1. History-based Adaptive Modulation for a Downlink Multicast Channel in OFDMA systems Haibo Wang, Hans Peter Schwefel and Thomas Skjodeberg Toftegaard Center for Teleinfrastructure Aalborg University WCNC 2008

2. Outline  Introduction  System model  Adaptive modulation strategies  Simulation  Conclusion

3. Introduction  The next generation mobile cellular networks are expected to transmit rich multi-media services live video/audio streaming, live video/audio streaming, online mobile gaming online mobile gaming music download music download  Many of these services require large transmission bandwidth

4. Introduction  Most efficient way Wireless Multicast [1] Wireless Multicast [1]  How to optimize the efficiency and reliability of wireless Multicast transmissions s r2 r3 r1 … Shared multicast channel

5. Introduction  Some related works utilized advanced radio transmission techniques [2][3][4] MIMO MIMO Beam-forming Beam-forming space-time coding space-time coding  Some others utilized subchannel allocation in multi-carriers systems[5][6][7][8] adaptation techniques of multicarriers adaptation techniques of multicarriers e.g. OFDM 、 OFDMA e.g. OFDM 、 OFDMA

6. Introduction  OFDMA Channel State Information (CSI) Channel State Information (CSI) Adaptive Modulation (AM) Adaptive Modulation (AM)  Goal multicast transmission reliability multicast transmission reliability keep the data rate keep the data rate

7. System model i =1,…,N is the index of multicast receivers j is the index of OFDM subcarriers within a multicast subchannel BS ms … 16QAM 64QAM Modulation scheme KMKMKMKMBPSK K0K0K0K0 4QAM K1K1K1K1 16QAM K2K2K2K2 64QAM K3K3K3K3 256QAM K4K4K4K4

8. System model  The optimization target Maximize the downlink data rate Maximize the downlink data rate keep an average BER constraint keep an average BER constraint

9.  Reward function Global performance metric Global performance metric System model number of mobiles average BER constraint for i Normailized average user Goodput per session BER constraint for N

10. Adaptive modulation strategies  Best Reward strategy with Fixed BER threshold  Best Reward strategy with Adaptive BER threshold  BPSK with turn-off Strategy

11. Best Reward strategy with Fixed BER threshold  Example 10db5db10db 20db15db15db 30db25db20db i j mobile subcarrier0.30.20.50.50.10.6 0.70.30.1 BER(16QAM,SNRi,j) i j T’(16QAM)=K 16QAM /K 256QAM *1/3(0.7+0.5+0.3)

12. Best Reward strategy with Adaptive BER threshold

14. Adaptive BER threshold Algorithm  Variables and parameters

15. Adaptive BER threshold Algorithm BER too good, loose threshold BER break boundary, tight threshold

16. BPSK with turn-off Strategy   selects BPSK   turn off the subcarrier j when min {SNR i,j }

17. Simulation

18. Simulation

19. Simulation

20. Simulation

21. Conclusion   Adaptive Modulation shows its capacity to improve the spectral efficiency   Future work build analytical models to reveal achievable goodput upper-boundary BER constraint joint power and rate adaptation