Multicast Capacity of Wireless Ad Hoc Networks Under Gaussian Channel Model

被引:41
作者
Li, Xiang-Yang [1 ,2 ]
Liu, Yunhao [3 ]
Li, Shi [4 ]
Tang, ShaoJie [1 ]
机构
[1] IIT, Dept Comp Sci, Chicago, IL 60616 USA
[2] Hangzhou Dianzi Univ, Inst Comp Applicat Technol, Hangzhou 310018, Zhejiang, Peoples R China
[3] Hong Kong Univ Sci & Technol, Dept Comp Sci & Engn, Kowloon, Hong Kong, Peoples R China
[4] Princeton Univ, Dept Comp Sci, Princeton, NJ 08540 USA
基金
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词
Capacity; Gaussian channel; multicast; percolation theory; scheduling; unicast; wireless ad hoc networks;
D O I
10.1109/TNET.2009.2037431
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
We study the multicast capacity of large-scale random extended multihop wireless networks, where a number of wireless nodes are randomly located in a square region with side length a = root n, by use of Poisson distribution with density 1. All nodes transmit at a constant power F, and the power decays with attenuation exponent alpha > 2. The data rate of a transmission is determined by the SINR as B log(1 + SINR), where B is the bandwidth. There are as randomly and independently chosen multicast sessions. Each multicast session has k randomly chosen terminals. We show that when k <= theta(1) n/(log n)(2 alpha+6) and n(s) >= theta(2)n(1/2+beta) capacity that each multicast session can achieve, with high probability, is at least c(s) root n/n(s)root k, where theta(1), theta(2), and c(s) are some special constants and beta > 0 is any positive real number. We also show that for k = O(n/log(2) n), the per-flow multicast capacity under Gaussian channel is at most O(root n/n(s)root k) when we have at least n(s) = Omega(log n) random multicast flows. Our result generalizes the unicast capacity for random networks using percolation theory.
引用
收藏
页码:1145 / 1157
页数:13
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