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arXiv 0809.0016cs.ITmath.IT
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无线网络传输容量综述

An overview of the transmission capacity of wireless networks

Steven Weber, Jeffrey G. Andrews, Nihar Jindal

摘要:

本文调查和统一了一些最近的贡献,共同开发了一个度量分散的无线网络分析称为传输容量。虽然众所周知,很难得出多终端或\adhoc网络的一般端到端容量结果,但传输容量(TC)框架允许通过关注简化的物理/MAC层模型来量化可实现的单跳速率。通过使用随机几何来量化网络中的多用户干扰,可以确定网络中传输的最佳空间密度和成功概率之间的关系,并且通常相当简单地用关键网络参数来表示。首先讨论的基本模型和分析工具,并应用到一个简单的网络路径损耗,我们提出了严格的上限和下限的传输容量(通过中断概率的下限和上限)。然后,我们引入随机信道(衰落/阴影),并给出TC和中断近似的任意信道分布,以及瑞利和Nakagami衰落的特殊情况下的确切结果。然后,我们应用这些结果来展示TC如何用于更好地理解调度,功率控制和分散网络中多天线的部署。文章最后讨论了该模型的不足之处以及未来的研究方向。

英文摘要:

This paper surveys and unifies a number of recent contributions that have collectively developed a metric for decentralized wireless network analysis known as transmission capacity. Although it is notoriously difficult to derive general end-to-end capacity results for multi-terminal or \adhoc networks, the transmission capacity (TC) framework allows for quantification of achievable single-hop rates by focusing on a simplified physical/MAC-layer model. By using stochastic geometry to quantify the multi-user interference in the network, the relationship between the optimal spatial density and success probability of transmissions in the network can be determined, and expressed -- often fairly simply -- in terms of the key network parameters. The basic model and analytical tools are first discussed and applied to a simple network with path loss only and we present tight upper and lower bounds on transmission capacity (via lower and upper bounds on outage probability). We then introduce random channels (fading/shadowing) and give TC and outage approximations for an arbitrary channel distribution, as well as exact results for the special cases of Rayleigh and Nakagami fading. We then apply these results to show how TC can be used to better understand scheduling, power control, and the deployment of multiple antennas in a decentralized network. The paper closes by discussing shortcomings in the model as well as future research directions.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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