Assessing the appropriateness of using markov decision processes for RF spectrum management
Proceedings of the 16th ACM international conference on Modeling, analysis & simulation of wireless and mobile systems
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Modern embedded systems are increasingly likely to be distributed across multiple devices and platforms that must interact with high precision across wireless networks. Traditional ways of managing the wireless radio spectrum suffer from two fundamental limitations, which the research presented in this paper addresses: (1) spectrum is divided a priori into static coarse-grained partitions without reference to details of particular applications, and (2) partitions are non-overlapping, which although beneficial to reduce interference prevents a much greater utilization of the spectrum through carefully allowing overlap of spectrum allocations. To overcome these limitations, we propose an approach to spectrum allocation based on dynamic allocation of diverse portions of the overall spectrum and overlapping allocations to increase utilization. This paper makes three main contributions to the state of the art in spectrum management for embedded systems: (1) it examines how memory management techniques such as Knuth's buddy algorithm can be applied to spectrum management, in the face of transmission failures that may arise from the physical environment, (2) it extends that approach to consider transmission failures resulting from interference, when overlapping regions of spectrum are allocated to increase utilization, and (3) it presents results of simulation experiments we conducted to evaluate those approaches, which demonstrate their efficacy and suggest future extensions based on them.