An effective channel allocation algorithm to maximize system utility in heterogeneous DCB WLANs

Abstract

IEEE 802.11ac is a recent amendment that improves the system throughput to meet the rapidly growing data rate requirements of Wireless Local Area Networks (WLANs). One important technique adopted by 802.11ac is Dynamic Channel Bonding (DCB) that allows for the selection and combination of multiple contiguous basic channels in a single transmission. For a particular link, the adoption of wider bandwidth can offer it a higher data rate, while also makes it suffer from much severer competition with other links for wireless channel airtime occupation. Thus, there is a basic tradeoff between data rate and channel access opportunity for a link in DCB WLANs and it is then non-trivial to come up with an effective way to properly allocate the limited orthogonal basic channels to each WLAN and assign the corresponding primary channel. This paper attempts to explore the optimal channel allocation problem in a heterogeneous DCB network, in which all WLANs are operating under DCB while not all of them are within the carrier-sensing range (CSRange) of each other. In particular, we first introduce an analytical framework that uses Continuous Time Markov Chain (CTMC) model to analyze the throughput performance and present a CTMC construction algorithm to generate the Markov chain for any given heterogeneous DCB network. After that, we analyze the system utility under different channel allocation schemes and formulate an optimization problem with the target of maximizing the system utility, which is a concave and non-decreasing function of the achievable link throughputs. Due to the high complexity of the optimization problem, we design a heuristic and effective algorithm to find the near-optimal channel allocation that achieves good system utility for the heterogeneous DCB networks. Simulations validate that our proposed MIS-based channel allocation algorithm (MCAA) can achieve good performance in terms of both system utility and aggregate throughput under various network topologies and protocol parameter settings.