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Start Over Author "Huang, Yu-Li" Publisher elsevier bv
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5. Optimal energy efficiency capacity under joint design of sensing and transmission duration for cognitive radio system

Author

Xiao-dong Xu, Bao-xue Wu, and Huang-yu Li

Subjects
Mathematical optimization, Optimization problem, Computer Networks and Communications, Computer science, Iterative method, Brute-force search, Spectrum management, Cognitive radio, Transmission (telecommunications), Signal Processing, Energy (signal processing), Simulation, Information Systems, Efficient energy use
Abstract

Due to its opportunistic spectrum sharing capability, cognitive radio (CR) has been proposed as a fundamental solution to alleviate the contradiction between spectrum scarcity and inefficient utilization of licensed spectrum. In CR system (CRS), to efficiently utilize the spectrum resource, one important issue is to allocate the sensing and transmission duration reasonably. In this paper, the evaluation metric of energy efficiency, which represented the total number of bits that were delivered with per joule of energy consumed, is adopted to evaluate the proposed scheme. We study a joint design of energy efficient sensing and transmission durations to maximize energy efficiency capacity (EEC) of CRS. The tradeoff between EEC and sensing and transmission durations are formulized as an optimization problem under constraints on target detection probability of secondary users (SUs) and toleration interference threshold of primary users (PUs). To obtain the optimal solution, optimizing sensing duration and transmission duration will be first performed separately. Then, a joint optimization iterative algorithm is proposed to search the optimal pair of sensing and transmission durations. Analytical and simulation results show that there exists a unique duration pair where the EEC is maximized, and that the EEC of the proposed joint optimization algorithm outperforms that of existed algorithms. Furthermore, the simulation results also reveal that the performance of the proposed low complexity iterative algorithm is comparable with that of the exhaustive search scheme.

Published
2013

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