针对6G物联网中信道误差影响与用户采集能量的公平性问题,该文在用户信干噪比受限、发射功率约束和反射相位模一约束的条件下,研究了智能反射面(IRS)辅助的信息与能量同传(SWIPT)系统中公平性采集能量最大化问题.为了解决该非凸问题,分别运用Schur-Complement和S-Procedure将无限维约束转换为有限维的矩阵线性不等式,然后利用罚函数和连续凸逼近的方法将难以求解的原问题转化为标准的凸优化问题,进而提出了一种迭代的鲁棒公平性能量采集算法.数值结果表明,所提鲁棒优化算法能够明显提升网络采集的公平性能量.
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.