On Decentralized Sum-Rate Maximization with Successive Interference Cancellation

2026-04-14

AI Summary

This study addresses the problem of sum-rate maximization in decentralized wireless networks without requiring global channel state information (CSI). Focusing on the two-user symmetric Gaussian interference channel, the work investigates joint power and rate allocation combined with successive interference cancellation (SIC). By leveraging game-theoretic and convex optimization techniques, the authors propose a novel distributed resource allocation algorithm that converges to a solution closely approximating the global optimum using only local CSI. The proposed mechanism substantially outperforms orthogonal access and greedy strategies, achieving significant sum-rate gains without reliance on global CSI. To the best of the authors’ knowledge, this is the first approach to enable efficient and scalable decentralized SIC-based optimization in symmetric interference channels.

Technology Category

• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Distributed Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

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.

Problem

• Decentralized
• Sum-Rate Maximization
• Successive Interference Cancellation
• Gaussian Interference Channel
• Power and Rate Allocation

Innovation

• Decentralized optimization
• Successive Interference Cancellation
• Gaussian interference channel
• Power and rate allocation
• Channel State Information