Intelligent reflecting surface (IRS) has recently been emerged as an effective way for improving the performance of wireless networks by reconfiguring the propagation environment through a large number of passive reflecting elements. This game-changing technology is especially important for stepping into the Internet of Everything (IoE) era, where high performance is demanded with very limited available resources. In this paper, we study a backscatter-assisted wireless powered communication network (BS-WPCN), in which a number of energy-constrained users, powered by a power station (PS), transmit information to an access point (AP) via backscatter and active wireless information transfer, with their communication being aided by an IRS. Using a practical energy harvesting (EH) model which is able to capture the characteristics of realistic energy harvesters, we investigate the maximization of total network throughput. Specifically, IRS reflection coefficients, PS transmit and AP receive beamforming vectors, power and time allocation are designed through a two-stage algorithm, assuming minimum mean square error (MMSE) receiver at the AP. The effectiveness of the proposed algorithm is confirmed via extensive numerical simulations. We also show that our proposed scheme is readily applicable to practical IRS-aided networks with discrete phase shift values.
翻译:智能反射表面(IRS)最近成为通过大量被动反射元素对传播环境进行重新配置,从而改进无线网络绩效的有效途径,通过大量被动反射元素对传播环境进行重新配置。这种改变游戏技术对于进入“一切”的互联网时代特别重要,因为在这个时代,以非常有限的资源要求高性能。在本文件中,我们研究了一个反射器辅助无线动力通信网络(BS-WPCN),在这个网络中,一些受能源限制的用户在发电站的动力下,通过反射和主动无线信息传输向接入点(AP)传送信息,其通信得到IRS的帮助。利用能够捕捉到现实能源采集器特点的实用能源采集(EH)模型,我们调查了网络总吞吐量的最大化。具体地说,IRS反射系数、PS传输和AP接收的矢量、能量和时间分配是通过两阶段的算法设计的,假设AP的最小平均平方错误(MMSE)接收器。提议的算法的有效性通过广泛应用数字模拟系统得到确认。我们提议的I 算算算算算法的可迅速转换。我们还显示我们的离离离子模型。