Fair rate control for cognitive multi-channel wireless ad hoc networks

Multi-channel wireless ad hoc networks enhance network capacity with the use of available channels in parallel but should strike a balance between maintaining network connectivity and maximizing utilization of different channels. Also, a promising wireless multi-channel ad hoc network should be cognitive to interference from various wireless devices operating on industrial, scientific, and medical bands effectively by scavenging less loaded channels dynamically using periodic spectrum sensing and distributed channel selection algorithm. In this paper, we study cross-layer fair rate control problems for hybrid channel assignment-based multi-channel ad hoc networks in the cognitive context. We first identify two inherent constraints which are specific to multi-channel multi-radio wireless ad hoc networks and primary user interference. We then formulate a fair rate control problem by exploiting the network utility maximization framework and propose a price-based distributed solution. We investigate in detail the convergence property of the distributed solution via simulation on a grid topology. We also show its convergence in adaptation to the change in primary user interference in the cognitive context. We present a performance comparison study with a generic class of existing works in the literature.