Dynamic Energy-Efficient Power Allocation in Multibeam Satellite Systems

TL;DR

This paper proposes a novel energy-aware power allocation method for multibeam satellite systems that minimizes power use and unmet capacity through a new optimization approach and a fast-converging algorithm.

Contribution

It introduces a new multi-objective optimization framework and a successive convex approximation algorithm with proven complexity for dynamic satellite power management.

Findings

The SCA algorithm converges quickly, suitable for real-time satellite systems.

The method effectively balances power consumption and system capacity unmet.

A new complexity analysis of the SCA method is provided.

Abstract

Power consumption is a major limitation in the downlink of multibeam satellite systems, since it has a significant impact on the mass and lifetime of the satellite. In this context, we study a new energy-aware power allocation problem that aims to jointly minimize the unmet system capacity (USC) and total radiated power by means of multi-objective optimization. First, we transform the original nonconvex-nondifferentiable problem into an equivalent nonconvex-differentiable form by introducing auxiliary variables. Subsequently, we design a successive convex approximation (SCA) algorithm in order to attain a stationary point with reasonable complexity. Due to its fast convergence, this algorithm is suitable for dynamic resource allocation in emerging on-board processing technologies. In addition, we formally prove a new result about the complexity of the SCA method, in the general case, that complements the existing literature where the complexity of this method is only numerically analyzed.