Sorour Falahati , Mikael Sternad, Tommy Svensson, Daniel Aronsson Uppsala University

1. Adaptive modulation and multiuser scheduling gains in adaptive TDMA/OFDMA systems in the WINNER framework Sorour Falahati , Mikael Sternad, Tommy Svensson, Daniel Aronsson Uppsala University Chalmers University of Technology

2. Outline • Introduction • FDD downlink and uplink structure • Timing events in DL/UL transmission • Key techniques • Channel prediction • Scheduling • Link adaptation • Compression of feedback information • Simulation results • Summary

3. Introduction • Predictive adaptive resource scheduling using TDMA/OFDMA: • Providing fast link adaptation in an OFDM system based on the predicted channel state information of time-frequency chunks • Providing multi-user scheduling gain by allocating the resources to the flows with the potential of improving the throughput based on their channel status.

4. FDD downlink and uplink structure FDD downlink freq Chunk D D PU UP Chunk BW P: pilots symbols D: DL control symbols U: UL control symbols 8 sub-carriers D D PU UP 6 TOFDM time freq FDD uplink O O O O O O O O C C C C C C C C O: overlapping pilots C: DL control feedback T chunk time

5. Timing events in DL/UL transmission UL O O O O O O O O C C C C C C C C DL DL UL O O O O O O O O D D PU UP D D PU UP 1. DL control symbols: Report which present chunks belong to which flows C C C C C C C C D D PU UP D D PU UP 2. DL pilot symbols: Used for channel prediction Used for channel estimation Dl prediction horizon: 2.5X0.3372ms=0.843ms UL prediction horizon: 2.5X0.3372ms=0.843ms 3. UL control symbols: Report which next UL chunks appointed to which uplink flows 5. DL control feedback symbols: Carry DL channel prediction report 4. Pilot symbols: Used for coherent detection And updating predictor states 6. UL overlapping pilot symbols: Used for prediction

6. Channel prediction • Prediction in frequency domain • A set of linear predictors, one for each sub-band • Kalman predictor: • Predict the complex channel and its power • Using pilots in parallel sub-carriers: • Utilizing correlation in frequency and time domain • Generalized Constant Gain (GCG) algorithm: • No need to update a sate-space Riccati difference eq. • Moderate complexity and negligible performance loss as compared to Kalman algorithm

7. Channel prediction … • SINR and prediction horizon limit at 5 GHz downlink:

8. Channel prediction … • SINR and prediction horizon limits at 5 GHz uplink: 2 users 8 users

9. Scheduling • Resource scheduling • Proportional fair strategy: • Allocating resources (chunks) to the user with the highest SINR relative to its average • For users with the same average SINR, this strategy reduces to Max. Throughput strategy. • Allocating chunks to users with the highest MC rate. • Due to curvature within the chunk, MC scheme is determined based on: Chunk Average SINR Chunk minimum SINR

10. Link adaptation • Each user selects a modulation and coding (MC) scheme for each chunk in competition based on the prediction SINR: • The rate limit for a set of MC schemes are adjusted based on the TBER, average SNR and prediction error variance • Based on the predicted chunk SINR, a MC scheme which fulfills the BER requirement and maximized the throughput is selected.

11. Link adaptation … • BER performance of MC schemes for perfect and imperfect prediction (NMSE=0.1)

12. Link adaptation … • Variation of rate limits of MC schemes with prediction quality: • SNR=10 dB and TBER=0.001

13. Compression of feedback information • Tricks or tools to reduce downlink overhead: • Use implicit signaling of utilized modulation rate whenever possible • Contention-band: The active terminals are in competition for only a part of the total BW • Use short-hand addresses to indicate identities of active users whenever possible.

14. Compression of feedback information … • Tricks or tools to reduce uplink overhead: • Contention-band • Compression of feedback information • Discrete cosine transform: utilizing correlation in frequency • Sub-sampling of transform coefficients in the time domain

15. Compression of feedback information … • THP as a function of feedback rate: • ITU VA channels, v=50 km/h, sub-sampling factor of 2 10 users 5 users 1 user

16. Simulation results • Simulation set-up • Wide-area full-duplex FDD downlink • WINNER Urban Macro channel model • Single cell (sector) and SISO • Users with equal velocities and average SINRs

17. Simulation results … • Multi-user diversity, channel variations: • THP versus SNR for 2 and 8 users

18. Simulation results … • Multi-user diversity, channel variations: • BER versus SNR for 2 and 8 users

19. Simulation results … • Prediction quality, multi-user diversity, channel variation: • THP versus number of users (19 dB)

20. Simulation results … • Prediction quality, multi-user diversity, channel variation: • BER versus number of users (19 dB)

21. Simulation results … • Prediction quality, multi-user diversity, channel variation: • THP versus number of users (10 dB)

22. Simulation results … • Prediction quality, multi-user diversity, channel variation: • BER versus number of users (10 dB)

23. Simulation results … • TDMA/OFDMA versus use of TDMA: • THP versus number of users (19dB)

24. Summary • An adaptive transmission based on TDMA/OFDMA using multiuser scheduling is investigated. • Predictive adaptation to the short-term fading and frequency-domain channel variability leads to significant multi-user diversity gain. • With TDMA instead of TDMA/OFDMA, only half of these gains are realized for channels with Urban Macro scenarios. • Predictive adaptation can use MC rate boundaries adjusted so that BER constraints are fulfilled in the presence of SINR prediction uncertainty.

25. Summary… • Feasibility of adaptive transmission is limited by prediction accuracy. • Prediction accuracy is determined by SINR and terminal velocity. • For realistic SINR values, transmission at 50 km/h is feasible at 5 GHZ in FDD DL. • A solution to reduce the required feedback rate: • To feed back the required SINR and source code it by a combination of transform coding in the frequency direction and sub-sampling in the time direction.