International Technology Alliance In Network & Information Sciences International Technology Alliance In Network & Information Sciences 1 Cooperative Wireless Networks: From Radio to Network Protocol Designs May 29, 2009 by Zhengguo Sheng Supervisor: Prof. Kin K. Leung

2 Outline  Introduction Current Research Conclusion

Introduction Cooperative diversity is a cooperative multiple antenna techniques which exploits user diversity by decoding the combined signal of the relayed signal and the direct signal in wireless multi-hop networks. 3

motivation for cooperative diversity 4 Motivation for ad-hoc networks with cooperative transmission –Wireless links are unreliable due to multi-path propagation –Spatial diversity is bandwidth efficient to combat fading –Spatial diversity is difficult to achieve due to processing complexity, power consumption,... Solution: Cooperative Transmission –Allow users to share their antennas cooperatively to assist each other for successful reception Advantages of cooperative transmission: Virtual antenna array –Boosted reception reliability –Achieved higher data rates –Bandwidth efficient and increased coverage

A simple example of cooperative transmission 5 Normalized TX power with or without cooperative transmission (CT). The data rate is set as R = 0.1 bit/s/Hz, and the prefixed required outage probability is P=10%. Two sources are located at (−5, 0) and (−5, 0).

6 Outline Introduction  Current Research  Quality-of-Service Routing Algorithm for Wireless Cooperative Networks  Distributed and Power Efficient Routing in Wireless Cooperative Networks  Interference Subtraction with Supplementary Cooperation in Wireless Cooperative Networks Conclusion

7 QoS Routing Algorithm Algorithm description –Select the best relay and establish a one-hop cooperative route from source to destination and compare its ETE (End-to-end) BER with the target BER –If this BER is larger than target BER, identify the link with the highest BER along the route and improve its BER performance by selecting a new relay –Repeat second stage, until the ETE BER is no larger than target BER, then the cooperative route is finalized Source Destination A Simple Network Scenario [1] Z. Sheng, Z. Ding and K. K. Leung, "On the Design of a Quality-of-Service Driven Routing Protocol for Wireless Cooperative Networks", proc. of IEEE Vehicular Technology Conference (VTC), Singapore, MAY 2008.

8 Routing Comparison between Proposed Algorithm and DV Algorithm Compared with 9 hops and 10% ETE BER of Distance-Vector (DV) algorithm, our proposed algorithm (5 hops and 3% end-to-end BER) shows better performance

9 BER Performance Comparison with DV Algorithm Under same number of hops, proposed routing algorithm can achieve much better error performance than DV algorithm as well as the scheme without relay transmission As the number of hops increases in the route, the ETE BER of proposed algorithm is reduced correspondingly

ROUTING PERFORMANCE EVALUATION 10 Theorem1: For infinitely dense network where node exists at any location, the upper bound BER for the proposed routing with N hops is proportional to, where A, being perfect power of 2, is the largest integer that smaller than the total number of hops N and k is the pass loss exponent. The cooperative links of the optimal routing are uniformly distributed along the line between the source and the destination node The performance of the proposed algorithm closes to optimal. [2] Z. Sheng, Z. Ding, K. K. Leung, D. L. Goeckel and D. Towsley, "Error Performance Bound for Routing Algorithms in Wireless Cooperative Networks", proc. of The Second Annual Conference of The International Technology Alliance (ACITA 2008), UK.

11 Outline Introduction  Current Research  Quality-of-Service Routing Algorithm for Wireless Cooperative Networks  Distributed and Power Efficient Routing in Wireless Cooperative Networks  Interference Subtraction with Supplementary Cooperation in Wireless Cooperative Networks Conclusion

12 Transmission Power Optimization of Cooperative Link Observations –Both source and relay are assumed so far to transmit at the same Tx power –One can further reduce total Tx power to achieve a given target BER Source Destination Relay Cooperative Link Question? Can we do better to minimize Ps+Pr ? [3] Z. Sheng, Z. Ding and K.K. Leung, "Distributed and Power Efficient Routing in Wireless Cooperative Networks", Proc. of IEEE International Conference on Communications, ICC 2009.

13 Transmission Power Optimization Tx Power Optimization with a target ETE BER (Outage probability Using the Kuhn-Tucker condition, the minimum Tx power can be shown as where where R=data rate, =noise spectral density and B=bandwidth)

Simulation Result Power Reduction for CL 14 source destination 50 Relay candidates Network Topology Relay randomly placed in the 100m *100m square Average power reduction for all relay nodes is 82.73% and 21.22%, compared with two-hop transmission and MPCR, respectively …… … 100 meters …

Routing Performance Evaluation 15 The total power consumption of our proposed routing algorithm can reduce by a couple dB compared to the existing cooperative routing algorithms.

16 Outline Introduction  Current Research  Quality-of-Service Routing Algorithm for Wireless Cooperative Networks  Distributed and Power Efficient Routing in Wireless Cooperative Networks  Interference Subtraction with Supplementary Cooperation in Wireless Cooperative Networks Conclusion

Motivation for Supplementary Cooperation Observations –Broadcast nature of wireless transmission can be further explored –Cooperation can be extended across the CLs 17 S1 S2 S3 S4 R1 R2 R3 Cooperation? Yes T2 T1T3T4 T5 T6 [4] Z. Sheng, Z. Ding and K. Leung, “Interference Subtraction with Supplementary Cooperation in Wireless Cooperative Networks”, Proc. of IEEE International Conference on Communications, ICC 2009.

Outage Probability of Supplementary Cooperation Channel Capacity: Outage Probability: By computing the limit, we have 18

BER Improvement with Supplementary Cooperation SC generates routes with a smaller number of hops and satisfactory BER when compared with CC 19

Motivation for Interference Subtraction Observations –No interference is considered so far –Concurrent transmissions harm BER performance –One can further reduce interference from prior information 20 S1 S2 S3 R1 R2 R3 T1T2T3T4T5T6 S1(1) R1(1) S2(1) R2(1)S3(1)R3(1) S1(2) S4 T1T2T3T4T5T6T7 S1(1) R1(1) S2(1) R2(1)S3(1)R3(1) S1(2) R1(2) S2(2) S4(1) R2(2) S1(3)

Linear Network Analysis 21 A five-node linear network Assumption: Transmission range=1; Interference range=2; Interference free, d>2 Each node successfully receives a message on an average in every two time slots, the average throughput for direct transmission with interference subtraction is

22 Linear Network Analysis A five-node linear network For conventional cooperative transmission: a message on an average requires three time slots to be received, the average throughput is For supplementary cooperative transmission: The average throughput is 24% 42%

23 Interference Effects on BER Performance Channel resource reuse factor: spatial frequency reuse for scheduling Link throughput can be increased without bring in significant BER Trade-off between throughput, reuse factor and end-to-end BER Link throughput is the desired transmission rate is the reuse factor

Conclusion 24 What we have done 1)Optimal solution: QoS routing algorithm for cooperative networks 2)Interference effects on BER performance 3)Transmission power optimization 4)Throughput analysis Future works 1)Delay analysis 2)Multi-QoS solution; more insights on BER, delay and throughput 3)System performance for a general network scenario (stochastic geometry)

Thank you 25