Power Allocation Of Multi-beam Satellite System In Fading Channel

Nowadays, due to high throughput demands and flexible deployments with large coverage area, multi-beam satellite communication system has earned extensive researches. It can resolve the contradiction between high antenna gain and complete coverage. However, on account of their scarce and expensive onboard resources, energy efficiency and spectral efficiency have been the important indicators to measure system communication performance. In this paper, in order to resolve the ever-increasing communication demands and limited payload on board, a power allocation scheme is proposed for energy and spectrum efficiency trade-off in multi-beam satellite systems.Firstly, a new algorithm aims to optimize the power allocation to each beam is addressed, where co-channel interference can be ignored. Suppose a shadowed Rice model for land mobile satellite channels. Under the constraint of total power and rate of system, we set up a double-objective optimization problem, which optimizes power allocation of beams to maximize both EE and SE. Then we analyze that under this frame EE is quasi-concave in SE. Based on this analysis and Lagrangian duality theory, Pareto optimal solution sets can be acquired. Besides, the impacts of system parameter such as the elevation angle、static circuit power and the number of beams on algorithm performance are under discussion. Finally, the simulation results demonstrate the effectivity of this power allocation scheme for achieving desirable EE and SE, and confirm the validity of the conclusion.Secondly, a power allocation scheme is proposed for energy efficiency (EE) and spectrum efficiency (SE) trade-off in the multi-beam satellite system with co-channel interference. To meet different traffic demand among various spot beams, signal-to-interference-ratio (SIR) is first derived according to the statistic characteristic of the forward link and the analytical result of the achievable rate is approximately obtained in a closed-form expression. Then, the inter-beam power allocation problem is formulated as a multi-objective optimization problem under constraints of individual throughput and total power consumption. A multi-objective metaheuristic technique, namely non-dominated sorting in genetic algorithms (NSGA-Ⅱ), is adopted to solve this optimization problem and obtain applicable Pareto front. Simulation results demonstrate the validity of the closed-form expression and the efficiency of the NSGA-Ⅱ algorithm.