A Game Theoretic Approach for Interuser Interference Reduction in Body Sensor Networks

Abstract

As a kind of small-scale cyber-physical systems (CPSs), body sensor networks (BSNs) can provide the pervasive, long-term, and real-time health monitoring. A high degree of quality-of-service (QoS) for BSN is extremely required to meet some critical services. Interuser interference between different BSNs can cause unreliable critical data transmission and high bite error rate. In this paper, a game theoretic decentralized interuser interference reduction scheme for BSN is proposed. The selection of the channel and transmission power is modeled as a noncooperative game between different BSNs congregating in the same area. Each BSN measures the interference from other BSNs and then can adaptively select the suitable channel and transmission power by utilizing no-regret learning algorithm. The correctness and effectiveness of our proposed scheme are theoretically proved, and the extensive experimental results demonstrate that the effect of inter-user interference can be reduced effectively with low power consumption.