基于多包接收和重传分集的随机接入协议无限用户模型

R. Sámano-Robles, M. Ghogho, D. McLernon
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引用次数: 19

摘要

近年来,随着多分组接收(MPR)系统和网络分集多址(NDMA)等新的跨层协议的出现,随机接入协议的研究重新受到重视。尽管它们具有相关性,但这两个系统仅使用有限用户群体模型并考虑对活跃用户的完美检测同时进行了研究,这些假设仅在用户数量少且信噪比高的情况下有用。本文的目的是引入一个无限用户群模型,该模型适用于具有大量用户和有限流量负载的场景,它允许我们将ALOHA MPR协议的可用结果扩展到使用重传分集(RD)的系统。与现有方法不同,我们的模型既包括数据包解码错误的影响,也包括对活跃用户的不完美检测的影响,这在有限信噪比环境下极大地影响了传统NDMA系统的性能。此外,与传统的带休假的M/G/1队列公式相比,该模型能更好地逼近NDMA协议的排队延迟。最后,该算法还代表了由信号处理工具(如SICTA(连续干扰消除树算法))和其他源分离辅助算法辅助的竞争二叉树算法的扩展和推广。利用仿真和分析结果对该模型的效益进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An infinite user model for random access protocols assisted by multipacket reception and retransmission diversity
The study of random access protocols has recently regained attention due to new cross-layer schemes such as multipacket reception (MPR) systems and network diversity multiple access protocols (NDMA). Despite their relevance, these two systems have only been simultaneously studied employing finite user population models and considering perfect detection of the active users, which are assumptions only useful in scenarios with low numbers of users and high values of the SNR. The purpose of this paper is to introduce an infinite user population model, valid for scenarios with large numbers of users and finite traffic loads, which allows us to extend the available results on ALOHA MPR protocols to systems that use retransmission diversity (RD). Unlike existing approaches our model includes both the effects of packet decoding errors and the effects of imperfect detection of the active users, which considerably affect the performance of conventional NDMA systems in finite SNR environments. Additionally, the proposed model provides a better approximation to the queuing delay of NDMA protocols than the conventional formula of an M/G/1 queue with vacations. Finally, the proposed algorithm also represents an extension and generalization of contention binary tree algorithms assisted by signal processing tools such as SICTA (successive interference cancellation tree algorithm) and other algorithms assisted by source separation. The benefits of the proposed model are assessed using simulation and analytic results.
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