2005/12/06OPLAB, Dept. of IM, NTU1 Optimizing the ARQ Performance in Downlink Packet Data Systems With Scheduling Haitao Zheng, Member, IEEE Harish Viswanathan,

2005/12/06 OPLAB, Dept. of IM, NTU 1

Optimizing the ARQ Performance in Downlink Packet Data Systems With

Scheduling

Haitao Zheng, Member, IEEE

Harish Viswanathan, Senior Member, IEEE

IEEE TRANSACTIONS ON

WIRELESS COMMUNICATIONS

VOL. 4, NO. 2, MARCH 2005

Presented by Li-Yi Lin


Outline

IntroductionOptimizing the mapping between SINR and MCSOptimizing the scheduler ranking for HARQSimulation and discussion


Introduction

Two main considerations of designing systems which provide high-speed packet data service on the downlink

- the selection of MCS based on the channel quality of the link

- the selection of the user to whom a particular slot is assigned

Adaptive techniques - Dynamic Link Adaptation of Adaptive Modulation and coding

- Automatic Repeat reQuest (ARQ) or Hybrid ARQ (HARQ)

- Scheduler


Dynamic Link Adaptation of Adaptive Modulation and coding

Link adaptation continuously adjusts the modulation and coding scheme (MCS)

The transmitter selects an appropriate MCS, based on the user’s channel quality feedback

The performance of link adaptation largely depends on the accuracy of channel quality measurement.


Automatic Repeat reQuest (ARQ) or Hybrid ARQ

Packet data is delay-tolerant - feasible to use retransmission schemes to recover erroneous packets.

HARQ can compensate for link adaptation errors and provide a finer granularity of coding rate

HARQ - simple ARQ

- chase combining

- incremental redundancy


Simple ARQ - simple ARQ based transmitter retransmits the same packet and

repeats the procedure until the packet is received successfully.

Chase combining - the base station repeatedly sends the same packet and the receiver

aggregates the energy from the (re)transmissions to improve signal to noise ratio (SNR)

Incremental redundancy (IR) - transmits additional redundant information in each retransmission and

gradually refines coding rate and SNR till a successful decoding is achieved.


Scheduler

Scheduler can take advantage of channel variations by giving certain priority to the users with transitorily better channel conditions.

The choice of the scheduling algorithm critically impacts the system performance.


Introduction (cont’)

Aggressive MCS

The conventional mapping design fails to take into account the performance improvement by HARQ.

The instantaneous rate does not fully represent the true data throughput.


Outline



Optimizing the mapping between SINR and MCS

Assume that the channel quality feedback carries SINR.

The mapping is between the SINR and the MCS.

For both Chase combining and simple ARQ, the MCS used in retransmissions is the same as that in the original transmission.

Assume the channel condition stays constant during retransmissions as that of the initial transmission.


Notation


The traditional mapping selection criteria


A single unified mapping criterion

- The average throughput of an AWGN channel using MCS i

),|( iSE η

),|( iTE η

： the average number of successfully received information bits

： the average time taken by the packet


TRPT-Chase：


(6)

TRPT-SARQ：



Outline



Optimizing the scheduler ranking for HARQ

Two important characteristics - Frame Error Rate Information

- Retransmission Information

The scheduler design and the mapping selection can be conducted jointly to optimize the system performance.

But for simplicity, we assume the scheduler design and the mapping selection are performed independently.

Replacing the instantaneous rate with effective rate.


Ranking A: Instantaneous Rate

Ranking B: ARQ Success Probability Weighted Instantaneous rate

,


Ranking C: Average Packet Throughput Based Effective Throughput

),|(

),|()(

iTE

iSEkRAT η

η


Ranking C:


Ranking C:


Ranking D: Success Probability Weighted Instantaneous Rate

Ranking E: Approximated Average Packet Throughput Based Effective Throughput


Outline



The simulated radio network - Opnet network simulation tool

- a radio network controller (RNC)

- a base station (Node B)

- mobile terminals

- total networking delay = 50 ms

- time multiplexing

- each scheduling interval of frame lasts 2 ms

- apply built-in module to IP, TCP, UDP, HTTP, FTP

Simulation and discussion


- Radio Link Protocol (RLP) * performs data block segmentation and reassembly * The RLP PDU size is chosen to be 40 bytes

- * performs scheduling, MCS selection and HARQ functionality * HARQ operates in terms of three Stop And Wait process * the Maximum number of retransmissions is 4 * MAC scheduler makes scheduling decision about 1 ms prior to the

actual transmission

- PHY * assume the uplink channel operates at 64 kbps and 0% FER * For the downlink channel, the frame error is generated by relating the

SINR at each mobile terminal to a link level performance curve * Physical mobility of the user has not been considered * 5-MHz spectrum and 2-ms frame



4MCS set - 640kbps 、 1.28Mbps 、 1.92Mbps 、 2.56Mbps

6MCS set - 320kbps 、 480kbps 、 640kbps 、 1.28Mbps 、 1.92Mbps 、 2.56Mbps



AGG criterion ： 3 dB more aggressive than TRPT-chase



Three scenarios

Scenario A: Single User With TCP

Scenario B: Multiple Users With TCP and Modified

Scheduler Rankings

Scenario C: Multiple Users With TCP Using Ranking C

for Various Mapping Criterion



Performance measurement ：




Scenario B: Multiple Users With TCP and Modified Scheduler Rankings

Fairness measurement


Fig. 7. Multiple-user HTTP performance of various scheduler rankings using Chase combining and TRPT-chase mapping criterion, 6MCS set. (a) 3 km/h and (b) 30 km/h.



Fig. 8. Multiple-user HTTP performance of various scheduler rankings using Chase combining and AGG mapping criterion, 6MCS set. (a) 3 km/h and (b) 30 km/h.





Fig. 10. User HTTP performance of various mapping criterion using Chase combining, proportional fair scheduler with ranking C, 4MCS set, 3 km/h. (a) System metric and (b) user throughput.

Scenario C: Multiple Users With TCP Using Ranking C for Various Mapping Criterion


Summary & future workThe proposed mapping design achieves 5%-50% throughput improvement.

The modified proportional fair scheduler achieves 10%-30% performance improvement.

The sensitivity of the performance to the mapping depends on the granularity of the MCS set with decreasing sensitivity for larger MCS sets.

The channel estimation and prediction error can also be included in the mapping design by modifying the frame error rate accordingly


Thank You!

Documents

2005/12/06OPLAB, Dept. of IM, NTU1 Optimizing the ARQ Performance in Downlink Packet Data Systems With Scheduling Haitao Zheng, Member, IEEE Harish Viswanathan,