利用遗传和萤火虫算法减少认知无线电网络的干扰

A. Elahi, I. Qureshi, Mehreen Atif, N. Gul
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引用次数: 12

摘要

认知无线电(CR)是一种新兴的无线通信技术,它能够巧妙地利用主用户的空闲频谱。非连续正交频分复用(NCOFDM)多载波系统被认为是CR物理层的合适候选,但由于其高副瓣,其高带外辐射(OOB)会影响其频谱共享能力。在本文中,我们提出了两种搜索算法:遗传算法(GA)和萤火虫算法(FFA)来估计抵消子载波(cc)的幅度。这些cc被插入到使用的NCOFDM信号的两侧以抵消旁瓣。仿真结果表明,与文献中已有的方法相比,本文提出的算法具有更好的旁瓣抑制效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Interference reduction in Cognitive radio networks using Genetic and Firefly Algorithms
Cognitive radio (CR) is the novel technology in wireless communication, which has an ability to use the vacant spectrum of primary user smartly. Non Contiguous orthogonal frequency division multiplexing (NCOFDM), a multicarrier system is considered as the appropriate candidate for CR physical layer, but due to its high sidelobes it suffers from high out of band (OOB) radiation, that can affect its spectrum sharing capability. In this paper, we proposed two search algorithms: Genetic Algorithm (GA) and Firefly algorithm (FFA) for estimating the amplitudes of the Cancellation subcarriers (CCs). These CCs are inserted on either side of the used NCOFDM signal to cancel the sidelobes. Simulation results show that better sidelobe reduction is achieved by the proposed algorithms as compared to the existing techniques in the literature.
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