Distributed Power Control for Delay Optimization in Energy Harvesting Cooperative Relay Networks

作者：Hakami Vesal; Dehghan Mehdi

来源：IEEE Transactions on Vehicular Technology, 2017, 66(6): 4742-4755.

DOI：10.1109/TVT.2016.2610444

• Bursty traffic
• cooperative relaying
• energy harvesting (EH)
• power control
• reinforcement learning
• stochastic game
• wireless communication

We consider cooperative communications with energy harvesting (EH) relays and develop a distributed power control mechanism for the relaying terminals. Unlike prior work, which mainly deals with single-relay systems with saturated traffic flow, we address the case of bursty data arrival at the source cooperatively forwarded by multiple half-duplex EH relays. We aim at optimizing the long-run average delay of the source packets under the energy neutrality constraint on the power consumption of each relay. While EH relay systems have been predominantly optimized using either offline or online methodologies, we take on a more realistic learning-theoretic approach. Hence, our scheme can be deployed for real-time operation without assuming acausal information on channel realizations, data/energy arrivals as required by offline optimization, or relying on precise statistics of the system processes, as is the case with online optimization. We formulate the problem as a partially observable identical payoff stochastic game (PO-IPSG) with factored controllers in which the power control policy of each relay is adaptive to its channel and energy states as well as to the state of the source buffer. We equip each relay with a reinforcement learning procedure and prove that the parallel execution of this procedure is convergent to (at least) a locally optimal solution of the formulated PO-IPSG. The proposed algorithm operates without explicit message exchanges between the relays, while inducing only little source-relay signaling overhead. By simulation, we contrast the delay performance of the proposed method against existing heuristics for throughput maximization. It is shown that compared with these heuristics, the systematic approach adopted in this paper has a smaller suboptimality gap once evaluated against a centralized optimal policy armed with perfect statistics.

• 出版日期2017-6