本文提出将能量采集技术引入认知无线电系统，并研究了能量采集与频谱感知的联合优化设计。文中将时隙模式下认知 无线电传输划分为能量收集、频谱感知监测和数据传输三个部分，以最大化有效吞吐量为目标进行建模。基于最优停止策略， 提出了一种明显优于传统的模拟退火算法（Simulated Annealing Algorithm，SAA）的自适应动态优化算法和频谱感知规则。为 了降低计算复杂度，在自适应动态计算的最优算法基础上，又提出了低计算复杂度的静态次优计算方法，并得出了静态问题的 闭型求解公式，实现了对移动通信授权频段在非高峰情况下相对空闲的频谱资源的最优感知模式和共享规则。

In this paper, a paradigm of cognitive radio systems with energy harvesting is proposed and joint optimization for energy harvesting and spectrum sensing is investigated. The operation timeslot of the cognitive radio system is partitioned into three parts for energy harvesting, spectrum sensing and data transmitting to maximize the achievable throughput. An adaptive optimization algorithm along with a spectrum sensing rule is proposed based on optimal stopping strategy, which significantly outperforms conventional simulated annealing algorithm (SAA). To further reduce computational complexity, a low‑complexity static strategy is proposed based on adaptive computation and close form solution for the static problem is derived. Results in this paper enable optimal spectrum sensing and sharing of less congested licensed bands with non‑peak usage.