Abstract
IEEE Journal on Selected Areas in Communications, vol. 41, no. 5,
pp. 1383-1397, May 2023 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.