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Different Object Functions for SWIPT Optimization by SADDE and APSO
Symmetry ( IF 2.2 ) Pub Date : 2021-07-24 , DOI: 10.3390/sym13081340
Wei Chien , Chien-Ching Chiu , Po-Hsiang Chen , Yu-Ting Cheng , Eng Hock Lim , Yue-Li Liang , Jia-Rui Wang

Multiple objective function with beamforming techniques by algorithms have been studied for the Simultaneous Wireless Information and Power Transfer (SWIPT) technology at millimeter wave. Using the feed length to adjust the phase for different objects of SWIPT with Bit Error Rate (BER) and Harvesting Power (HP) are investigated in the broadband communication. Symmetrical antenna array is useful for omni bearing beamforming adjustment with multiple receivers. Self-Adaptive Dynamic Differential Evolution (SADDE) and Asynchronous Particle Swarm Optimization (APSO) are used to optimize the feed length of the antenna array. Two different object functions are proposed in the paper. The first one is the weighting factor multiplying the constraint BER and HP plus HP. The second one is the constraint BER multiplying HP. Simulations show that the first object function is capable of optimizing the total harvesting power under the BER constraint and APSO can quickly converges quicker than SADDE. However, the weighting for the final object function requires a pretest in advance, whereas the second object function does not need to set the weighting case by case and the searching is more efficient than the first one. From the numerical results, the proposed criterion can achieve the SWIPT requirement. Thus, we can use the novel proposed criterion (the second criterion) to optimize the SWIPT problem without testing the weighting case by case.

中文翻译:

SADDE 和 APSO 用于 SWIPT 优化的不同对象函数

针对毫米波同步无线信息和功率传输 (SWIPT) 技术,研究了采用算法波束成形技术的多目标函数。在宽带通信中研究了使用馈电长度来调整具有误码率(BER)和收割功率(HP)的 SWIPT 不同对象的相位。对称天线阵列对于多接收器的全向波束成形调整非常有用。自自适应动态差分演化 (SADDE) 和异步粒子群优化 (APSO) 用于优化天线阵列的馈电长度。论文中提出了两种不同的目标函数。第一个是加权因子乘以约束 BER 和 HP 加上 HP。第二个是约束BER乘以HP。仿真表明,第一个目标函数能够在 BER 约束下优化总收集功率,并且 APSO 可以比 SADDE 更快地收敛。但是,最终目标函数的权重需要预先进行预测试,而第二个目标函数不需要逐个设置权重,搜索效率比第一个高。从数值结果来看,所提出的准则可以达到 SWIPT 要求。因此,我们可以使用新提出的标准(第二个标准)来优化 SWIPT 问题,而无需逐个测试加权。而第二个目标函数不需要逐个设置权重,搜索效率比第一个高。从数值结果来看,所提出的准则可以达到 SWIPT 要求。因此,我们可以使用新提出的标准(第二个标准)来优化 SWIPT 问题,而无需逐个测试加权。而第二个目标函数不需要逐个设置权重,搜索效率比第一个高。从数值结果来看,所提出的准则可以达到 SWIPT 要求。因此,我们可以使用新提出的标准(第二个标准)来优化 SWIPT 问题,而无需逐个测试加权。
更新日期:2021-07-24
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