Abstract
As the penetration of wireless networks increase, number of neighboring networks contending for the limited unlicensed spectrum band increases. This interference between neighboring networks leads to large systems of locally interacting networks. We investigate whether the short-term fairness of this system of networks degrades with the system size and density if transmitters employ random spectrum access with carrier sensing (CSMA). Our results suggest that (a) short-term fair capacity, which is the throughput region that can be achieved within the acceptable limits of short-term fairness, reduces as the number of contending neighboring networks, i.e., degree of the conflict graph, increases for random regular conflict graphs where each vertex has the same number of neighbors, (b) short-term fair capacity weakly depends on the network size for a random regular conflict graph but a stronger dependence is observed for a grid deployment. We demonstrate the implications of this study on a city-wide Wi-Fi network deployment scenario by relating the short-term fairness to the density of deployment. We also present related results from the statistical physics literature on long-range correlations in large systems and point out the relation between these results and short-term fairness of CSMA systems.
Highlights
Popularity of wireless access technologies manifests itself in the form of ever increasing penetration of wireless local area networks
9 Conclusions This article was aimed at characterizing the performance of a system of networks employing CSMA protocol under a short-term fairness constraint
Our main findings can be summarized as follows: (1) Short-term fairness significantly depends on the degree of the network: highdegree topologies have less short-term fair capacity than low-degree topologies
Summary
Popularity of wireless access technologies manifests itself in the form of ever increasing penetration of wireless local area networks. Transitions between such states become rare as the system size increases, leading to multiple distinct equilibrium distributions in the limit Such short-term behavior is suggested by existence of long-range dependence in a graphical system model. Adaptive CSMA algorithms that can achieve throughput optimality have been proposed [2,3,13,14] These algorithms solve the long-term fairness problem of CSMA systems by adapting the channel access rate of nodes according to their demands. In these algorithms, nodes in an unfair position will increase their channel access probability as their queue lengths grow. We demonstrate that this relationship may result in a tradeoff between the coverage and the short-term fairness of a Wi-Fi-based access network
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