Cell-free massive multiple-input multiple-output (MIMO) system is a promising architecture for next generation wireless systems by deploying a very large number of distributed access points (APs), which simultaneously serve a smaller number of user equipments (UEs) over the same time-frequency resources. It guarantees uniformly good service at high spectral efficiency with simple linear precoding techniques and max-min power control. In this article, we propose a new joint maximum-ratio and zero-forcing (JMRZF) precoding scheme, where part of APs are combined to perform centralized zero-forcing (ZF), while other APs apply simple maximum-ratio transmission (MRT). Our proposed precoder offers an adaptable trade-off between the spectral efficiency and front-haul signalling overhead. A corresponding AP subset selection scheme is also proposed which is based on large-scale fading coefficients. A closed-form expression for the achievable spectral efficiency of our proposed scheme is derived, which represents a generalized result including both fully distributed MRT and fully centralized ZF cases. Based on this closed-form expression, max-min power control is formulated and solved via the second order cone and first order methods. The former can obtain the global optimal solution, but its computational complexity is very high. On the other hand, the latter technique is sub-optimal, yet, it has very low computational complexity. Hence, it is suitable for large-scale cell-free massive MIMO systems with hundreds or thousands of APs and users. Numerical results show that our proposed JMRZF scheme can substantially outperform the local precoding schemes, even when a small part of APs are combined to deploy ZF and is implementable even when each AP has very few antennas. In addition, it is shown that our max-min power controls improves the spectral efficiency significantly, compared to the uniform power control scheme.

Vector perturbation (VP) precoding which utilizes a scaled Gaussian vector to minimize the effective transmit power is proved can obtain better diversity compared with linear precoding techniques. In this paper, we apply VP precoding in wireless MIMO wiretap channels to obtain practical physical layer security which aims at maximizing eavesdropper's error probability. The proposed scheme can also avoid performance loss introduced by artificial noise (AN) based secure schemes. New limit of perturbation vector is developed to guarantee practical secrecy and a new sphere decoder is given to meet such limitation. Furthermore, a modified VP scheme is proposed to reduce the complexity introduced by sphere decoder. Simulation results show that the proposed scheme could also achieve practical secrecy as AN based schemes, and better performance is obtained at the intended user with proposed scheme at the cost of computation complexity.

Small cell networks (SCNs) have emerged as promising technologies to meet the data traffic demands for the future wireless communications. However, the benefits of SCNs are limited to their hard handovers between base stations (BSs). In addition, the interference is another challenging issue. To solve this problem, this study employs a cooperative transmission mechanism focusing on correlated Rician/Gamma fading channels with zero‐forcing receivers. The analytical expressions for the achievable sum rate, symbol error rate and outage probability are derived, which are applicable to arbitrary Rician factors, correlation coefficients, the number of antennas, and remain tight across entire signal‐to‐noise ratios (SNRs). Asymptotic analyses at the high and low SNR regimes are carried out in order to further reveal the insights of the model parameters on the system performance. Monte‐Carlo simulation results validate the correctness of their derivations. Numerical results indicate that the theoretical expressions provide sufficiently accurate approximation to simulated results.

In this paper, we investigate the energy efficiency (EE) of large-scale distributed multiple-input multiple-output (D-MIMO) systems. Firstly, we derive an analytical closed-form expression of the lower bound on the ergodic capacity for D-MIMO systems, and the asymptotic performance for the large-scale antenna arrays systems over K fading channels is proposed. Utilizing these results, we elaborate on the EE optimization problem with transmitted power constraint. To tackle this multi-objective optimization problem, we propose an one-dimension iterative search algorithm with low complexity to obtain the optimal number of receive antennas, transmitted power and achievable sum rate with optimum EE. Simulation results verify the performance gain of the proposed scheme along with the increasing number of transmit antennas.

In this paper, we investigate the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) systems with linear maximum ratio combining (MRC) and zero-forcing (ZF) receivers. To be practical, the baseband power consumption with algorithm computational complexity (ACC) is taken into account. Utilizing this model, we maximize the global optimal number of receiver antenna and sum rate with optimal EE by fixed the number of users for different receivers, respectively. In parallel, the low complexity iterative algorithm is proposed to reap the optimal values. Simulation results indicate that the EE improves with the number of users for the two receivers.