This paper studies the performance improvement of a multi-user downlink system via polarization design at the transmitter such that the gains at the desired locations are maximized. To this end, a weighted sum rate maximization problem is formulated, constrained under total power, polarization norm, and a minimum signal-to-interference-and-noise ratio guarantee to the users for simultaneous transmission (ST), and its performance is compared with time-shared transmission (TT). As a solution strategy, weighted minimum mean square error based and fair resource allocation algorithms have been proposed to optimize ST and TT respectively with only long-term channel statistics as well as with channel state information (CSI) at the transmitter. Weighted sum rate performance is theoretically studied for long-term channel statistics. Branch-and-bound approach and the duality gap are considered to validate the optimal resource allocation with CSI for small-scale and large scale scenarios, respectively. Simulation results show that the proposed joint phase and polarization beamforming consistently enhances the multiaccess performance with respect to only phase beamforming, with average gain of about 23% and 6% with CSI and 89% and 4% with long-term channel statistics for ST and TT, respectively. We also study the performance of the proposed beamforming strategies with imperfect CSI and non-orthogonal multiple access-based ST to capture practical scenarios.

This paper characterizes the impact of polarization on sustainable wireless power transfer (WPT) to the mobile Internet-of-Thing (IoT) devices, focusing on various transmitter and receiver antenna polarization states. It investigates both line-of-sight (LOS) and controlled non-LOS (NLOS) reflections via reconfigurable intelligent surface (RIS), deriving closed-form expressions for received power to identify optimal antenna polarization. Theoretical findings are experimentally validated in an anechoic chamber, showing strong agreement with a normalized root mean square error ≤ 0.08. The research also assesses the necessity of RIS's polarization handling, concluding its non-essentiality in single source-receiver setups. Simulations reveal that horizontal polarization boosts received power by ≤ 28% compared to other polarizations. Furthermore, incorporating RIS in green communication significantly enhances received power.

Distributed beamforming is a promising technique for transferring power to a node wirelessly, as it allows optimal design of waveforms at each transmitter such that they interact constructively at the receiver node. In this paper, we propose a distributed RF beamforming scheme which involves phase detection and prediction for the sources participating in beamforming process. The proposed method is capable of tracking source drifts and statistical fluctuations of the channel. The phase detection process requires one feedback for synchronizing all the sources to the receiver pairs and provides a closed-form solution for the phase offsets between a pair of received beams under the presence of RF power measurement errors. Autoregressive (AR) model is used for phase prediction which avoid feedback in synchronization process all together. Performance of the proposed detection and prediction model is quantified in terms of average received power, efficiency, and number of message exchange between the sources and the receiver.