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Active interference restriction in OFDM-based cognitive radio network using genetic algorithm

机译:基于遗传算法的基于OFDM的认知无线电网络的有源干扰限制。

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In OFDM based cognitive radio networks, minimizing the interference caused to the primary user (PU) by the leakage emission of secondary users (SUs) is a great challenge. In this paper, we propose an interference restriction scheme using the additive signal side-lobe reduction technique and genetic algorithm (GA) in CR-OFDM systems. Additive signal side-lobe reduction technique is based on adding a complex array to modulated data symbols in the constellation plane for sidelobe reduction in OFDM system. In the proposed method, GA generates optimum additive signal which can effectively reduce the SU out-of-band (OOB) signal interference and consequently strives to keep the interference below a tolerable limit pre-defined by PU. The results show that the side-lobes of the OFDM-based SU signal can be reduced by up to 35dB and the PU interference tolerable limit can be satisfied.
机译:在基于OFDM的认知无线电网络中,最大限度地减少由次级用户泄漏(SUS)的泄漏发出对主用户(PU)造成的干扰是一个很大的挑战。在本文中,我们在CR-OFDM系统中提出了一种利用添加信号侧瓣减少技术和遗传算法(GA)的干扰限制方案。添加剂信号侧瓣减少技术基于在OFDM系统中添加复数阵列以在星座平面中的调制数据符号进行调制数据符号。在该方法中,GA产生最佳的添加剂信号,其能够有效地降低苏带外(OOB)信号干扰,因此致力于将干扰保持低于PU预定限定的可容许极限。结果表明,基于OFDM的SU信号的侧瓣可以减少高达35dB,并且可以满足PU干扰可容许限制。

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