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EVM based rate maximized relay selection for cooperative cognitive radio networks

机译:基于EVM的速率最大化的中继选择合作认知无线电网络

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Cooperative relaying being a novel technique in cognitive radio (CR) communications promises enhanced performance for secondary users (SU) by exploiting spatial diversity. This paper proposes a cooperative framework for the rate maximized relay selection (RRS) based on error vector magnitude (EVM). EVM is the measure of error vector between received constellation points to the ideal ones. The problem is transformed to convex optimization (CO) problem for maximizing the capacity for both primary user (PU) and SU network in a interweave communication model. Simulation result reveals that PU can achieve higher capacity with cooperative relaying compared to the direct transmission and energy constraint of the cognitive radio network (CRN) is met by implementing RRS algorithm. Energy efficiency is improved up to 19% more than the conventional schemes. Furthermore, PU provides the opportunistic time gain (OTG) for those SU's that act as relay for its transmission. (C) 2019 Elsevier GmbH. All rights reserved.
机译:合作中继作为认知无线电(CR)通信的新技术,通过利用空间多样性,对二级用户(SU)的表现增强了增强的性能。本文提出了一种基于误差矢量幅度(EVM)的速率最大化中继选择(RRS)的合作框架。 EVM是接收星座之间的误差矢量的误差矢量点。该问题被转换为凸优化(CO)问题,用于最大化互通通信模型中的主要用户(PU)和SU网络的容量。仿真结果表明,与通过实现RRS算法满足认知无线电网络(CRN)的直接传输和能量约束,PU可以通过协作中继实现更高的容量。能量效率高达传统方案的增加高达19%。此外,PU为那些充当其传输的继电器提供机会主义的时间增益(OTG)。 (c)2019年Elsevier GmbH。版权所有。

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