Optimal Power Allocation and AP Deployment in Green Wireless Cooperative Communications

1. Optimal Power Allocation and AP Deployment in Green Wireless Cooperative Communications • Xiaoxia Zhang • x79zhang@bbcr.uwaterloo.ca • Department of Electrical and Computer Engineering • University of Waterloo

2. Outline • Introduction • System Model • Power Allocation for a Single-User Link • AP Deployment • Conclusions and Future Work

3. Introduction • Global Emission of CO2 in 2011 - Increased by 3% - Reaching an all-time high of 34 billion tonnes SAVE OUR ENVIRONMENT!!! Figure 1. Global Emission of CO2 in 2011

4. Sustainable Energy • Eco-friendly renewable energy: solar, wind, tide, etc. • Occupied 16.7 % of global energy in 2011 Figure 2. Renewable Energy Share of Global Final Energy Consumption, 2011.

5. Green Technology in Wireless Communications • In wireless communications - Up to 90% of power consumption in BSs - Energy cost is high and increasing • Green wireless networks: network devices powered by sustainable energy - Example: Huawei • Solar-powered base stations deployed over 1500 sites in over 30 countries and regions • Operation cost reduced over 60% • Carbon footprints reduced over 40% Figure 3. A Green Base Station

6. Motivation • Characteristics of Sustainable Energy - Variable or intermittent in its capacity - Highly dependent on the location and weather • Fulfillment of users’ QoS demand is challenging. - Introduction of cooperative communication - More efficient green wireless network • Device deployment • Resource allocation

7. Objective In a WLANnetwork where green APs are deployed, we would like to maximize the overall throughput by jointly allocating transmitting power and deploying the green APs, subject to the harvested energy constraint.

8. Outline • Introduction • System Model • Power Allocation for a Single-User Link • AP Deployment • Conclusions and Future Work

9. System Model • A wireless local area network (WLAN) where a green AP is deployed. • Nodes could communicate with each other in an ad hoc manner. • Transmission links are separated by TDMA. • AP can cooperate with the source nodes to transmit data to the destination. • n links in total. Figure 4. A green wireless cooperative communication network.

10. System Model • During each transmission period, only one source-destination pair (si,di) exists. AP • The AP functions as a relay node. • - Two relaying protocols: • Amplify-and-Forward • Decode-and-Forward need extra resources Easy to implement Noise cannot be eliminated Coding cost Noise free

11. Achievable Rate for Single-User Relay Channel • Information theoretic achievable rate relay decoding rate destination decoding rate • AWGN channel with path loss path loss exponent constant and identical for all links

12. Achievable Rate for Single-User Relay Channel • Noise variances received at the relay and at the destination are the same value. • Joint superposition encoding/decoding to maximize cooperation between source and relay. • Generation of two codes. + relay decoding rate destination decoding rate

13. Problem Formulation • Objective: maximize overall throughput under instant available power constraint. Links are scheduled by TDMA Power allocation on one link does not affect other links

14. Outline • Introduction • System Model • Power Allocation for a Single-User Link • AP Deployment • Conclusions and Future Work

15. Power Allocation for a Single-User Link • Objective: jointly determine , and to maximize the achievable rate. • Note: optimum is achieved when destination decoding rate = relay decoding rate relay decoding rate destination decoding rate

16. Synchronous Case • Destination decoding rate is the bottleneck. • Increase and reduce to balance. • Coherent transmission. Optimal power allocation is: Largest achievable rate is: relay decoding rate destination decoding rate

17. Asynchronous Case • Relay decoding rate is the bottleneck. • Source will set and . • Independent transmission. Optimal power allocation is: Largest achievable rate is: relay decoding rate destination decoding rate

18. Outline • Introduction • System Model • Power Allocation for a Single-User Link • AP Deployment • Conclusions and Future Work

19. AP Deployment • Optimal power allocation and maximum rate depends on the location of AP. Direct transmission without help of relay can achieve highest rate. Relay closer to the source Synchronous case achieves higher rate Relay closer to the destination Asynchronous case achieves higher rate

20. Optimal AP Deployment for a Single Link • Two local maximum Let , the two possible relay positions to maximize the throughput is the solutions to the following two equations: , ,

21. Optimal AP Deployment • Sustainable energy can only be exploited in some specific locations due to the availability and neighboring environment. • Several candidate AP locations are considered. • The optimal location can be decided based on the overall throughput which is calculated by

22. Simulation Results Synchronous Asynchronous Figure 5. Rate comparison of three power allocation schemes when and .

23. Simulation Results Figure 6. Achievable rate of a single user link with different AP locations.

24. Simulation Results • 100m×100m area • 30 candidate locations Figure 7. The overall throughput by our proposed AP deployment metric and random deployment method.

25. Outline • Introduction • System Model • Power Allocation for a Single-User Link • AP Deployment • Conclusions and Future Work

26. Conclusions and Future Work • In this paper, a single-user channel achievable rate maximization problem is formulated and the optimal power allocation scheme is derived. • A throughput upper bound of each single-user channel is attained and the optimal AP deployment is provided. • In the future, we will consider the dynamic charging and discharging buffer in the AP.

27. Thanks!