Understanding the Paradoxical Effects of Power Control on the Capacity of Wireless Networks

TL;DR

This paper investigates how transmission power affects wireless network capacity, revealing that capacity can either increase or decrease depending on network configurations and interactions with link scheduling and routing.

Contribution

It provides a theoretical analysis showing capacity is non-decreasing with power and can be unbounded in some cases, but is bounded in uniform node distributions, and explores practical implications.

Findings

Optimal capacity is non-decreasing with power.

Capacity can be unboundedly increased with higher power in certain networks.

In uniform distributions, capacity gain is limited by a positive constant.

Abstract

Recent works show conflicting results: network capacity may increase or decrease with higher transmission power under different scenarios. In this work, we want to understand this paradox. Specifically, we address the following questions: (1)Theoretically, should we increase or decrease transmission power to maximize network capacity? (2) Theoretically, how much network capacity gain can we achieve by power control? (3) Under realistic situations, how do power control, link scheduling and routing interact with each other? Under which scenarios can we expect a large capacity gain by using higher transmission power? To answer these questions, firstly, we prove that the optimal network capacity is a non-decreasing function of transmission power. Secondly, we prove that the optimal network capacity can be increased unlimitedly by higher transmission power in some network configurations. However, when nodes are distributed uniformly, the gain of optimal network capacity by higher transmission power is upper-bounded by a positive constant. Thirdly, we discuss why network capacity in practice may increase or decrease with higher transmission power under different scenarios using carrier sensing and the minimum hop-count routing. Extensive simulations are carried out to verify our analysis.