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Partially connected hybrid beamforming (HBF) is a promising approach to alleviate the implementation of large scale millimeter-wave multiple-input multiple-output (MIMO) systems. In this paper, we develop rate maximizing algorithms for the full array- and subarray-based processing strategies of partially connected HBF. We formulate the rate maximization problem as a weighted mean square error minimization problem and use alternating optimization to tackle it.

The problem of network multiple-input multiple-output precoding under distributed channel state information is a notoriously challenging question, for which optimal solutions with reasonable complexity remain elusive. In this context, we assess the value of hierarchical information exchange, whereby an order is established among the transmitters (TXs) in such a way that~a given TX has access not only to its local channel estimate but also to the estimates available at the less informed TXs.

We consider a two-way full-duplex (FD) multiple-input multiple-output (MIMO) communication system in which devices are equipped both with multi-tap analog interference cancellers and TX-RX beamforming capabilities, and propose a joint analog and digital algorithm to simultaneously maximize the rate and minimize the self-interference (SI) in such a system.

Cell-free massive MIMO system is a promising technology of 5G wireless communications that provide a user-centric coverage to the user by the basestation cooperation. Most prior works on the cell-free massive MIMO systems assume the time division duplexing (TDD) systems, although the frequency division duplexing (FDD) systems dominate the current wireless communications. In the FDD systems, CSI acquisition and feedback overhead are serious concerns when the number of antennas is large.

Nowadays, a significant goal of technology is to prolong the lifetime of the wireless communication devices. To this end, this paper studies and optimizes the performance of simultaneous wireless information and power transfer with an integrated energy and information receiver, which has the advantage of low complexity and energy cost. Specifically, a tractable expression for the achievable rate is provided, which is then used to describe the achievable harvested energy-rate region.

In multi-antenna systems, it is preferred to activate only a subset of the available transmit antennas in order to save hardware and energy resources, without seriously degrading the system performance. However, antenna selection often poses very hard optimization problems. Joint multicast beamforming and antenna selection is one particular example, which is often approached by Semi-Definite Relaxation (SDR) type approximations. The drawback is that SDR lifts the problem to a much higher dimension, leading to considerably high memory and computational complexities.