Distributed Opportunistic Scheduling for Wireless Ad-Hoc Networks with Block-Fading Model
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In this paper, we study a distributed opportunistic scheduling problem to exploit the channel fluctuations in wireless ad-hoc networks. In this problem, channel probing is followed by a transmission scheduling procedure executed independently within each link in the network. We study this problem for the popular block-fading channel model, where channel dependencies are inevitable between different time instances during the channel probing phase. Different from existing works, we explicitly consider this type of channel dependencies and its impact on the transmission scheduling and hence the system performance. We use optimal stopping theory to formulate this problem, but at carefully chosen time instances at which effective decisions are made. The problem can then be solved by a new stopping rule problem where the observations are independent between different time instances. Since the stopping rule problem has an implicit horizon determined by the network size, we first characterize the system performance using backward induction. We develop one recursive approach to solve the problem and show that the computational complexity is linear with respect to network size. Due to its computational complexity, we present an approximated approach for performance analysis and develop a metric to check how good the approximation is. We characterize the achievable system performance if we ignore the finite horizon constraint and design stopping rules based on the infinite horizon analysis nevertheless. We present an improved protocol to reduce the probing costs which requires no additional cost. We characterize the performance improvement and the energy savings in terms of the probing signals. We show numerical results based on our mathematical analysis with various settings of parameters.