Doc.: IEEE 802.11-15/568r0 Submission Frequency Selective Scheduling (FSS) for TGax OFDMA May 2015...

doc.: IEEE 802.11-15/568r0

Submission

Frequency Selective Scheduling (FSS) for TGax OFDMA

May 2015

Slide 1

Date: 2015-05-11

Authors:

Kome Oteri (InterDigital)

Name Affiliations Address Phone email Kome Oteri

InterDigital Communication Inc.

9710 Scranton Road, San Diego, CA, 92121

858 210 4826 [email protected]

Alphan Saphin

Fengjun Xi

Hanqing Lou

Rui Yang

doc.: IEEE 802.11-15/568r0

Submission

Outline

May 2015

Kome Oteri (InterDigital)Slide 2

• Motivation

• Channel Selectivity and User Allocation

• Channel Selectivity Simulation Results

• System Throughput Simulation

• System Throughput Results

• Conclusions

• References

doc.: IEEE 802.11-15/568r0

Submission

Abstract

May 2015


This contribution quantifies the potential resource unit (RU) selection gains for OFDMA transmissions using different RU sizes, over a few TGax channels, in all TGax simulation scenarios.

The gains achieved from CSI-based RU selection for TGax OFDMA motivate the need for efficient RU-based feedback.

doc.: IEEE 802.11-15/568r0

Submission

Motivation

• The 11ax specification framework has already defined UL/DL OFDMA as one of the key 11ax MU features [1]. – OFDMA may exploit the channel selectivity to maximize frequency

selective multiplexing gain in dense network conditions [5][6][7]. • We quantify the gains for ideal resource unit (RU) selection for

OFDMA transmissions – over different TGax channels [2][3]– in different TGax simulation scenarios [8]– using different RU sizes

Slide 4

May 2015


doc.: IEEE 802.11-15/568r0

Submission

Channel Selectivity and User Allocation

May 2015


• OFDMA could be used to exploit the channel selectivity in the channel:– In one channel instance (using Channel D model [2]), the maximum gain

between best RU and worst RU is as high as 9dB.

• With CSI at the transmitter, it can allocate only the “best” sub-channel to a STA and avoid allocating the worst sub-channel to that user– this may require sounding or signaling between transmitter and receivers

doc.: IEEE 802.11-15/568r0

Submission

Simulation Methodology and Assumptions

May 2015


Simulation Methodology:• Characterize difference between best and worst user allocation (Instantaneous loss)

• Max_min delta (dB) = Channel power (best RU) – Channel power (worst RU). • Characterize the difference between a best and a random user allocation (Average loss)

• Ave_delta (dB) = Channel Power (best RU) – Channel power(Averaged) Simulation Assumptions:

• 20MHz• Channel-B, Channel-D [2], and UMi channel [3]• Statistics based on 10000 channel instances• Numerology derived from [4]

Number of RUs Number of tones Bandwidth (MHz)RU18 18 13 1RU9 9 26 2RU5 (4,1) (52,26) (4, 2)RU3 (2,1) (104,26) (8, 2)RU1 1 242 19

doc.: IEEE 802.11-15/568r0

Submission

Exemplary Simulation Results – Channel BMay 2015


– Observations: The smaller the RU size, the more RU selection gain potentially achieved

-1 0 1 2 3 4 5 6 7 80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

X: 2.446Y: 0.4999

max(SCk)-avg(SC

k), (dB)

CD

F

CDF of avg sub-channel differences, ChB, 20MHz

13 tones

26 tones52 tones

102 tones

0 5 10 15 20 25 30 35 400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

X: 8.22Y: 0.5003

max(SCk)-min(SC

k), (dB)

CD

F

CDF of max sub-channel differences, ChB, 20MHz

13 tones

26 tones52 tones

102 tones

saturation

Note: Similar results for Channel D and UMi channel may be found in the additional material section

Best vs. Worst RUs Best vs. Average RUs102 tones 3.4 1.452 tones 6.1 2.126 tones 7.6 2.413 tones 8.2 2.5

Difference at Median (dB)

doc.: IEEE 802.11-15/568r0

Submission

Summary of Channel Gain Analysis

• We summarize the gain in RU energy (Ave_delta (dB)) based on channel selection vs random channel allocation Channel B– Channel D– UMi

• Observations: – Gain increases as the RU size decreases– Rate of increase slows as the RU size decreases

May 2015


RU sizes Channel B Channel D UMi102 tones 1.4 1.3 0.752 tones 2.1 2.5 1.726 tones 2.4 3.4 313 tones 2.5 3.8 4

Difference at Median (dB) Best vs. Average

doc.: IEEE 802.11-15/568r0

Submission

System Throughput Simulation Assumptions• No MAC protocol overhead assumed • STAs are located based on specific TGax simulation scenarios [8]• Non-continuous resource allocation was allowed

May 2015


Scenario

NameTopology

Channel

Model

1 Residential

A - Apartment building10m x 10m apartments in a multi-floor

building5 STAs per BSS

Indoor(B/D)

2 EnterpriseB - Dense small BSSs with clusters

10m inter AP distance64 STAs per BSS

Indoor(B/D)

3Indoor Small BSS Hotspot

C - Dense small BSSs, uniform17.32 m inter AP distance

30 STAs per BSS

4Outdoor Large BSS Hotspot

D - Large BSSs, uniform130m inter AP distance

50 STAs per BSS

Outdoor(Umi)

Parameter Value

Scheduler 1. Proportional Fair [9]2. Random

System Throughput

Metric

Shannon Capacity based on system SINR

RU allocation

Non-contiguous

RU allocation

Case 1: RU1Case 2: RU2Case 3: RU5Case 4: RU9

Case 5: RU18Table derived from [8]

doc.: IEEE 802.11-15/568r0

Submission

May 2015


Exemplary Simulation Results : SS3

Number of stations: 30

PF: Proportional fair [9]

Gain of PF scheduling vs Random Scheduling

RU1 RU3 RU5 RU9 RU18SS3 Channel B 12.45% 0.2774 0.3277 35.29% 36.18%

Channel D 7.39% 0.2413 0.3294 38.88% 41.42%

doc.: IEEE 802.11-15/568r0

Submission

Summary of System Throughput Analysis

May 2015


• Large system throughput gains for scenarios with low baseline throughputs• SS3: 42% and SS4: 60%

• Behavior correlates to channel selectivity performance observed in previous results

• Channel B has large initial performance increase due to multi-user diversity in RU1 but quickly saturates as the number of RUs increase

• Channel D and UMi channel show much less initial increase and saturation

RU1 RU3 RU5 RU9 RU18SS1 Channel B 16.57% 25.93% 28.47% 28.90% 29.15%

Channel D 10.33% 22.32% 27.19% 30.02% 31.01%

SS2 Channel B 4.02% 16.47% 20.77% 23.47% 25.01%Channel D 2.36% 14.13% 21.00% 25.59% 29.05%

SS3 Channel B 12.45% 27.74% 32.77% 35.29% 36.18%Channel D 7.39% 24.13% 32.94% 38.88% 41.42%

SS4 UMi 4.98% 25.22% 34.01% 47.59% 60.75%

doc.: IEEE 802.11-15/568r0

Submission

Observations

– Scheduling for OFDMA transmission provides a gain in the system throughput of 802.11ax

– The scheduling is easily done at the AP when Channel State Information (CSI) is available.

– Currently, 802.11 provides CSI feedback for [10]: • Fast link adaptation: single MCS feedback sequence identifier

for a entire transmission bandwidth• DL MU-MIMO: compressed feedback of channel coefficients

for multiple sub-carriers and average SNR of each Space Time Stream

– The accuracy of the CSI required for DL/UL OFDMA may be more than that required for fast link adaptation and less than that required for DL MU-MIMO

May 2015


doc.: IEEE 802.11-15/568r0

Submission

Conclusions

May 2015


• With CSI-based RU selection, OFDMA may maximize the system throughput gain in TGax scenarios.

• We quantify the potential resource unit (RU) selection gains for TGax OFDMA transmissions with different RU sizes, for different channels and in different simulation scenarios. – System throughput gains of up to 42% in indoor scenarios and 60% in

outdoor scenarios may be seen by using CSI-based RU selection as opposed to a random allocation method.

• CSI specific to OFDMA is needed at the transmitter to realize these gains.

doc.: IEEE 802.11-15/568r0

Submission

References

[1] IEEE 802.11-15/132r4 Spec Framework, Intel

[2] IEEE 802.11-03/940r4, TGn Channel Models, Broadcom

[3] Report ITU-R M.2135-1, (12/2009), Guidelines for evaluation of radio interface technologies for IMT-Advanced

[4] IEEE 802.11-15/330r1, OFDMA Numerology and Structure, Intel

[5] IEEE 802.11-14/858r1, Analysis on Multiplexing Schemes exploiting frequency selectivity in WLAN Systems, Samsung

[6] IEEE 802.11-14/1227r2, OFDMA Performance Analysis, Mediatek

[7] IEEE 802.11-15/383r0, Impact of number of sub-channels in OFDMA, Ericsson

[8] IEEE 802.11-15/980r10, Simulation Scenarios, Qualcomm

[9] Zhishui Sun; Changchuan Yin; Guangxin Yue, "Reduced-Complexity Proportional Fair Scheduling for OFDMA Systems,“ Proc. IEEE International Conference on Communications, Circuits and Systems (ICCCAS), vol.2, pp.1221-1225, 2006

[10] IEEE P802.11ac™/D7.0, Draft STANDARD Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 4: Enhancements for Very High Throughput for Operation in Bands below 6 GHz

[11] IEEE 802.11-14/571r8, Evaluation Methodologies, Broadcom

Slide 14

May 2015


doc.: IEEE 802.11-15/568r0

Submission

Additional Material

Slide 15

May 2015


doc.: IEEE 802.11-15/568r0

Submission

Simulation Results – Channel D

May 2015


– Observations: Similar to Channel B but with less saturation at 13 tones

0 5 10 15 20 25 30 35 400

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

X: 14.45Y: 0.5018

max(SCk)-min(SC

k), (dB)

CD

F

CDF of max sub-channel differences, ChD, 20MHz

13 tones

26 tones52 tones

102 tones

-2 0 2 4 6 8 100

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

max(SCk)-avg(SC

k), (dB)

CD

F

CDF of avg sub-channel differences, ChD, 20MHz

13 tones

26 tones52 tones

102 tones

Best vs. Worst RUs Best vs. Average RUs102 tones 3.0 1.352 tones 7.1 2.526 tones 11.1 3.413 tones 14.3 3.8


doc.: IEEE 802.11-15/568r0

Submission

Simulation Results – Channel UMi

May 2015


– Observations: Even less saturation as number of RUs reduce

0 5 10 15 20 25 30 350

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

max(SCk)-min(SC

k), (dB)

CD

F

CDF of max sub-channel differences, Umi, 20MHz

13 tones

26 tones52 tones

102 tones

-2 -1 0 1 2 3 4 5 6 7 80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

max(SCk)-avg(SC

k), (dB)

CD

F

CDF of avg sub-channel differences, Umi, 20MHz

13 tones

26 tones52 tones

102 tones

Best vs. Worst RUs Best vs. Average RUs102 tones 1.5 0.752 tones 4.4 1.726 tones 8.4 313 tones 12.6 4


doc.: IEEE 802.11-15/568r0

Submission

May 2015


System Throughput Performance for SS1-4

SS3 SS4

SS1SS2

doc.: IEEE 802.11-15/568r0

Submission

Simulation Methodology of System Throughput

• Obtain per tone SINR of STAs based on path loss, shadowing of specific simulation scenario and fading channel

• Estimate effective SINR of sub-channels based on the specific numerology using the capacity mapping in [11]

• Perform proportional fair scheduling based on effective SINR of different sub-channels [9]

• Assign users to sub-channels• Estimate PHY layer system throughput based on capacity of chosen

users• Average over multiple drops

May 2015


Doc.: IEEE 802.11-15/568r0 Submission Frequency Selective Scheduling (FSS) for TGax OFDMA May 2015...

Documents

Transcript of Doc.: IEEE 802.11-15/568r0 Submission Frequency Selective Scheduling (FSS) for TGax OFDMA May 2015...