基于中继选择和功率分配的非再生认知无线网络信噪比最大化

K. Sultan, I. Qureshi, M. Zubair
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引用次数: 9

摘要

在保持对主用户干扰约束的同时实现信噪比最大化是认知无线电网络(crn)的关键挑战。协作通信是利用空间多样性实现这一目标的一种很有前途的技术。在底层频谱共享环境下,考虑了一种由一个源-目的对和多个中继组成的基于放大转发的认知中继网络,并解决了中继选择和中继功率分配问题。在这种情况下,我们制定了一个优化问题,目的是在对PU的干扰功率约束和单个中继的发射功率约束下,使次要目的地的信噪比(SNR)最大化。与单一中继选择方法相比,我们的中继选择方案允许多个中继进行合作,而单一中继选择方法会损害空间多样性。我们用人工蜂群(ABC)来解决优化问题。该算法具有较低的计算复杂度,仿真结果证明了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SNR maximization through relay selection and power allocation for non-regenerative Cognitive Radio Networks
SNR maximization while adhering to interference constraint towards primary users is a key challenge in Cognitive Radio Networks (CRNs). Cooperative communication is a promising technique to achieve this goal by exploiting spatial diversity. We consider an Amplify-and-Forward based cognitive relay network comprising one source-destination pair and multiple relays in underlay spectrum sharing environment and solve the problem of relay selection and power allocation to the selected relays. In this scenario, we formulate an optimization problem aiming to maximize the signal-to-noise ratio (SNR) at the secondary destination under interference power constraint towards the PU as well as individual relay's transmit power constraint. Our relay selection scheme allows more than one relay to cooperate in contrast to single relay selection methods which compromise on spatial diversity. We solve our optimization problem using Artificial Bee Colony (ABC). The proposed algorithm has low computational complexity and its effectiveness is proved through simulation results.
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