基于混合阈值的资源有效利用选择分集接收机

P. Bithas, Athanasios S. Lioumpas, Theodore Mouroutis, Yiannis Stylianou, G. Efthymoglou
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引用次数: 0

摘要

在无线网络中,由于传输介质的随机性,特别是在具有移动性和接收器和发射器之间缺乏视距链接的操作环境中,传输介质在保持服务质量方面提出了一些挑战。另一方面,面对衰落信道的影响,需要采用复杂但必要的机制,如信道均衡和分集接收和/或传输,这些机制利用硬件和信道资源。在资源消耗和性能改进之间折衷的一种常见做法是采用自适应分集机制,例如选择分集(SD),它在各种无线通信场景中都是一种有吸引力的解决方案,因为它提供了相对较低的复杂性和改进的性能。然而,在许多实际情况下,连续监控所有可用的分集路径(SD方案中强制要求)会导致不必要的资源消耗(例如控制通道)。为了减轻这种复杂性,我们采用了一种新的基于自适应阈值的SD (t-SD)接收机,只要信噪比高于预定义的阈值,就只使用当前分集路径进行信号接收,否则接收机就变成了纯SD。为此目的,提出了一个新的分析性能评估框架,根据重要的统计指标,以及复杂性分析。数值评估结果表明,该方案在性能和复杂性权衡方面优于其他已知方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid threshold-based selection diversity receivers for efficient resources utilization
In wireless networks, the transmission medium poses several challenges in preserving the Quality-of-Service due to its random nature especially in operational environments with mobility and absence of line-of-sight links between the receiver and the transmitter. On the other hand, confronting the effects of fading channels requires the employment of complex but necessary mechanisms, such as channel equalization and diversity reception and/or transmission, which utilize hardware and channel resources. A common practice, which compromises between resources consumption and performance improvement, is to employ adaptive diversity mechanisms, such as the selection diversity (SD), which represents an attractive solution in various wireless communication scenarios, since it offers relatively low complexity and improved performance. In many practical situations, though, the continuous monitoring of all the available diversity paths, which is mandatory in SD schemes, leads to unnecessary resources consumption (e.g., control channels). In order to alleviate this complexity, we adopt a new adaptive threshold-based SD (t-SD) receiver, where only the current diversity path is used for signal reception as long as its signal-to-noise ratio is above a predefined threshold, otherwise the receiver becomes a pure SD. To this aim a new analytical performance evaluation framework is presented in terms of important statistical metrics, along with a complexity analysis. Numerical evaluated results illustrate how the proposed scheme outperforms other well known schemes in terms of performance and complexity trade-off.
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