Game-Theoretic Modeling and Analysis of Multi-Relay Selection in Energy-Harvesting Wireless Networks

In this paper, the problem of distributed multi-relay selection in energy-harvesting cooperative wireless networks is studied and modeled as an Indian Buffet Game (IBG). Particularly, the IBG is utilized to model the multi-relay selection decisions of network source nodes, while taking into account the negative network externality. Since the relays are energy-harvesting (and thus intermittently harvest random amounts of energy), the accumulated energy at each relay is unknown to the source nodes, leading to uncertain relays' energy states. In turn, a non-Bayesian learning algorithm is devised for source nodes to learn the relays' energy states. After that, a distributed best-response multi-relay selection (BR-MRS) recursive algorithm is proposed to allow source nodes to make multi-relay selections, while guaranteeing subgame perfect Nash equilibrium. Simulations results are presented to verify the efficacy of the proposed algorithm when compared to other multi-relay selection schemes, and illustrate that it yields comparable rate improvement (and utility) to the centralized multi-relay selection.