A Game Theory Inspired Channel Allocation Policy for Multi-Radio Pervasive Ad Hoc Communications

The impressive increase of innovative wireless communication technologies and applications represents nowadays a key approach to enable pervasive communications environments. In particular, the emerging paradigms of the Internet of Things and Capillary Networks offer effective ways to get devices connected. This has triggered the development of effective methodologies and procedures to allow an unlimited number of devices to exchange information mainly in an autonomous mode. However, it is a well known concept that wireless networks capacity usually decreases with the number of nodes. In particular, in order to improve the throughput scalability, a promising approach is that of resorting to the use of multiple radio interfaces at each node, in order to exploit spatial re-use of frequencies. Towards this end, game theory methodologies offer efficient approaches to solve the complex radio interfaces selection and allocation problems. This paper proposes a game theory inspired approach to efficiently select the number of radio interfaces to be used at each node site in order to lower the energy consumption and maximize the end-to-end (E2E) throughput of any communication on which the node is involved in. The good behaviour of the proposed approach is validated by provided theoretical framework and numerical results derived by considering different data packets wireless forwarding schemes.