Interference and priority aware resource allocation in coexisting WBANs using game models

Abstract

Wireless body area networks (WBANs) have become an integral part of our health monitoring system. However, the specific challenges offered by a dense co-existence of heterogeneous WBANs have not been properly addressed. The interference between the coexisting WBANs which cause throughput degradation and energy wastage can be mitigated by suitable channel and slot allocations. In this work, a Stackelberg game model with pricing is used for resource scheduling among multi-class WBANs. The access points (APs) act as leaders who decide the prices to be paid by the normal WBAN users for reusing the resources allocated to the critical WBAN users. The normal WBAN users act as followers which use the pricing information and a distributed learning algorithm that guarantees Pareto-optimal solution. As a benchmark for comparison purpose, we propose a centralized resource scheduling which is formulated as an optimization problem where the objective is to maximize system throughput while guaranteeing the quality of service (QoS) requirements of multi-class WBANs. To efficiently solve this problem, a column generation method is proposed. Numerical results are provided to show the efficiency and effectiveness of the proposed game model.