Wireless Capacity with Oblivious Power in General Metrics

TL;DR

This paper analyzes the capacity of wireless networks under oblivious power control, providing approximation algorithms and characterizations for maximizing capacity in general metric spaces with practical power assignments.

Contribution

It offers the first constant-factor approximation for capacity with monotone, sub-linear power in general metrics and characterizes the optimality of mean power for bi-directional links.

Findings

Constant-factor approximation for capacity in general metrics.

Mean power assignment is optimal for bi-directional links.

Logarithmic approximation for scheduling bi-directional links with oblivious power.

Abstract

The capacity of a wireless network is the maximum possible amount of simultaneous communication, taking interference into account. Formally, we treat the following problem. Given is a set of links, each a sender-receiver pair located in a metric space, and an assignment of power to the senders. We seek a maximum subset of links that are feasible in the SINR model: namely, the signal received on each link should be larger than the sum of the interferences from the other links. We give a constant-factor approximation that holds for any length-monotone, sub-linear power assignment and any distance metric. We use this to give essentially tight characterizations of capacity maximization under power control using oblivious power assignments. Specifically, we show that the mean power assignment is optimal for capacity maximization of bi-directional links, and give a tight $\theta(\log n)$-approximation of scheduling bi-directional links with power control using oblivious power. For uni-directional links we give a nearly optimal $O(\log n + \log \log \Delta)$-approximation to the power control problem using mean power, where $\Delta$ is the ratio of longest and shortest links. Combined, these results clarify significantly the centralized complexity of wireless communication problems.