Secure Energy Efficiency Maximization in Cognitive Satellite-Terrestrial Networks

This article investigates the secure energy efficiency (EE) optimization problem in a cognitive satellite-terrestrial network with a capable eavesdropper. The objective is to maximize the secure EE for the primary satellite network while satisfying the allowable signal-to-interference-plus-noise ratio requirements of the secondary and primary users along within the transmit power limitation of both satellite and the terrestrial base station. Owing to the nonconvexity and intractability of the original optimization problem, a beamforming scheme and associated transformation algorithms are proposed by jointly applying the Taylor approximation, fraction programming, and alternating search to cope with the implementation difficulty. The key is to convert the original optimization problem into a simple convex framework and obtain the optimal solution step by step. Finally, numerical simulations are given to verify the feasibility and practicability of the proposed optimization algorithms.