Distributed Power Control Based on Constrained MPC in Cognitive Satellite Terrestrial Networks

• Published in: International Wireless Communications and Mobile Computing Conference (Online) pp. 994 - 999
• Main Authors: Zhang, Shuying, Ni, Zuyao, Jiang, Chunxiao, Kuang, Linling, Han, Zhu, Zhao, Xiaohui
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2020
• Subjects: Cognitive satellite terrestrial networks; constrained MPC; control; Interference; Power control; Regulators; Satellite broadcasting; Satellites; Signal to noise ratio; Tracking loops
• ISSN: 2376-6506
• DOI: 10.1109/IWCMC48107.2020.9148085

This paper proposes a distributed power control scheme based on the constrained model predictive control (MPC) for the underlay cognitive satellite terrestrial networks (CSTNs), where the primary satellite communication network coexists with the secondary terrestrial mobile network. We model this power control problem as a closed-loop dynamic control system with the inner loop and outer loop. On the basis of combining target power control (TPC) algorithm in the inner loop and tracking of flexible target signal to interference plus noise ratio (SINR) in the outer loop, we develop a corresponding state space expression of the problem where the fluctuation of each channel power gain is formulated as the exogenous disturbance input so that we do not need the accurate instantaneous channel state information (CSI). Then we design a SINR regulator in the outer loop, which is a constrained model predicted controller with rolling optimal operation subject to the interference temperature constraint obtained by calculating a linear matrix inequality. Finally, we obtain our constrained model predictive power control algorithm. In contrast to the previous static power control schemes based on the optimization theory that highly depend on the known instantaneous CSI and large signalling exchanges, the proposed scheme only needs locally measured information and outdate feedbacks. The performance of the proposed algorithm is shown to be effective through computer simulations.