Focusing on examine the influence of channel errors and the fairness of energy collected by users in 6G internet of things,the problem of maximizing fairness energy for Intelligent Reflecting Surface(IRS)-aided Simultaneous Wireless Information and Power Transfer(SWIPT)is examined when the users have a limited signal-to-interference noise ratio,a transmission power constraint and a reflection phase mode one constraint.As part of the process of solving the nonconvex problem,Schur Complete and S-Process are used to convert the infinite dimensional constraint into a linear inequality involving a finite dimensional matrix,and then the original difficult-to-solve problem is transformed into a standard convex optimization problem using the penalty function and continuous convex approximation,and then an iterative robust fairness energy acquisition algorithm is proposed.Numerical results indicate that the proposed robust optimization algorithm improves the fairness of network harvested energy significantly compared to previous algorithms.
关键词
智能反射面/信息与能量同传/采集能量最大化/鲁棒优化算法
Key words
Intelligent Reflecting Surface(IRS)/Simultaneous Wireless Information and Power Transfer(SWIPT)/Maximizing fairness energy/Robust optimization algorithm
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