Robust energy efficient maximization in wireless powered CRNs based on power splitting

摘要

In this paper, we study the optimal design for simultaneous wireless information and power transfer (SWIPT) in cognitive radio networks (CRNs), where each secondary receiver (SR) can harvest energy and decode information using the signals received from the secondary transmitter (ST). It is assumed that the ST and SR adopt orthogonal frequency division multiplexing (OFDM) modulation. Each SR uses the power splitting (PS) to coordinate the process of energy harvesting (EH) and information decoding (ID). The optimization problem of maximizing the energy efficiency of the secondary system is formulated. In particular, in order to accurately analyze the uncertain channel state information (CSI) and improve the performance of wireless networks in dynamic environments, the probability constraints are introduced. To settle this non-convex problem, the nonlinear fractional programming is utilized. Then we decompose the equivalent optimization problem into two convex subproblems, and the probability constraints of signal-to-interference-plus-noise ratio (SINR) are converted to deterministic ones by integral transformation. An efficient iterative algorithm for robust resource allocation is presented. Finally, simulation results have verified the effectiveness of the proposed algorithm.