This paper proposes a novel network framework of intelligent reflecting surface (IRS)-assisted simultaneous wireless information and power transfer (SWIPT) non-orthogonal multiple access (NOMA) networks, where IRS is used to enhance the NOMA performance and the wireless power transfer (WPT) efficiency of SWIPT. We formulate a problem of minimizing base station (BS) transmit power by jointly optimizing successive interference cancellation (SIC) decoding order, BS transmit beamforming vector, power splitting (PS) ratio and IRS phase shift while taking into account the quality-of-service (QoS) requirement and energy harvested threshold of each user. The formulated problem is non-convex optimization problem, which is difficult to solve it directly. Hence, a two-stage algorithm is proposed to solve the above-mentioned problem by applying semidefinite relaxation (SDR), Gaussian randomization and successive convex approximation (SCA). Specifically, after determining SIC decoding order by designing IRS phase shift in the first stage, we alternately optimize BS transmit beamforming vector, PS ratio, and IRS phase shift to minimize the BS transmit power. Numerical results validate the effectiveness of our proposed optimization algorithm in reducing BS transmit power compared to other baseline algorithms. Meanwhile, compared with non-IRS-assisted network, the IRS-assisted SWIPT NOMA network can decrease BS transmit power by 51.13\%.
翻译:本文建议建立一个新型网络框架,由智能反映表面(IRS)辅助的同步无线信息和电力传输(SWIPT)非横向多功能接入(NOMA)网络组成,其中IRS用来提高NOMA的性能和SWIPT的无线电力传输效率。我们提出了一个最大限度地减少基地站传输能力的问题,方法是共同优化连续取消干扰(SIC)解码顺序、BS传输信号成形矢量、分电比率(PS)和IRS阶段转移,同时考虑到每个用户的服务质量(QOS)要求和能量采集阈值。制定的问题是非电离子优化问题,难以直接解决这个问题。因此,我们提出一个两阶段的算法,通过采用半确定性放松(SDR)、高斯随机化和连续调近光度(SCA),具体来说,在确定SICD解码顺序后,在第一阶段设计IRS级转换时,我们将BS传输的成成形矢量、PS比率和IRSS升级后,将BS级网络的动力升级升级到S级网络。