Opportunistic Communication: From Theory to Practice

Transcription

1 Opportunistic Communication: From Theory to Practice David Tse Department of EECS, U.C. Berkeley March 9, 2005 Viterbi Conference

2 Fundamental Feature of Wireless Channels: Time Variation Channel Strength Time time-varying channel multipath fading large-scale channel variations time-varying interference

3 Traditional Approach to Wireless System Design Channel Strength Channel Strength Time Time time-varying channel constant channel Compensates for channel fluctuations.

4 Case Study: CDMA Systems Two main compensating mechanisms: 1. Channel diversity: time diversity via coding and interleaving frequency diversity via Rake combining, macro-diversity via soft handoff transmit/receive antenna diversity 2. Interference management: power control interference averaging

5 Case Study: CDMA Systems Two main compensating mechanisms: 1. Channel diversity: time diversity via coding and interleaving frequency diversity via Rake combining, macro-diversity via soft handoff transmit/receive antenna diversity 2. Interference management: power control interference averaging

6 What Drives this Approach? Channel Strength Channel Strength Time Time time-varying channel constant channel Main application is voice, with very tight latency requirements. Needs a consistent channel.

7 Opportunistic Communication: A Different View Transmit more when and where the channel is good. Exploits fading to achieve higher long-term throughput, but no guarantee that the channel is always there. Appropriate for data with laxer latency requirements.

8 Opportunistic Communication: A Different View Transmit more when and where the channel is good. Exploits fading to achieve higher long-term throughput, but no guarantee that the channel is always there. Appropriate for data with laxer latency requirements.

9 Opportunistic Communication: A Different View Transmit more when and where the channel is good. Exploits fading to achieve higher long-term throughput, but no guarantee that the channel is always there. Appropriate for data with laxer latency requirements.

10 Point-to-Point Fading Channels Capacity-achieving strategy is waterfilling over time. (Goldsmith and Varaiya 97)

11 0 / 1. Performance over Rayleigh Channel % & ')(+*-,) "!$# "!

12 Performance: Low SNR 3 C C awgn CSIR Full CSI SNR [db] At low SNR, capacity can be greater when there is fading.

13 Hitting the Peaks Near Optimal Allocation Optimal Allocation N 0 h[m] 2 1 λ N 0 h[m] 2 1 λ (a) P [m] Time m (a) Time m N 0 h[m] 2 N 0 h[m] 2 (b) P [m] 1 λ Time m 1 λ (b) Time m At low SNR, one can transmits only when the channel is at its peak. Primarily a power gain. In practice, hard to realize such gains due to difficulty in tracking the channel when transmitting so infrequently.

14 Hitting the Peaks Near Optimal Allocation Optimal Allocation N 0 h[m] 2 1 λ N 0 h[m] 2 1 λ (a) P [m] Time m (a) Time m N 0 h[m] 2 N 0 h[m] 2 (b) P [m] 1 λ Time m 1 λ (b) Time m At low SNR, one can transmits only when the channel is at its peak. Primarily a power gain. In practice, hard to realize such gains due to difficulty in tracking the channel when transmitting so infrequently.

15 Multiuser Opportunistic Communication Fading Channel Mobile User 1 User 2 Base Station User K (Knopp and Humblet 95, T 97)

16 Performance C sum [bits/s/hz] 8 K=16 AWGN CSIR Full CSI 6 4 K=4 K=2 K=1 2 SNR [db]

17 Multiuser Diversity Total average SNR = 0 db. 2.5 Total Spectral Efficieny in bps/hz Rayleigh Fading AWGN Channel Number of Users In a large system with users fading independently, there is likely to be a user with a very good channel at any time. Long term total throughput can be maximized by always serving the user with the strongest channel.

18 Multiuser Diversity: A More Insightful Look Requested rates in bps/hz Time Slots Independent fading makes it likely that users peak at different times. In a wideband system with many users, each user operates at low average SNR, effectively accessing the channel only when it is near its peak. In the downlink, channel tracking can be done via a strong pilot amortized between all users.

19 Multiuser Diversity: A More Insightful Look Requested rates in bps/hz Time Slots Independent fading makes it likely that users peak at different times. In a wideband system with many users, each user operates at low average SNR, effectively accessing the channel only when it is near its peak. In the downlink, channel tracking can be done via a strong pilot amortized between all users.

20 Multiuser Diversity: A More Insightful Look Requested rates in bps/hz Time Slots Independent fading makes it likely that users peak at different times. In a wideband system with many users, each user operates at low average SNR, effectively accessing the channel only when it is near its peak. In the downlink, channel tracking can be done via a strong pilot amortized between all users.

21 1x EV-DO s DownLink Data Fixed Transmit Power User 1 Measure Channel Request Rate Base Station User 2 Information theory suggests that resource should be scheduled in a channel-dependent way. Challenge is to exploit multiuser diversity while sharing the benefits fairly and timely to users.

22 1x EV-DO s DownLink Data Fixed Transmit Power User 1 Measure Channel Request Rate Base Station User 2 Information theory suggests that resource should be scheduled in a channel-dependent way. Challenge is to exploit multiuser diversity while sharing the benefits fairly and timely to users.

23 Symmetric Users 1500 symmetric channels requested rate (kbps) time slots Serving the best user at each time is also fair in terms of long-term throughputs.

24 Asymmetric Users 2500 asymmetric channels 2000 requested rate (kbps) t c time slots Want to serve each user when it is near its peak. A peak should be defined with respect to a latency time-scale t c.

25 Asymmetric Users 2500 asymmetric channels 2000 requested rate (kbps) t c time slots Want to serve each user when it is near its peak. A peak should be defined with respect to a latency time-scale t c.

26 Asymmetric Users 2500 asymmetric channels 2000 requested rate (kbps) t c time slots Want to serve each user when it is near its peak. A peak should be defined with respect to a latency time-scale t c.

27 Proportional Fair Scheduling (T 99) Schedule the user with the highest ratio R k /T k, where R k = current requested rate of user k T k = average throughput in past t c time slots

28 Performance Low mobility environment 800 Total throughput (kbps) latency time scale t c = 1.6s Average SNR = 0dB Fixed environment High mobility environment Number of users Fixed environment: 2Hz Rician fading with E fixed /E scattered = 5. Low Mobility environment: 3 km/hr, Rayleigh fading High mobility environment: 30 km/hr, Rayleigh fading

29 Channel Dynamics 1400 mobile environment 1400 fixed environment requested rate of a user (kbps) sec requested rate of a user (kbps) sec time slots time slots Channel varies faster and has more dynamic range in mobile environments.

30 Inducing Randomness Scheduling algorithm exploits the nature-given channel fluctuations by hitting the peaks. If there are not enough fluctuations, why not purposely induce them?

31 Dumb Antennas (Viswanath, T and Laroia 02) $!#" The information-bearing signal at each of the transmit antennas are multiplied by a random complex gain.

32 Inducing Randomness Channel Strength before opportunistic beamforming Channel Strength after opportunistic beamforming user 1 t t Channel Strength Channel Strength user 2 t t transmission times

33 Slow Fading: Opportunistic Beamforming user 1 user 2 Dumb antennas create a beam in random time-varying direction. In a large system, there is likely to be a user near the beam at any one time. By transmitting to that user, close to true beamforming performance is achieved.

34 Fast Fading antenna, Ricean Density antenna, Ricean Rayleigh Channel Amplitude Improves performance in fast fading Rician environments by spreading the fading distribution.

35 Overall Performance Improvement mobile fixed but with opp. beamforming total throughput (kbps) fixed latency time scale t c = 1.6s average SNR = 0 db number of users Mobile environment: 3 km/hr, Rayleigh fading Fixed environment: 2Hz Rician fading with E fixed /E scattered = 5.

36 Smart vs Dumb Antennas Space-time codes increase reliability of point-to-point links but decreases multiuser diversity gains. Dumb antennas add fluctuations to point-to-point links but increases multiuser diversity gains.

37 Smart vs Dumb Antennas Space-time codes increase reliability of point-to-point links but decreases multiuser diversity gains. Dumb antennas add fluctuations to point-to-point links but increases multiuser diversity gains.

38 Conclusions Implementation of a new point of view has to obey system constraints. The new point of view impacts rest of the system design and suggests new research problems. Interplay between theory and system is what makes communications research so fun!

39 Conclusions Implementation of a new point of view has to obey system constraints. The new point of view impacts rest of the system design and suggests new research problems. Interplay between theory and system is what makes communications research so fun!

40 Conclusions Implementation of a new point of view has to obey system constraints. The new point of view impacts rest of the system design and suggests new research problems. Interplay between theory and system is what makes communications research so fun!