Wireless powered communication network (WPCN) is a promising technique to resolve the power constraint issue faced by wireless nodes at the same time it also provides green and a safer solution. This paper studies, mutual sharing between WPCN and simultaneous wireless information and power transfer model where optimal resource allocation occurs between licensed/bandwidth group and an unlicensed/power group to enhance the system performance. The main aim of this paper is to maximize system weighted sum rate and minimize power consumption during transmission by optimal time allocation and energy beamforming vector allocation. These multiobjective combinatorial problems are solved using joint metaheuristic particle swarm optimization-cuckoo search algorithm to provide an optimal solution. The results are compared using a conventional mathematical optimization algorithm to set as a baseline for performance parameters. The obtained results demonstrate that the efficient joint metaheuristic approach provides a significant gain in the system performance and also offers a computationally less complex approach for solving a complicated non-convex multiobjective problem of wireless powered network.

无线供电通信网络（WPCN）是解决无线节点面临的功率约束问题的一种很有前途的技术，同时它也提供了绿色和更安全的解决方案。本文研究了WPCN与同时无线信息和功率传输模型之间的相互共享，其中在许可/带宽组和非许可/功率组之间进行最佳资源分配以提高系统性能。本文的主要目的是通过优化时间分配和能量波束赋形矢量分配来最大化系统加权和速率并最小化传输过程中的功耗。这些多目标组合问题使用联合元启发式粒子群优化 - 布谷鸟搜索算法解决，以提供最佳解决方案。使用传统的数学优化算法比较结果，将其设置为性能参数的基线。获得的结果表明，有效的联合元启发式方法显着提高了系统性能，并且还为解决无线供电网络的复杂非凸多目标问题提供了一种计算上不太复杂的方法。