Using Biologically-Inspired Foraging Approach for Spectrum Reconfiguration in Distributed Cognitive Radio Network

O. Oki, P. Mudali, M. Adigun, T. Olwal
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引用次数: 2

Abstract

The dynamic spectrum management techniques have been introduced to address the current Radio Frequency bands inefficiency challenges. Cognitive Radio (CR) technology has been regarded as the most promising technology in the dynamic spectrum management area. One of the major aspects of the spectrum management is the decision making ability of CR users. The dynamic reconfiguration of both the operating frequency and channel bandwidth in a distributed CR network has not received sufficient attention despite their importance in spectrum decision making. In this paper, we present a biologically-inspired optimal foraging model to address the dynamic reconfiguration of frequency and channel bandwidth problems in a distributed cognitive radio network. One of the main advantages of biologically-inspired foraging model is its analytical simplicity and optimum solution. The average channel switching time, successful transmission probability, network throughput and energy efficiency were measured. The MATLAB simulation results show that the proposed optimal foraging model can reduce the communication overhead, balance the communication performance and improve the energy efficiency, which in-turn will help to achieve optimal spectrum utilization.
基于生物启发的分布式认知无线电网络频谱重构方法
引入动态频谱管理技术来解决当前射频频段效率低下的挑战。认知无线电(CR)技术被认为是动态频谱管理领域中最有前途的技术。频谱管理的一个重要方面是用户的决策能力。分布式CR网络中工作频率和信道带宽的动态重构在频谱决策中具有重要意义,但却没有得到足够的重视。在本文中,我们提出了一个受生物学启发的最优觅食模型来解决分布式认知无线电网络中频率和信道带宽的动态重构问题。生物启发觅食模型的一个主要优点是其分析简单和最优解。测量了平均信道交换时间、成功传输概率、网络吞吐量和能源效率。MATLAB仿真结果表明,所提出的最优觅食模型可以降低通信开销,平衡通信性能,提高能源效率,从而有助于实现最优的频谱利用率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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