Over the past few years, the prevalence of wireless devices has become one of the essential sources of electromagnetic (EM) radiation to the public. Facing with the swift development of wireless communications, people are skeptical about the risks of long-term exposure to EM radiation. As EM exposure is required to be restricted at user terminals, it is inefficient to blindly decrease the transmit power, which leads to limited spectral efficiency and energy efficiency (EE). Recently, rate-splitting multiple access (RSMA) has been proposed as an effective way to provide higher wireless transmission performance, which is a promising technology for future wireless communications. To this end, we propose using RSMA to increase the EE of massive MIMO uplink while limiting the EM exposure of users. In particularly, we investigate the optimization of the transmit covariance matrices and decoding order using statistical channel state information (CSI). The problem is formulated as non-convex mixed integer program, which is in general difficult to handle. We first propose a modified water-filling scheme to obtain the transmit covariance matrices with fixed decoding order. Then, a greedy approach is proposed to obtain the decoding permutation. Numerical results verify the effectiveness of the proposed EM exposure-aware EE maximization scheme for uplink RSMA.

翻译：过去几年来,无线装置的普及已成为公众电磁辐射的重要来源之一。面对无线通信的迅速发展,人们对于长期接触EM辐射的风险持怀疑态度。由于需要将EM照射限制在用户终端,因此盲目地减少传输功率是无效的,导致光谱效率和能源效率有限。最近,建议分率多重接入(RSMA)作为提供更高无线传输性能的有效方法,这是未来无线通信的一个有希望的技术。为此,我们提议使用RSMA来增加大规模MIMOT上链接的EE,同时限制用户的EM接触。特别是,我们利用统计频道状态信息调查传输可变性矩阵和分解顺序的优化问题。这个问题被描述为非电离子混合组合组合组合程序,一般难以处理。我们首先提出修改充水计划,以获得固定解码秩序传输变异矩阵。随后,拟议采用贪婪方式来核实NumerIM的曝光率。随后,提议对NuEM系统进行最大程度的升级计划,以便获得EDOL-DRM结果。