An intelligent reflective surface (IRS) is a novel and revolutionizing communication technology destined to enable the control of the radio environment. An IRS is a real-time controllable reflectarray with a massive number of low-cost passive elements which introduce a phase shift to the incoming signals from the sources before the propagation towards the destination. This technology introduces the notion of a smart propagation environment with the aim of improving the system performance. In this paper, we provide a comprehensive literature overview on IRS technology, including its basic concepts and reconfiguration, as well as its design aspects and applications for wireless communication systems. We also study the performance metrics and the setups considered in recent publications related to IRS and provide suggestions of future research lines based on still unexplored use cases in the state-of-the-art.

Hybrid analog/digital schemes for precoding/combining have proved to be a low-complexity and/or low-power strategy to obtain reasonable beamforming gains in multiuser millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems. Hybrid precoding/combining performs jointly baseband processing and analog processing in the radio frequency (RF) domain. In these systems, the number of RF chains limits the maximum number of streams simultaneously handled by the transceivers. In the uplink of a multiuser mmWave MIMO system, the hardware reduction based on hybrid transceivers is limited by the number of data streams that must be simultaneously served by the centralized node. Most works approach hybrid transceiver design by considering more RF chains than data streams, an unrealistic assumption when the number of nodes is large. On the other hand, statistically independent information is conventionally assumed in multiuser mmWave systems. This assumption does not hold in scenarios like wireless sensor networks (WSNs), where the sources produce correlated information. In this paper, by enabling inter-user correlation exploitation, we propose a grouping approach to handle a high number of individual sources with a limited number of RF chains through distributed quantizer linear coding (DQLC) mappings. The allocation of the users per group and the hybrid design of the combiner at the common central node to serve the grouped users is also analyzed. We also propose a hybrid minimum mean square error (MMSE) combining design in order to exploit the spatial correlation between the sources in a conventional uncoded mmWave uplink. Simulation results show the performance advantages of the proposed approaches in various hardware-constrained system settings. INDEX TERMS Millimeter-wave communications, multiuser channels, joint source-channel coding, hybrid combining, source correlation.

The combination of multiple-input multiple-output (MIMO) and intelligent reflecting surfaces (IRSs) is foreseen as a key enabler of beyond 5G (B5G) and 6G. In this work, two different approaches are considered for the joint optimization of the IRS phase-shift matrix and MIMO precoders of an IRS-assisted multi-stream (MS) multi-user MIMO (MU-MIMO) system with the aim of maximizing the system sum-rate for every channel realization. The first one is a novel contextual bandit (CB) approach with continuous state and action spaces called deep contextual bandit-oriented deep deterministic policy gradient (DCB-DDPG). The second is an innovative deep reinforcement learning (DRL) formulation where the states, actions and rewards are selected such that the Markov decision process (MDP) property of reinforcement learning (RL) is properly met. Both proposals perform remarkably better than state-of-the-art heuristic methods in high multi-user interference scenarios.

Analog-digital hybrid precoding and combining schemes constitute an interesting approach to millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems due to the low hardware complexity and/or low power required for its deployment. However, the design of the hybrid precoders and combiners of a wideband multiuser (MU) mmWave MIMO system is challenging because the signal processing in the analog domain is constrained to be frequency flat. Furthermore, the number of radio frequency (RF) chains limits the number of individual streams that a common base station (BS) can simultaneously serve. This work jointly addresses the user scheduling, the user precoder design, and the BS hybrid combining design for the uplink of wideband MU mmWave MIMO systems. On the one hand, user precoding and BS hybrid combining are jointly designed to minimize the impact of having frequencyflat RF components. On the other hand, a number of users larger than the number of RF chains are served at the BS by employing a distributed quantizer linear coding (DQLC)-based non-orthogonal multiple access (NOMA) scheme. The use of this encoding strategy also allows exploiting the spatial correlation between the source information. Simulation results show remarkable performance gains of the proposed approaches for wideband mmWave MIMO hardware-constrained systems. INDEX TERMS User scheduling, wideband mmWave, multiuser communications, non-orthogonal multiple access, joint source-channel coding.

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