The maximal secondary throughput in cognitive radio networks with energy harvesting. Issue 3 (20th November 2022) - Ge, Haijiang; Zheng, Kechen; Chi, Kaikai; Liu, Xiaoying
Abstract: In terms of spectrum reuse and lifetime prolongation, the energy‐harvesting cognitive radio networks (EH‐CRNs) have been a hot issue in the wireless networking research community. While satisfying the minimal throughput demand of primary users (PUs), it is aimed to maximize the throughput of secondary users (SUs) in the EH‐CRN with multiple SUs. Specifically, the problem of secondary throughput maximization (STM) is first formulated as a non‐linear optimization problem, then its convexity is proven, and finally an efficient algorithm is proposed that jointly uses the Fibonacci search method and equal interval search method to obtain the optimal time allocation among primary transmitter (PT)'s energy transfer and each SU's packet transmission, and the optimal transmit power of PT. Furthermore, for the scenarios where the circuit power is negligible, the convex problem is first proven, and a more efficient algorithm is presented for the problem of STM. Simulation results demonstrate that, with the increase of the minimal throughput demand of PUs, the reduction rate of the maximal secondary throughput increases. Abstract : While satisfying the minimal throughput demand of primary users, we maximize the throughput of secondary users in the EH‐CRN. Specifically, we first formulate the problem of secondary throughput maximization (STM) as a non‐linear optimization problem, then prove its convexity, and finally propose an efficient algorithm that jointly uses the Fibonacci search method and equal interval search method to obtain the optimal time allocation and the optimal transmit power of PT. Furthermore, for the scenarios where the circuit power is negligible, we first prove the convex problem, and present a more efficient algorithm for the problem of STM.