This letter investigates the achievable spectral efficiency (SE) of massive multiple-input multiple-output transmission systems with hybrid architectures based on discrete Fourier transform (DFT) processing, where the base station (BS) has perfect channel state information and baseband processing is performed by zero-forcing precoding. We derive tractable upper and lower bounds on the achievable SE. Based on these results, the effects of the number of radio frequency (RF) chains, signal-to-noise ratio (SNR), and the number of users are revealed. Compared to hybrid architectures with ideal and quantized phase shifters, simulations indicate that the achievable SE with DFT processing is inferior to the one with ideal phase shifters. In addition, the achievable SE with DFT processing is independent of the number of BS antennas and can be improved by increasing the SNR and the number of RF chains, while there exists an optimal number of users that maximizes the total achievable SE.

This paper investigates the downlink achievable spectral efficiency (SE) and energy efficiency (EE) of massive MIMO for hybrid architectures based on phase shifters, where the base station (BS) has perfect channel state information and baseband processing is done zero-forcing precoding. We derive an approximated upper bound on the achievable SE for hybrid architecture with ideal phase shifters. Based on the derived analytical expression, we find that the total achievable SE increases with the number of BS antennas and users, and the signal-to-noise ratio (SNR). In order to acquire the required limited feedback, we propose an algorithm to generate the corresponding quantized matrix and study hybrid architectures with quantized phase shifters. Compared to fulldigital architectures, results show that hybrid architectures enjoy a much higher achievable EE in massive MIMO systems, whereas its achievable SE is inferior to full-digital architectures. In addition, results also showcase that the achievable SE of hybrid architectures can be improved by increasing the bits of phase shifters, and there exists an optimal SNR and antenna number to maximize the achievable EE of the system.

We analyze the downlink multiuser precoding of massive multiple input multiple output (MIMO) system, where the base station (BS) has ideal channel state information (CSI) and adopts three types of different linear precoding schemes, i.e., maximum ratio transmission (MRT), zero-forcing (ZF), and minimum mean squared error (MMSE). Under a Rayleigh fading channel, we attain the exact expressions on the achievable rate for these three precoding schemes. Moreover, we provide several insights on the achievable rates and reveal the relation of the number of BS antennas, the number of users, and the input signal-to-noise ratio (SNR) with the achievable rates respectively. It is found in general that the achievable rate increases with the number of BS antennas and the input SNR. To be more specific, the MRT precoding scheme is much inferior to the ZF and MMSE precoding schemes and tends to be at a fixed rate at the high SNR case. On the contrary, the MRT precoding scheme outperforms ZF precoding schemes at the low SNR case. Moreover, the total achievable rate always does not increase with the number of users and the optimal number of users always exists for the ZF and MMSE precoding schemes.

Due to the broadcast nature of wireless transmission, traditional wireless two-hop relaying is vulnerable for eavesdroppers to overhear messages. In order to enhance the physical-layer security, this paper studies one cooperative network with caching relays to reduce the transmission links overheard by the eavesdropper. Relays are grouped into different clusters so that the secrecy outage probability of any cluster is better than the traditional two-hop transmission. Based on the secrecy outage probability of clusters and the groups of files, we propose a novel hybrid cache placement, which combines the traditional base station caching strategy, most popular content caching strategy and largest content diversity caching strategy to cache the popular contents. The performance analysis and optimal design results are provided on the two objective functions: the secrecy outage probability and average secrecy capacity. From these two objective functions, some interesting observations are reached: for the function of secrecy outage probability, we can always find an optimal value of most popular files to minimize the secrecy outage probability; and for the function of average secrecy capacity, we can also find an optimal value of most popular files to maximize the average secrecy capacity. The numerical and simulation results are finally demonstrated to verify the proposed studies.

This paper investigates the achievable spectral efficiency (SE) of millimeter wave massive multiple-input multiple-output systems with three different array topologies deployed at the base station (BS), namely uniform rectangular array (URA), uniform linear array (ULA) or uniform circular array (UCA). To be practical, both small scale fading and large scale path loss, and shadowing effects are considered in the analysis. A three dimensional (3D) channel model taking both the azimuth and elevation domains into account is adopted for the analysis of the URA and UCA topologies. Considering randomly distributed users in the cell, we firstly deduce the distribution functions of the distances between the users and the BS, and the azimuth and elevation angles of departure, respectively. Based on the derived probability distribution, tight approximations on the achievable SE with maximum ration transmission under the three antenna array topologies are derived. Analytical results show that under all the three topologies, the total achievable SE increases with the number of BS antennas, but decreases with the radius of cell and decay exponent. Moreover, it converges to a saturated value in the high SNR regime and a large inter-element spacing. It is also found that the UCA configuration has a superior achievable SE than the URA and ULA cases, and thus is the best choice for mmWave massive MIMO systems in terms of the achievable SE.

The accuracy of channel state information (CSI) acquisition is nontrivial for intelligent reflection surface (IRS)-assisted massive multiple-input–multiple-output (MIMO) systems due to the IRS comprises of a large number of low-cost electromagnetic reflection units that can smartly reflect the impinging signal. In this article, we investigate the downlink channel estimation problem for IRS-assisted millimeter-wave (mmWave) massive MIMO systems, where the IRS provides effective reflected paths to enhance the coverage and spectral efficiency. To reduce the hardware costs and power consumption, the massive MIMO system is adopted the mixed-analog-to-digital converter (ADC) architecture, in which a fraction of antennas is equipped with high-resolution ADCs and a large number of antennas are deployed with low-resolution ADCs. Considered the finite-dimensional millimeter-wave channel model, we utilize the special row–column sparse characteristics of the channel matrix and propose a row-structured sparsity based on the orthogonal matching pursuit (RS-OMP) algorithm. The RS-OMP algorithm sequentially calculates the row–column support sets of the angular cascaded channel matrix and then uses the least square (LS) algorithm to reconstruct the cascaded channel matrix, which aim to achieve a lower computational complexity. Simulation results demonstrate that under the same system configuration, the proposed RS-OMP algorithm not only improves the accuracy of channel estimation but also reduces more than 75% of the pilot overhead compared to the traditional orthogonal matching pursuit algorithm.