Distributed Algorithms for Spectral and Energy-Efficiency Maximization of K-User Interference Channels

Mohammad Soleymani,Ignacio Santamaria,Peter J Schreier

doi:10.1109/access.2021.3094976

Mohammad Soleymani, Ignacio Santamaria + Show 1 more

Open Access

https://doi.org/10.1109/access.2021.3094976

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Abstract

In this paper, we propose a cooperative distributed framework to optimize a variety of rate and energy-efficiency (EE) utility functions, such as the minimum-weighted rate or the global EE, for the K-user interference channel. We focus on the single-input multiple-output (SIMO) case, where each user, based solely on local channel state information (CSI) and limited exchange information from other users, optimizes its transmit power and receive beamformer, although the framework can also be extended to the multiple-output multiple-input (MIMO) case. The distributed framework combines an alternating optimization approach with majorization-minimization (MM) techniques, thus ensuring convergence to a stationary point of the centralized cost function. Closed-form power update rules are obtained for some utility functions, thus obtaining very fast convergence algorithms. The receivers treat interference as noise (TIN) and apply the beamformers that maximize the signal-to-interference-plus-noise (SINR). The proposed cooperative distributed algorithms are robust against channel variations and network topology changes and, as our simulation results suggest, they perform close to the centralized solution that requires global CSI. As a benchmark, we also study a non-cooperative distributed framework based on the so-called “signal-to-leakage-plus-noise ratio” (SNLR) that further reduces the overhead of the cooperative version.

Highlights

I NTERFERENCE has been the main bottleneck of multiuser wireless communication systems for decades, and interference-management techniques are expected to continue playing a key role in future beyond 5G (B5G) networks [1]
In this paper, we have proposed two distributed power control frameworks for the K-user interference channel (IC) when interference is treated as noise at receivers
Our cooperative distributed algorithm can be applied to any optimization problem in which the objective and/or constraint functions are linear functions of achievable rate of users

Summary

INTRODUCTION

I NTERFERENCE has been the main bottleneck of multiuser wireless communication systems for decades, and interference-management techniques are expected to continue playing a key role in future beyond 5G (B5G) networks [1]. In order to obtain fast solutions for the K-user SIMO IC, we specialize our framework to each considered utility function and find closed-form solutions for the power updating rules These closed-form solutions make it possible to implement these distributed algorithms in large-scale networks even with low-cost user equipments. The proposed cooperative distributed algorithms dynamically adapt to possible channel variations and changes in the network configuration This is due to the fact that each user can employ the latest CSI when updating its transmission parameters. To further reduce the overhead of the cooperative algorithms, we propose a non-cooperative distributed framework based on the definition of the so-called “signal-to-leakageplus-noise ratio” (SLNR) [26] To this end, we define the virtual rate and virtual EE for each user, and derive distributed algorithms that maximize these metrics.

SYSTEM MODEL AND PROBLEM STATEMENT

COOPERATIVE DISTRIBUTED ALGORITHM

NUMERICAL RESULTS

CONCLUSION