On Decentralized Sum-Rate Maximization with Successive Interference Cancellation
For wireless network operators, this work provides a practical decentralized solution to sum-rate maximization with SIC, addressing the challenge of optimal deployment in environments lacking centralized coordination.
This paper tackles joint power and rate allocation in a two-user Gaussian interference channel with SIC, proposing a novel decentralized algorithm that significantly outperforms traditional benchmarks like Orthogonal Access and greedy strategies, even without global Channel State Information.
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.