摘要
文章联合优化数据-能量传输时长与能量波束,在保障节点最低传输速率的前提下最大化所有节点的加权和速率,提出了一种基于交替迭代的求解框架。对于能量-数据时长优化,提出基于节点剔除的数据时长分配算法与基于黄金分割的能量时长搜索算法;对于能量波束设计,提出基于半正定规划和矩阵分解的信号数目选择和波束设计算法。仿真结果表明:所提方案通过设置节点最低数据传输速率,可以更好地保障节点数据的成功传输;此外,相比于单天线方案,多天线可以显著提高系统传输性能。
The energy-data duration allocation and energy beamforming design are jointly optimized to maximize the weighted sum rate of sensing nodes(SNs) subject to the corresponding minimum data rate requirements. An alternative-iteration-based framework is proposed to solve this problem. For the energy-data duration allocation, the node-exclusion-based algorithm and the golden-section-based algorithm are presented to optimize the transmission duration allocation among SNs and the setting of energy duration. For the energy beamforming design, the semi-definite programming and matrix de- composition are employed to adaptively select the number of energy signals and the corresponding beamforming vectors. Simulation results show that the proposed scheme provides better guarantee for the successful data reporting of SNs by setting the minimum data rate requirements. Meanwhile, com- pared with the single-antenna scheme, the proposed multi-antenna scheme is able to greatly improve the transmission capacity.
出处
《合肥工业大学学报(自然科学版)》
CAS
北大核心
2017年第6期763-768,共6页
Journal of Hefei University of Technology:Natural Science
基金
国家自然科学基金资助项目(61362008)