Conjecture-based channel selection game for delay-sensitive users in multi-channel wireless networks

In this paper, we study the problem of multi-user channel selection in multi-channel wireless networks. Specifically, we study the case in which the autonomous users deploy delay-sensitive applications. Existing centralized approaches result in efficient allocations, but require intensive message exchanges among the users (i.e. they are not informationally efficient). Current distributed approaches do not require any message exchange for collaboration, but they often result in inefficient allocations, because users only respond to their experienced contention in the network. Alternatively, in this paper we study a distributed channel selection approach, which does not require any message exchanges, and which leads to a system-wise Pareto optimal solution by enabling a foresighted user to predict the implications (based on their beliefs) of their channel selection on their expected future delays and thereby, foresightedly influence the resulting multi-user interaction. We model the multi-user interaction as a channel selection game and show how users can play an epsiv -consistent conjectural equilibrium by building near-accurate beliefs and competing for the remaining capacities of the channels. We analytically show that when the system has the foresighted user, this self-interested leader can deploy a linear belief function in each channel and manipulates the equilibrium to approach the Stackelberg equilibrium. Alternatively, when the leader is altruistic, the system will converge to the system-wise Pareto optimal solution. We propose a low-complexity learning method based on linear regression for the foresighted user to learn its belief functions.