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Sidelobe suppression for OFDM based cognitive radio systems using genetic algorithm for subcarrier weighting

机译:基于遗传算法的子载波加权的基于OFDM的认知无线电系统旁瓣抑制

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Orthogonal frequency division multiplexing (OFDM), because of its different advantages, has been proposed as the enabling modulation technology for cognitive radios. However, the high sidelobes of the subcarriers are a major disadvantage that result in out-of-band radiation (OOB) causing interference to adjacent licensed users. Subcarrier weighting is an efficient technique for suppressing these sidelobes. This paper proposes the genetic algorithm to solve the subcarrier weighting technique's optimization problem that gives the optimum weight vector for sidelobe suppression. The genetic algorithm calculates the weights of the OFDM subcarriers in an optimized way such that the sidelobes of these subcarriers interfere destructively with each other, resulting in a smooth signal in the optimization range thus the sidelobes are suppressed and minimal interference is offered to adjacent users.
机译:正交频分复用(OFDM),由于其不同的优势,已被提出作为认知无线电的使能调制技术。但是,副载波的高旁瓣是一个主要缺点,导致带外辐射(OOB)对相邻许可用户造成干扰。副载波加权是抑制这些旁瓣的有效技术。提出了一种遗传算法来解决子载波加权技术的优化问题,该算法给出了抑制旁瓣的最佳加权矢量。遗传算法以优化的方式计算OFDM子载波的权重,从而使这些子载波的旁瓣相互之间具有破坏性干扰,从而在优化范围内产生平滑信号,从而抑制了旁瓣,并为相邻用户提供了最小的干扰。

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