Optimization of Spectrum Sensing Period in Cognitive Radio Networks Based on GA

Abstract:

In Cognitive Radio Networks (CRN), an important issue associated with MAC-layer sensing is how often the availability of licensed channels should be sensed. To solve this issue in multi-channel environment, we address how to maximize the discovery of spectrum opportunities by setting a set of reasonable sensing-periods. Based on alternating renewal theory we develop an channel-usage pattern estimation method, and derived the states transition matrix by discrete-time Markov process. At last, we proposed an objective function of spectrum sensing efficiency, and solved the multi-objective optimization problem by improved Genetic Algorithms (GA). Our simulation results demonstrate the efficiency of the objective function and the significant performance of the improved GA. The sensing-period vector we derived discovers more than 80 percent of the analytical maximum of discoverable spectrum-opportunities in six-channel environment, which is shown to discover up to 30% more than the method that sensing each channel with the same period.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 2448-2451
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.2448
• Online since: September 2013
• Authors: Yang Liu, Ying Cui, Ou Li
• Keywords: Cognitive Radio Network, Genetic Algorithm (GA), Multi-Channel, Sensing Period

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