Performance Analysis of a Novel Relay Selection Scheme for Wireless-Powered Cluster-Based Multi-Hop Cognitive Relay Networks

IF 8 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-11-13 DOI:10.1109/TCCN.2024.3496853
Hui Sun;Mort Naraghi-Pour;Yuwen Qian;Weixing Sheng;Yubing Han
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Abstract

In this paper, we study the performance of wireless-powered cluster-based multi-hop cognitive relay networks (MCRNs), where secondary nodes harvest energy from multiple dedicated power beacons (PBs) and share the spectrum with multiple primary receivers (PRs) in the underlay paradigm. For this system, we propose a hop-by-hop relay selection scheme called the largest decoding set (LDS). In each stage, relay selection is based on the harvested energy from PBs and the channel state information (CSI) of both the interference links to PRs and the relaying links in the subsequent hop. Considering both harvested energy and maximum interference constraints, we derive the exact end-to-end outage probability and show that the results closely match those obtained from simulations. Moreover, the asymptotic end-to-end outage probabilities in two different scenarios are derived to provide more valuable insights. Numerical results show that the outage probability of the proposed LDS scheme is very close to that of the best-path scheduling (BPS) scheme, which provides a lower bound on outage probability but requires global CSI before the secondary source transmits. We also compare the LDS scheme with other relay selection schemes that have appeared recently in the literature and show that LDS has the best outage performance.
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基于集群的多跳认知中继网络的新型中继选择方案性能分析
在本文中,我们研究了基于无线供电集群的多跳认知中继网络(mcrn)的性能,其中辅助节点从多个专用功率信标(PBs)收集能量,并在底层范式中与多个主接收器(pr)共享频谱。对于该系统,我们提出了一种逐跳中继选择方案,称为最大解码集(LDS)。在每个阶段,中继选择是基于从PBs收集的能量和到PRs的干扰链路和后续跳中的中继链路的信道状态信息(CSI)。在考虑能量收集和最大干扰约束的情况下,我们得到了精确的端到端中断概率,并表明结果与模拟结果非常吻合。此外,还推导了两种不同场景下的渐近端到端中断概率,以提供更有价值的见解。数值结果表明,LDS方案的中断概率与最佳路径调度(BPS)方案非常接近,BPS方案提供了中断概率的下界,但需要在副源发送前进行全局CSI。我们还将LDS方案与最近在文献中出现的其他中继选择方案进行了比较,并表明LDS具有最佳的中断性能。
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来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
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