Multiple-input Multiple-output Cellular Networks Research Articles

A QoS-Adaptive Interference Alignment Technique for In-Band Full-Duplex Multi-Antenna Cellular Networks

In this paper, we propose a novel interference alignment (IA) technique for an in-band full-duplex (IBFD) multiple-input multiple-output (MIMO) cellular network where a base station (BS) and user equipment (UE) are equipped with multiple antennas, and the local channel state information (CSI) is available at all nodes. Considering a practical IBFD MIMO cellular network, it is assumed that only the BS operates with full-duplex (FD) communication while UE operate in half-duplex (HD) mode. These IBFD networks introduce a new type of interference called cross-link interference (CLI), in which uplink UE affects downlink UE. The proposed IA technique consists of two symmetric IA schemes according to the number of antennas in the uplink and downlink UE, and both schemes effectively mitigate CLI in the IBFD MIMO network. It is worth noting that both IA schemes are adaptively applicable according to the network's quality-of-service (QoS) requirements, such as uplink and downlink traffic demands. Furthermore, we theoretically characterize and prove the achievable sum-degrees-of-freedom (DoF) of the proposed IA technique. Simulation results show that the proposed IA technique significantly improves the sum rate performance compared to conventional HD communications (multi-user MIMO) while achieving the same achievable DoF as the interference-free IBFD MIMO network.

Coverage and Rate in MIMO Cellular Networks With Location-Aware Transmission Rank Selection

In this letter, we study the performance of a multiple-input multiple-output (MIMO) cellular network with location-aware transmission rank selection, where the number of transmit streams for every base-station (BS) and user equipment (UE) link is determined based on the average received power at the UE (hence, the link distance). We assume open-loop zero-forcing beam-forming (OL-ZFBF) at the receiver. We first develop a stochastic geometry based analytical framework for this setup by including the adaptive rank as a mark of each BS. Using this framework, we derive the coverage probability and spectral efficiency (SE) as a function of the rank selection threshold. Our analysis demonstrates that selecting transmission rank for each link on the basis of distance improves SE. We also investigate the tradeoff between coverage probability and SE.

Utilizing Non-Orthogonal Polarization With Polarization Reuse Technique for 4 × 4 MIMO Capacity Enhancement

5G communication promises fast and large data stream which requires higher capacity of a cellular wireless network. A higher capacity could be achieved with wider bandwidth and network densification, but they are expensive approaches. Instead, upgrading the wireless network with higher-order Multiple Input Multiple Output (MIMO) antenna system with polarization diversity can inexpensively escalate the peak data rate for higher capacity. We present a 4x4 MIMO cellular network scheme utilizing polarization reuse scheme and using 4 polarization to reform the cellular network from current state of the art of dual polarization 4x4 MIMO scheme. 4 Polarizations (vertical, Horizontal, ±45° slant) is used in 2 orthogonal polarization pair form, with a beam-separation among pair, to intensify polarization diversity and maximize the MIMO network channel capacity. This beam-separated polarization reuse technique minimizes the channel correlation which maximizes the probability of four independent data streams (rank 4). The simulated result of the channel capacity with the proposed scheme achieves a 30% higher capacity compared to the baseline configuration of 3-sector 4x4 MIMO. The field trial of the presented network indicates a higher portion of rank 4, supporting four independent data streams in the rich scattering environment of a cellular network.

Position-Aided Beam Learning for Initial Access in mmWave MIMO Cellular Networks

In this article, beam learning based on position information (PI) about mobile station positions in the initial access (IA) of millimeter wave (mmWave) multiple-input–multiple-output (MIMO) cellular networks is investigated. The existing PI-based IA procedure cannot efficiently tackle the position inaccuracy and blockage or may cause a long IA delay because of the inefficient beam learning. Based on the sparse scattering of mmWave signals, the serving area is partitioned into smaller areas and the beams are learned for each small area. Moreover, the number of learned beams is restricted and fixed after learning. Thus, the impact of position inaccuracy and blockage can be mostly mitigated and the IA delay is short in each successful IA. The analysis shows the lower bound of the probability of miss detection. Additionally, the simulation results show that the proposed approach can achieve a reasonable IA delay and superior IA performance than other PI-based approaches.

Performance enhancement using multiple‐input multiple‐output (MIMO) electronic relay in massive MIMO cellular networks

Device-to-device (D2D) communication system is considered one of the most effective technology directions for solving the spectrum scarcity problem in 5G wireless communication. In this study, an electronic relay is proposed to be utilised in D2D communication. The electronic relay is a hybrid cooperative relay consisting of compress and forward relay with and without coding techniques, decode and forward relay and amplify and forward relay with variable gain. The selection of the most appropriate one has performed automatically according to the feedback channel state information. Additionally, the multiple-input multiple-output (MIMO) electronic relay with the multi-user and massive MIMO destination is introduced. The closed formulas of the outage probability for both cellular user and D2D transmission are derived. Furthermore, the analytical discussions for the proposed electronic relay are executed. Extensive MATLAB simulation programmes are executed to study the performance of the proposed system and to compare it with the conventional one. Moreover, the average sum rate is derived in terms of a number of electronic relay antennas and the D2D density through cellular networks.

Achievable Degrees of Freedom of Relay-Aided MIMO Cellular Networks Using Opposite Directional Interference Alignment

In this paper, we propose an interference alignment (IA) scheme for the multiple-input multiple-output (MIMO) uplink cellular network with the help of a relay which operates in half-duplex mode. The proposed scheme only requires global channel state information (CSI) knowledge at the relay, with no transmitter beamforming and time extension at the user equipment (UE), which differs from conventional IA schemes for cellular networks. We derive the feasibility condition of the proposed scheme for the general cellular network configuration and analyze the degrees-of-freedom (DoF) performance of the proposed IA scheme while providing a closed-form beamformer design at the relay. Extensions of the proposed scheme to downlink and full-duplex cellular networks are also proposed in this paper. The DoF performance of the proposed scheme is compared to those of linear IA scheme and relay-aided interference management scheme for a cellular network with no time extension. It is also shown that advantages similar to those in the uplink case can be obtained for the downlink case through the duality of a relay-aided interfering multiple-access channel (IMAC) and an interfering broadcast channel (IBC). Furthermore, the proposed scheme for a full-duplex cellular network is shown to have advantages identical to those of a number of proposed half-duplex cellular cases.

Downlink Signal-to-Interference Ratio and Spectral Efficiency of MIMO Cellular Networks Using Truncated Lognormal Approximation

This work focuses on analytical performance evaluation of a multiple-input multiple-output (MIMO) multicellular radio access network, while taking into account distance-dependent path loss, lognormal-distributed shadowing, and Rayleigh-distributed multipath fading. We propose a truncated moment-matching method for approximating the distribution of the sum of independent lognormal random variables in order to model the statistical behavior of the downlink signal-to-interference ratio (SIR) experienced by user equipment at a particular location in the presence of cochannel interference. The proposed method offers a good match with the simulated results in terms of the downlink SIR as well as mean and outage spectral efficiency for various MIMO schemes such as transmit and receive diversity, closed- and open-loop spatial diversity, and closed-loop multiuser MIMO. We compare the semianalytical results with that obtained from Monte Carlo simulations and quantify the relative error in terms of statistical metrics such as Kullback–Leibler divergence and Kolmogorov–Smirnov distance. In contrast to the existing works, the proposed model is useful for a wide range of shadowing standard deviation (4–12 dB) and activity of neighboring base stations (0.4–1). Moreover, the presented method is shown to achieve a comparable accuracy with the state of the art in spite of being less time consuming.

Spectral efficiency of massive MIMO networks with pilot contamination and channel covariance matrix estimation

This study addresses spectral efficiencies (SEs) in a massive multiple-input multiple-output cellular network with pilot contamination. Both uplink and downlink SEs are investigated with practical channel state information. A downlink precoder minimising signal detection error and power leakage with considerations on spatial correlation has been derived. Also, a low-complexity covariance matrix estimation method has been proposed and compared with the existing estimation method in terms of normalised mean-squared error. It has been demonstrated via simulations that both uplink and downlink SEs using the proposed covariance matrix estimation method can grow with the number of antennas even with a relatively small number of pilot symbols.

Joint Beamforming and Power Optimization for D2D Underlaying Cellular Networks

This paper studies the optimal joint beamforming and power control strategy for device-to-device (D2D) communication underlaying multiuser multiple-input multiple-output cellular networks. We consider multiple antennas at the base station (BS) and a single antenna at each cellular user (CU), D2D transmitter (DT), and D2D receiver (DR). We aim to minimize the total transmission power of the system by jointly designing the transmit beamforming at the BS and the transmit powers for both BS and DTs, while satisfying the signal-to-interference-plus-noise ratio based quality-of-service constraints for both CUs and DRs. Due to the nonconvex nature of the problem, we apply the semidefinite relaxation technique to find the optimal solution, which always satisfies the rank-one constraint. We also investigate three suboptimal fixed beamforming schemes: zero-forcing (ZF), regularized ZF, and hybrid maximum ratio transmission-ZF, where the focus is to minimize the total transmission power while reducing complexity. When perfect channel information is not available, we propose a robust transmit power minimization strategy with ZF beamforming that only requires limited feedback based channel direction information at the BS. Finally, computer simulation results are presented to demonstrate the effectiveness of the proposed schemes.

Ergodic Spectral Efficiency in MIMO Cellular Networks

This paper shows how the application of stochastic geometry to the analysis of wireless networks is greatly facilitated by (i) a clear separation of time scales, (ii) the abstraction of small-scale effects via ergodicity, and (iii) an interference model that reflects the receiver's lack of knowledge of how each individual interference term is faded. These procedures render the analysis both more manageable and more precise, as well as more amenable to the incorporation of subsequent features. In particular, the paper presents analytical characterizations of the ergodic spectral efficiency of cellular networks with single-user multiple-input multiple-output (MIMO) and sectorization. These characterizations, in the form of easy-to-evaluate expressions, encompass the coverage, the distribution of spectral efficiency over the network locations, and the average thereof.

The Feasibility of Interference Alignment for Full-Duplex MIMO Cellular Networks

The feasibility condition of interference alignment (IA) for full-duplex (FD) multiple-input multiple-output (MIMO) cellular networks is considered. A necessary condition and a sufficient condition on the IA feasibility are established, characterizing the optimal sum degrees of freedom (DoF) for a broad class of network topologies. The necessary and sufficient condition is shown specially for a class of symmetric network topologies. The results demonstrate that FD operation at the base station with appropriate IA is able to improve the sum DoF than the conventional half-duplex operation.

Degrees of Freedom of MIMO Cellular Networks: Decomposition and Linear Beamforming Design

This paper investigates the symmetric degrees of freedom (DoF) of multiple-input multiple-output (MIMO) cellular networks with $G$ cells and $K$ users per cell, having $N$ antennas at each base station and $M$ antennas at each user. In particular, we investigate techniques for achievability that are based on either decomposition with asymptotic interference alignment or linear beamforming schemes and show that there are distinct regimes of $(G,K,M,N)$ , where one outperforms the other. We first note that both one-sided and two-sided decomposition with asymptotic interference alignment achieve the same DoF. We then establish specific antenna configurations under which the DoF achieved using decomposition-based schemes is optimal by deriving a set of outer bounds on the symmetric DoF. Using these results, we completely characterize the optimal DoF of any $G$ -cell network with single-antenna users. For linear beamforming schemes, we first focus on small networks and propose a structured approach to linear beamforming based on a notion called packing ratios. Packing ratio describes the interference footprint or shadow cast by a set of transmit beamformers and enables us to identify the underlying structures for aligning interference. Such a structured beamforming design can be shown to achieve the optimal spatially normalized DoF (sDoF) of two-cell two-user/cell network and the two-cell three-user/cell network. For larger networks, we develop an unstructured approach to linear interference alignment, where transmit beamformers are designed to satisfy conditions for interference alignment without explicitly identifying the underlying structures for interference alignment. The main numerical insight of this paper is that such an approach appears to be capable of achieving the optimal sDoF for MIMO cellular networks in regimes where linear beamforming dominates asymptotic decomposition, and a significant portion of sDoF elsewhere. Remarkably, polynomial identity test appears to play a key role in identifying the boundary of the achievable sDoF region in the former case.

Backhaul Limited Asymmetric Cooperation for MIMO Cellular Networks via Semidefinite Relaxation

Multicell cooperation has recently attracted tremendous attention because of its ability to eliminate intercell interference and increase spectral efficiency. However, the enormous amount of information being exchanged, including channel state information and user data, over backhaul links may deteriorate the network performance in a realistic system. This paper adopts a backhaul cost metric that considers the number of active directional cooperation links, which gives a first order measurement of the backhaul loading required in asymmetric Multiple-Input Multiple-Output (MIMO) cooperation. We focus on a downlink scenario for multi-antenna base stations and single-antenna mobile stations. The design problem is minimizing the number of active directional cooperation links and jointly optimizing the beamforming vectors among the cooperative BSs subject to signal-to-interference-and-noise-ratio (SINR) constraints at the mobile station. This problem is non-convex and solving it requires combinatorial search. A practical algorithm based on smooth approximation and semidefinite relaxation is proposed to solve the combinatorial problem efficiently. We show that semidefinite relaxation is tight with probability 1 in our algorithm and stationary convergence is guaranteed. Simulation results show the saving of backhaul cost and power consumption is notable compared with several baseline schemes and its effectiveness is demonstrated.

Belief Propagation for Distributed Downlink Beamforming in Cooperative MIMO Cellular Networks

We propose a new graphical model approach to cooperative multiple-input multiple-output (MIMO) cellular networks. The objective is to optimize downlink transmit beamforming at each BS in order to maximize the sum throughput over the entire network. While ideal centralized beamforming requires full channel state information (CSI) sharing among all BSs in the network and huge computational complexity for combinatorial optimization, the proposed graphical model enables distributed beamforming which requires only local CSI sharing between neighboring BSs and efficiently solves the optimization problem in a distributed manner. As distributed solvers for this problem, we derive message-passing algorithms which can be implemented with polynomial-time computational complexity. Furthermore, we make a slight approximation on the objective function to derive a simpler graphical model, providing further complexity saving. Simulation results indicate that the proposed distributed downlink beamforming achieves average cell throughput typically within just 2% of ideal centralized beamforming.

Performance Analysis of MIMO Cellular Network with Channel Estimation Errors

This paper aims to analyze the throughput of a multiple-input multiple-output (MIMO) multiple-access (MA) wireless network. Some recent research studies showed that, in the concerned scenario, the joint processing of all the received signals by access point (AP) cooperation can dramatically enhance the system throughput because of the macrodiversity. However, in practice, the channel estimation quality for the paths from the macrodiversity providers is usually poor. Unfortunately, existing literature on the performance of the joint processing in the MIMO cellular networks is deficient in channel estimation errors. To fill this literature gap, this paper provides an analytical framework for calculating the large-system throughput of a MIMO cellular network with channel estimation errors. Unlike most large-system results, analytical results of this study can be applied in the scenarios with any given input distributions (not necessarily Gaussian) from transmitters. In addition, several issues including 1) how much of the coherence interval should be spent on training and 2) the impact of AP cooperation are highlighted by the analytical results.