An algorithm to optimize the power allocation by maximizing the system throughput in cognitive radio energy harvesting networks was proposed. The algorithm formulated the throughput optimization model subject to the causality constraints of the harvested energy within the two secondary users and the interference constraint of the primary user. In addition, by applying the variable-substitution method and problem equivalence transformation, the joint optimization problem of power and cooperative energy was decoupled into two problems: a power allocation problem and a coopera-tive energy one. The former problem could be solved by iterating the two decoupled problems. As shown in the simula-tion results, the energy cooperation can significantly improve the system throughput when the harvested energy difference between two nodes is rather large.%针对认知能量采集网络,提出一种基于系统吞吐量最大化的功率分配算法.该算法在满足2个次用户节点采集能量的因果性限制和对主用户干扰限制的条件下,构建了系统吞吐量的优化模型;通过变量代换和问题等价性变换,将各节点的功率和协作能量联合优化问题解耦为分离的功率分配问题和逐个时隙的协作能量求解问题,而原问题的最优解则通过迭代求解分离的2个问题来获得.仿真结果表明,在2个节点采集能量总量差距较大时,能量协作可以显著提高系统吞吐量.
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