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Electromagnetic exposure from wireless devices is strictly regulated around the world to ensure the safety of consumers. Recent studies have demonstrated that multi-antenna systems can leverage signal-level exposure models to jointly mitigate user radiation absorption and achieve high data rates. This is especially important for millimeter wave technologies, which are susceptible to power back-off techniques due to high propagation and blockage losses. However, prior models require significant overhead in the form of exposure measurements to compute model parameters and cannot be easily modified to predict electromagnetic absorption in different testing configurations. This article proposes methods to approximate the characteristic matrix of a quadratic model for two exposure measures in the millimeter wave band: incident power density and surface specific absorption rate (SAR). The presented models can be calculated with a small number of parameters and can be altered to account for mutual coupling, near-field effects, and changes in the exposure scenario. Spatial sampling schemes based on these models are derived to determine how many testing points are necessary to estimate exposure in a region within a specified margin of error. Software simulation results with half-wave dipoles validate the accuracy of the proposed models in a millimeter wave scenario. [ABSTRACT FROM AUTHOR]

The focus of this paper is on multi-user multi-input multi-output transmissions for millimeter-wave systems with a hybrid precoding architecture at the base station. To enable multiuser transmissions, the base station uses a cell-specific codebook of beamforming vectors over an initial beam alignment phase. Each user uses a user-specific codebook of beamforming vectors to learn the top-P (where P \geq 1) beam pairs in terms of the observed signal-to-noise ratio (\textSNR ) in a single-user setting. The top-P beam indices along with their \textSNR s are fed back from each user and the base station leverages this information to generate beam weights for simultaneous transmissions. A typical method to generate the beam weights is to use only the best beam for each user and either steer energy along this beam, or to utilize this information to reduce multi-user interference. The other beams are used as fall-back options to address blockage or mobility. Such an approach completely discards information learned about the channel condition(s) even though each user feeds back this information. With this background, this paper develops an advanced directional precoding structure for simultaneous transmissions at the cost of an additional marginal feedback overhead. This construction relies on three main innovations: first, additional feedback to allow the base station to reconstruct a rank- $P$ approximation of the channel matrix between it and each user; second, a zero-forcing structure that leverages this information to combat multi-user interference by remaining agnostic of the receiver beam knowledge in the precoder design; and third, a hybrid precoding architecture that allows both amplitude and phase control at low complexity and cost to allow the implementation of the zero-forcing structure. Numerical studies show that the proposed scheme results in a significant sum rate performance improvement over naïve schemes even with a coarse initial beam alignment codebook. [ABSTRACT FROM PUBLISHER]