Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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.

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 4 FDD downlink and uplink structure Chunk BW T chunk 8 sub-carriers 6 T OFDM time freq FDD downlink FDD uplink OOOOOOOOOOOOOOOO D D P U U P C O: overlapping pilots C: DL control feedback P: pilots symbols D: DL control symbols U: UL control symbols

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 5 Timing events in DL/UL transmission DLUL DL OOOOOOOOOOOOOOOO C D D P U U P 1. DL control symbols: Report which present chunks belong to which flows 2. DL pilot symbols: Used for channel prediction Used for channel estimation 3. UL control symbols: Report which next UL chunks appointed to which uplink flows 4. Pilot symbols: Used for coherent detection And updating predictor states UL OOOOOOOOOOOOOOOO C 6. UL overlapping pilot symbols: Used for prediction 5. DL control feedback symbols: Carry DL channel prediction report Dl prediction horizon: 2.5X0.3372ms=0.843ms UL prediction horizon: 2.5X0.3372ms=0.843ms

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 7 Channel prediction … SINR and prediction horizon limit at 5 GHz downlink: 30 km/h50 km/h70 km/h <0 dB, dB, dB, 0.273

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 8 Channel prediction … SINR and prediction horizon limits at 5 GHz uplink: 30 km/h50 km/h70 km/h <0 dB, dB, dB, km/h50 km/h70 km/h 3.5 dB, dB, dB, users8 users

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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.

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 11 Link adaptation … BER performance of MC schemes for perfect and imperfect prediction (NMSE=0.1)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 12 Link adaptation … Variation of rate limits of MC schemes with prediction quality: SNR=10 dB and TBER=0.001

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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.

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 15 Compression of feedback information … THP as a function of feedback rate: ITU VA channels, v=50 km/h, sub-sampling factor of 2 1 user 5 users 10 users

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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 Center frequency5.0+/ GHz Number of OFDM sub-carriers1024 FFT BW20 MHz Signal BW16.25 MHz paired Number of used sub-carriers832 Sub-carrier spacing19531 Hz OFDM symbol length (exc. CP)51.20 microseconds Cyclic prefix (CP) length5.00 microseconds Physical chunk size156.24kHz x microseconds Chunk size in symbols8 x 6=48

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 17 Simulation results … Multi-user diversity, channel variations: THP versus SNR for 2 and 8 users

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 18 Simulation results … Multi-user diversity, channel variations: BER versus SNR for 2 and 8 users

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 19 Simulation results … Prediction quality, multi-user diversity, channel variation: THP versus number of users (19 dB)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 20 Simulation results … Prediction quality, multi-user diversity, channel variation: BER versus number of users (19 dB)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 21 Simulation results … Prediction quality, multi-user diversity, channel variation: THP versus number of users (10 dB)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 22 Simulation results … Prediction quality, multi-user diversity, channel variation: BER versus number of users (10 dB)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 23 Simulation results … TDMA/OFDMA versus use of TDMA: THP versus number of users (19dB)

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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.

Event: CUBAN/WIP Workshop - Tunisia Date: May 2005 Slide 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.