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arXiv 0712.2274cs.NI
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多速率IEEE 802.11无线局域网中利用多用户分集的分布式MAC策略

Distributed MAC Strategy for Exploiting Multi-user Diversity in Multi-rate IEEE 802.11 Wireless LANs

Da Rui Chen, Ying Jun, Zhang

摘要:

快速速率自适应是提高无线网络物理层原始数据速率的有效途径。然而,在当前的IEEE 802.11传统中,MAC层吞吐量由具有最低数据率的用户主导,导致带宽的未充分利用。在本文中,我们提出并分析了一种新的分布式MAC策略,称为速率感知DCF(R-DCF),利用IEEE 802.11无线局域网的速率自适应的潜力。R-DCF的关键特征是通过根据瞬时信道条件引入不同的迷你时隙,只有具有最高数据率的竞争站可以接入信道。通过这种方式,R-DCF协议不仅以完全分布式的方式利用多用户分集,而且还减少了由于冲突而导致的吞吐量损失。通过分析,我们开发了一个分析模型,得出一般的多速率无线局域网的吞吐量的R-DCF。使用分析模型,我们研究了R-DCF协议在不同的网络设置与不同的速率自适应策略和信道变化的性能。在分析的基础上,我们进一步推导出R-DCF可实现的最大吞吐量。在实际应用中,提出了一种离线自适应回退方法,在较低的运行复杂度下获得接近最优的性能。通过大量的分析和仿真,证明了R-DCF的优越性。

英文摘要:

Fast rate adaptation has been established as an effective way to improve the PHY-layer raw date rate of wireless networks. However, within the current IEEE 802.11 legacy, MAC-layer throughput is dominated by users with the lowest data rates, resulting in underutilization of bandwidth. In this paper, we propose and analyze a novel distributed MAC strategy, referred to as Rate-aware DCF (R-DCF), to leverage the potential of rate adaptation in IEEE 802.11 WLANs. The key feature of R-DCF is that by introducing different mini slots according to the instantaneous channel conditions, only contending stations with the highest data rate can access the channel. In this way, the R-DCF protocol not only exploits multi-user diversity in a fully distributed manner but also reduces the loss of throughput due to collisions. Through analysis, we develop an analytical model to derive the throughput of R-DCF in general multi-rate WLANs. Using the analytical model we investigate the performance of R-DCF protocol in various network settings with different rate adaptation strategies and channel variations. Based on the analysis, we further derive the maximal throughput achievable by R-DCF. For practical implementation, an offline adaptive backoff method is developed to achieve a close-to-optimal performance at low runtime complexity. The superiority of R-DCF is proven via extensive analyses and simulations.

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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