh A510 Lo Bg La Sh A611 Lo Bg Sm Lg A612 Lo Bg La Lg A713 Hi Bg Sm Sh A714 Hi Bg La Sh A815 Hi Bg Sm Lg A816 Hi Bg La Lg A8

Rule IS A ∆P1 Hi La ∆P12 Hi Md ∆P13 Hi Sm ∆P24 Me La ∆P25 Me Md ∆P36 Me Sm ∆P47 Lo La ∆P58 Lo Md ∆P69 Lo Sm ∆P6

Fuzzy/neural congestion controller with NAPC

Fuzzy/neural congestioncontroller with FAPC

Channel access function(chapter 10.4.)

150 160 170 180 190 200

10-4

10-3

10-2

10-1

Number of users in a cell

Voice packet dropping ratio LV

NAPC

FAPC

Channel access function

150 160 170 180 190 20010-7

10-2

10-1

100

Number of users in a cell

Corruption ratio RC

NAPC

FAPC

Channel access function

150 160 170 180 190 200

0.6

0.7

0.8

0.9

Utilization U

Number of users in a cell

transmitter

transmitters

transmitters

Bandwidthmanager

(neighbour)

Bandwidthmanager

(neighbour)

Bandwidthmanager

receiver

Existing localconnections

Connectiondemand

Ad - traffic declarations

H- channelcharacteristics

Out-of-cell interference

Decision (accept or reject)

G - traffic statechannel characteristics

Kalman filter based adaptive access control

Receiver

RAKE

Decoded information

Interferencesamples

Is

BERc - channel bit error rate

Measurement(mean andvariance)

Interferenceprediction

adtraffic declaration(new connection)

ip, vp

( ) rIiyI P −<+ maxˆ Estimation

(Kalmanfilter)

( )yV

( )yI

Maximuminterference

threshold

Reservationthreshold

Imax

r

noyes

ACCEPT REJECT

( ) rIiyI P −<+ maxˆ

Estimation Decision

Average number of voice connections per cell with fixed power control [80]Fixed strategy Local strategy Global strategyA ∆A r2 ∆A r2 r3SU2 34.5 +4% 9 +7% 5 1SU4 60.3 +10% 9 +12% 5 1SC2 11.6 +20% 9 +22% 5 1SC4 14.7 +13% 9 +17% 5 1SX2 29.9 +3% 9 +8% 5 1SX4 50.8 +7% 9 +10% 5 1NX2 28.1 +5% 9 +10% 5 1NX4 50.8 +6% 9 +8% 5 1

Mean connections per cell with SIR power control [80]Fixed strategy Local strategy Global strategyA ∆A r2 ∆A r2 r3SC2 11.5 +20% 10 +24% 5 1SC4 14.7 +27% 10 +33% 5 1SX2 29.3 +15% 10 +31% 5 1SX4 51.3 +14% 10 +24% 5 1NX2 28.8 +16% 30 +17% 25 21NX4 52.2 +10% 30 +17% 25 21

Software distribution & business model(upgrading procedures/cycles)