On Decentralized Sum-Rate Maximization with Successive Interference Cancellation

TL;DR

This paper explores decentralized strategies for sum-rate maximization in wireless networks using SIC, proposing a novel algorithm that outperforms traditional methods even without global channel information.

Contribution

It characterizes optimal solutions for joint power and rate allocation and introduces a decentralized algorithm for symmetric channels leveraging SIC.

Findings

Proposed decentralized algorithm outperforms benchmarks.

Algorithm achieves significant sum-rate improvements.

Effective without requiring global Channel State Information.

Abstract

Successive Interference Cancellation (SIC) is a powerful technique for managing interference in wireless networks, yet its optimal deployment in decentralized environments remains a challenge. This study investigates joint power and rate allocation in a two-user Gaussian interference channel incorporating SIC at the receivers. We characterize the global optimal solutions of the problem, and recognizing the limitations of centralized coordination, we introduce a novel decentralized algorithm for a symmetric channel configuration. Numerical results demonstrate that even without global Channel State Information, our proposed algorithm significantly outperforms traditional benchmarks, such as Orthogonal Access which suffers from temporal underutilization or greedy strategies that fail to exploit SIC gains.