Energy Harvesting Cognitive Radio With Channel-Aware Sensing Strategy
作者： Jeya J , Sanket S. Kalamkar , Adrish Banerjee
DOI: 10.1109/LCOMM.2014.2323240
关键词: Computer network 、 Partially observable Markov decision process 、 Mathematical optimization 、 Computer science 、 Transmission (telecommunications) 、 Communication channel 、 Throughput (business) 、 Cognitive radio 、 Throughput 、 Fading 、 Energy (signal processing)
摘要: An energy harvesting cognitive radio scenario is considered where a secondary user (SU) with finite battery capacity opportunistically accesses the primary (PU) channels. The objective to maximize throughput of SU under neutrality constraint and fading channel conditions in single-user multi-channel setting. A selection criterion based on probabilistic availability SU, conditions, network's belief state proposed, which chooses best subset channels for sensing, yielding higher throughput. We construct channel-aware optimal myopic sensing strategies Partially Observable Markov Decision Process framework proposed criterion. effects errors collisions between PU latter are studied. It shown that there exists trade-off transmission duration lost collisions.
harvard.edu
arxiv.org
128.84.21.199参考文章(11)
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