Optimization of Reconfigurable Intelligent Surfaces with Electromagnetic Field Exposure Constraints

This work tackles the problem of maximizing the achievable rate in a reconfigurable intelligent surface (RIS)-assisted communication link, by enforcing conventional maximum power constraints and additional constraints on the maximum exposure to electromagnetic radiations of the end-users. The RIS phase shift matrix, the transmit beamforming filter, and the linear receive filter are jointly optimized, and two provably convergent and low-complexity algorithms are developed. One algorithm can be applied to general system setups, but does not guarantee global optimality. The other is shown to be provably optimal in the special case of isotropic electromagnetic exposure constraints. The numerical results show that RIS-assisted communications can ensure high data rate transmissions while guaranteeing users' exposure constraints to radio frequency emissions.