Hybrid analog-digital (HAD) beamforming architectures have been proposed to facilitate the practical implementation of massive multiple-input multiple-output (MIMO) systems by reducing the number of employed radio frequency chains. While most prior studies have aimed to maximize spectral efficiency (SE), the present paper proposes a two-stage HAD beamforming design for multi-user MIMO systems that can be used to maximize either the system's overall energy efficiency (EE) or SE. This problem is nonconvex and NP-hard due to the joint optimization between the analog and digital domains and the constant modulus constraints required by the analog domain. To address this problem, we propose a decoupled two-stage design wherein the first stage, the analog beamforming parts are updated, which are then taken into account in the second stage to design the digital beamforming parts to maximize the system's EE or SE. We consider two widely-used HAD beamforming techniques that utilize either fully-connected (FC) or partially-connected (PC) architectures employing variable phase-shifters. Using the most recently available data for the circuitry power consumption of the components, we compare the performance of these two HAD architectures with that of the fully-digital (FD) architecture in terms of the total circuitry power consumption, and achieved SE and EE. We find that there is a certain number of users above which the FC architecture has higher circuitry power consumption than the FD counterpart, in contrast to the PC architecture that always has lower circuitry power consumption. More importantly, our results reveal, contrary to the common opinion, that depending on the circuitry parameters the FD architecture may achieve not only higher SE, but also higher EE than the HAD architectures.

Existing works concluded that coherent transmission outperforms non-coherent transmission in the downlink of cell-free systems when the fronthaul links have unlimited capacity. Since the capacity of the fronthaul links of cell-free networks is typically limited, in this paper we ask the question whether this conclusion holds under more realistic assumptions on the fronthaul capacity. To answer this question, we study and compare the performance of these transmission strategies by formulating novel energy efficiency (EE) maximization problems for both strategies, where we explicitly consider realistic fronthaul capacity and power consumption constraints. Despite the non-convexity of these problems, we derive closed-form equations to find suboptimal solutions of both problems using a unified framework that combines successive convex approximation and the Dinkelbach algorithm. Numerical results show that the performance of coherent transmission is severely impacted by limited fronthaul capacities, power consumption on the fronthaul links, user-centric cluster size and the number of antennas at the access points, such that in many cases non-coherent transmission achieves higher EE than coherent transmission. Based on these results, we provide deployment guidelines on when to use coherent or non-coherent transmission to maximize the EE of cell-free systems with limited fronthauls.

Hybrid beamforming (BF) architectures employing phase-shifters or switches reduce the number of required radio frequency chains and the power consumption of base stations that employ a large number of antennas. Due to the inherent trade-off between the number of radio frequency chains, the complexity of the employed analog and digital BF algorithms and the achieved spectral and energy efficiency, designing hybrid BF architectures is a complex task. To deal with this complexity, we propose a unifying design that is applicable to architectures employing either phase-shifters or switches. In our design, the analog part of the hybrid BF architecture maximizes the capacity of the equivalent channel, while the digital part is updated using the well-known block diagonalization approach. We then employ the proposed joint analog-digital beamforming algorithm on four recently proposed hybrid architectures and compare their performance in terms of spectral and energy efficiency, and find that the proposed analog-digital BF algorithm outperforms previously proposed schemes. We also find that phase shifter based architectures achieve high spectral efficiency, whereas switching-based architectures can boost energy efficiency with increasing number of base station antennas.

This letter proposes distributed beamforming as a means of reducing interference in dynamic time division duplexing multiple input multiple output networks. Specifically, we formulate an optimization task, whose objective is to minimize the base station (BS) transmit power, while satisfying a predefined signal-to-interference-plus-noise ratio threshold for each downlink user equipment and keeping the BS to BS interference power below a tolerable level. An iterative decentralized solution requiring reduced signaling load based on primal decomposition is proposed. This decentralized algorithm is shown to iterate towards the centralized solution, while feasible but suboptimal solutions can be obtained at any iteration.

In this letter, we present a sequential closed-form semiblind receiver for a one-way multihop amplify-and-forward relaying system. Assuming Khatri-Rao space-time coding at each relay, it is shown that the system with K relays can be modeled by means of a generalized nested PARAFAC model. Decomposing this model into K + 1 third-order PARAFAC models, we develop a closed-form semiblind receiver for jointly estimating the information symbols and the individual channels, at the destination node. Each step consists of a Khatri-Rao factorization. Parameter identifiability conditions are given, and simulation results are provided to illustrate the effectiveness of the proposed semiblind receiver.

We formulate the resource assignment problem of maximizing the spectral efficiency of a wireless system subject to user satisfaction constraints in the multiservice scenario that is a challenging resource allocation problem from the system operators' point of view. We show that although this optimization problem is nonlinear, it can be converted to an integer linear program. This way, the optimal solution can be obtained by standard techniques. Due to the high computational complexity to obtain the optimal solution, we propose a fast suboptimal algorithm named Reallocation-based Assignment for Improved Spectral Efficiency and Satisfaction (RAISES). Simulation results show that our proposal achieves near-optimal performance in low and medium loads with a much lower computational complexity compared with the algorithm used to obtain the optimal solution. Therefore, the RAISES algorithm achieves a good tradeoff between performance and computational complexity.