Massive Antenna Arrays Research Articles

3D Beamforming With Massive Cylindrical Arrays for Physical Layer Secure Data Transmission

In this letter, a novel approach for physical layer security is implemented using massive cylindrical antenna arrays. A part of the arrays is used for transmitting a signal reliably from source to destination using highly directive beams. At the same time, the remaining part can be used to mitigate eavesdropping by transmitting a jamming signal through another directive beam toward the eavesdropper. In addition, the cylindrical arrays can mitigate the impact of malicious jamming by placing a null in the array pattern at the destination in the direction of the jammer. The results show that the proposed approach can lead to good jamming mitigation and high secrecy capacity in both 2D and 3D, even when there are errors in determining the location of the eavesdropper.

Large-scale cloud radio access networks: Fundamental asymptotic analysis

Large-scale cloud radio access network (LS-CRAN) is a highly promising next-generation cellular network architecture whereby many base stations (BSs) equipped with a massive antenna array are connected to a cloud-computing based central processor unit via digital front/backhaul links. This paper studies the asymptotic behavior of downlink (DL) performance of a LS-CRAN. As an asymptotic performance measure, the scaling exponent of the signal-to-interference-plus-noise-ratio (SINR) is derived for interference-free (IF), maximum-ratio transmission (MRT), and zero-forcing (ZF) operations. Our asymptotic analysis reveals four fundamental operating regimes and the performances of both MRT and ZF operations are fundamentally limited by the UL transmit power for estimating user's channel state information, not the DL transmit power. We obtain the conditions that MRT or ZF operation becomes interference-free, i.e., order-optimal. As higher UL transmit power is provided, more users can be associated and the data rate per user can be increased simultaneously while keeping the order-optimality.

Interference coordination for millimeter wave communications in 5G networks for performance optimization

To address the increasing data rate demands for future wireless networks, a dense deployment of base stations or access points is the most promising approach; however, doing so may cause high intercell interference (ICI). Numerous interference coordination (IC) approaches have been proposed to reduce ICI. Conducting 5G communication on millimeter wave (mmWave) bands is more complex because of its higher propagation losses and greater attenuation variance, all of which depend on environment change. Massive antenna arrays with beamforming techniques can be used to overcome high propagation loss, reduce interference, deliver performance gains of coordination without a high overhead, and deliver high network capacity with multiplex transmitters. The central challenge of a massive antenna array that uses beamforming techniques is coordinating the users and beams for each transmitter within a large network. To address this challenge, we propose a novel two-level beamforming coordination approach that partitions a large network into clusters. At the intracluster level, this approach performs intracluster coordination similar to the user selection algorithms in a multiuser multiple input and multiple output (MU-MIMO); doing this maximizes the utility function or minimizes the signal-to-interference-plus-noise ratio (SINR) function within a cluster. A dynamic time domain IC approach is employed at the intercluster level, collecting interference information for cluster-edge user equipment (UE) and allocating the UE dynamically among the clusters to reduce the intercluster interference for a switched-beam system (SBS). Simulation results show that the proposed two-level IC approach achieves a higher edge user performance or cell capacity than with the current uncoordinated/coordinated approaches.

Asymptotic Performance Analysis of Massive MIMO Relay Systems With Multi-Pair Devices Over Correlated Fading Channels

In this paper, we investigate a relay system with multi-pair single-antenna devices, where massive antenna array (also known as massive multiple-input-multiple-output (MIMO) technology) is deployed at the relay with low-complexity maximum-ratio combining/maximum-ratio transmission precoding scheme. By combining massive MIMO and relay cooperation, the performance of relay-assisted communication systems is predicted to be dramatically improved in many areas, e.g., spectral efficiency, energy efficiency, inter-user interference cancelation, and so on, by exploring the abundant spatial degree of freedom of massive MIMO. However, a large number of antennas employed at relay node inevitably leads to antenna correlation because of small antenna spacing subjected to the limited size of the relay node, which may affect the system performance and has not yet been compressively studied. Thus, we focus on analyzing the effect of antenna correlation on the asymptotic performance of system ergodic rate by using a general channel correlation model. First, by means of the deterministic equivalent technology, the analytical expression of the ergodic rate with arbitrary channel correlations is derived, which presents the quantitative relations among system parameters, i.e., the numbers of relay antennas and device-pairs, the channel spatial correlations at the relay's receiver side and the transmitter side, and the transmit powers of the source devices and the relay. By using a general scaling model for system parameters with respect to the relay antenna number, the asymptotic performance of the ergodic rate under spatially correlated channel and the corresponding scaling laws of the system parameters are obtained, which provides useful guidelines to trade off the transmit power and the ergodic rate as well as the number of the served device-pairs. It is further revealed that the influence degrees of the antenna correlations at the relay's receiver and the transmitter on the ergodic rate is nearly the same. Finally, the analytical conclusions are justified through the numerical simulations.

Performance, Power, and Area Design Trade-Offs in Millimeter-Wave Transmitter Beamforming Architectures

Millimeter wave (mmW) communications is the key enabler of 5G cellular networks due to vast spectrum availability that could boost peak rate and capacity. Due to increased propagation loss in mmW band, transceivers with massive antenna array are required to meet link budget, but their power consumption and cost become limiting factors for commercial systems. Radio designs based on hybrid digital and analog array architectures and the usage of radio frequency (RF) signal processing via phase shifters have emerged as potential solutions to improve energy efficiency and deliver performances close to digital arrays. In this paper, we provide an overview of the state-of-the-art mmW massive antenna array designs and comparison among three architectures, namely digital array, sub-array, and fully-connected hybrid array. The comparison of performance, power, and area for these three architectures is performed for three representative 5G use cases, which cover a range of pre-beamforming SNR and multiplexing regimes. This is the first study to comprehensively model and analyze all design aspects and criteria including: 1) optimal linear precoder, 2) impact of quantization error in DAC and phase shifters, 3) RF signal distribution network, 4) power and area estimation based on state-of-the-art mmW circuits including baseband precoding, digital signal distribution, DACs, oscillators and mixers, phase shifters, RF signal distribution, and power amplifiers. The results show that the digital array is the most power and area efficient compared against optimal design for each architecture. Our analysis shows digital array benefits greatly from multi-user multiplexing. The analysis also reveals that sub-array is limited by reduced beamforming gain due to array partitioning, and system bottleneck of the fully-connected hybrid architecture is the excessively power hungry RF signal distribution network.

Efficacy of Hybrid Energy Beamforming With Phase Shifter Impairments and Channel Estimation Errors

Hybrid energy beamforming (HEB) can reduce the hardware cost, energy consumption, and space constraints associated with massive antenna array transmitter (TX). With a single radio frequency chain having $N$ digitally controlled phase shifter pairs, one per antenna element, theoretically achieving the same performance as a fully digital beamforming architecture with $N$ RF chains, this letter investigates the practical efficacy of the HEB. First adopting the proposed analog phase shifter impairments model and exploiting the channel reciprocity along with the available statistical information, we present a novel approach to obtain an accurate minimum mean-square error estimate for the wireless channel between TX and energy receiver (RX). Then, tight analytical approximation for the global optimal time allocation between uplink channel estimation and downlink energy transfer operations is derived to maximize the mean net harvested energy at RX. Numerical results, validating the analysis and presenting key design insights, show that with an average improvement of $\text{58}{\%}$ over the benchmark scheme, the optimized HEB can help in practically realizing the fully digital array gains.

Wireless-Powered Device-to-Device-Assisted Offloading in Cellular Networks

Offloading cellular traffic to device-to-device (D2D) communications has been proposed to improve the network capacity and to alleviate the traffic burden on base stations (BSs). However, as mobile devices are powered by limited battery energy, there is no obligation for D2D transmitters (D2D-Txs) to offload cellular traffic through D2D content sharing. In this paper, we model and analyze the wireless-powered D2D-assisted offloading (WPDO) in cellular networks, where the D2D-Txs can harvest radio frequency energy from nearby BSs and utilize the harvested energy to share popular contents with nearby user equipments. Stochastic geometry is used to characterize the intrinsic relationship between the wireless power transfer (WPT) and the information transmission. Based on the proposed model, we derive the average transmit power at D2D-Tx, the expected minimum transmit power at BS, the D2D outage probability, and the cellular downlink outage probability. We also investigate the energy efficiency of the WPDO network from a system-level perspective. Simulation and numerical results show that the energy efficiency of the WPDO network can be maximized by optimizing the fraction of time allocated for WPT and it can be further improved by using massive antenna arrays at each BS and by sharing more popular contents between devices.

Equal-Gain Transmission in Massive MIMO Systems Under Ricean Fading

This paper considers a multicell downlink (DL) massive MIMO system operating over Ricean fading channels in which each base station (BS) is equipped with a massive antenna array, while each user has a single antenna. We explore equal-gain transmission (EGT), line-of-sight (LOS) component-based EGT (LOS-EGT) and maximum-ratio transmission (MRT) under imperfect channel state information. Closed-form expressions for lower bounds of the achievable rates are derived for EGT over Ricean and Rayleigh fading channels, and for LOS-EGT and MRT over Ricean fading channels. With the obtained closed-form expressions, various power scaling laws concerning DL data transmit power and uplink (UL) pilot transmit power are established and discussed. In particular, it is found that, as the number of BS antennas $M$ grows unlimited, the lower bounds on the rates achieved with EGT, LOS-EGT and MRT schemes approach infinity and are not affected by pilot contamination, while the DL data transmit power and UL pilot transmit power can be scaled down proportionally to ${M^{ -a}}$ and ${M^{ - b}}$ (where $0 \leq a and $b > 0$ ), respectively. Numerical results corroborate the tightness and accuracy of these closed-form expressions and they also show that, when the number of antennas and intercell interference level are large, compared to the MRT, EGT and LOS-EGT are more resistant to intercell interference and pilot contamination.

Hybrid preprocessing aided spatial modulation in multi‐user massive MIMO systems

Massive multiple-input multiple-output (MIMO) as a promising technology to achieve high spectral efficiency encounters the problem of high cost and complexity of hardware implementation for digital signal processing. One proposed solution is hybrid analogue–digital processing to reduce the number of radio-frequency (RF) chains required at massive antenna arrays. In this study, hybrid analogue–digital preprocessing aided spatial modulation is introduced to the downlink of multi-user massive MIMO systems. Linear zero-forcing (ZF) and regularised ZF preprocessors which are near-optimal in massive MIMO systems and a low-complexity two-stage preprocessing scheme based on block-diagonalisation are proposed. These full-digital schemes are implemented in hybrid RF-baseband domain through a low-dimensional processor based on the baseband effective channel and phase controllers at the RF domain. The spatially correlated and sparsely scattered millimetre wave channels are adopted to consider the proposed preprocessing schemes. Under an imperfect channel state information at the transmitter, the robust design of full digital and hybrid analogue-digital preprocessors is presented using stochastic robust approximation. Furthermore, the hybrid RF-baseband preprocessors are realised using heavily quantised angles and the preprocessing schemes are investigated from the data rate point of view. The simulation results show desirable performance and close to that of full digital preprocessing is achieved by proper configuration of system.

IR-UWB Sensor Network Using Massive MIMO Decision Fusion: Design and Performance Analysis

This paper proposes and analyzes impulse radio ultra-wideband (IR-UWB) system for wireless sensor networks (WSNs) using massive antenna arrays (MAAs) at fusion center (FC) for distributed detection. The coherent- and energy-based fusion rules are analyzed for the proposed WSN over multiple access channels. The tradeoff between the performance and the implementation complexity of the coherent- and energy-based fusion is studied. Furthermore, we show that MAAs at FC with various levels of channel knowledge can enhance the performance of energy-based detector in a UWB sensor network with simple system implementation and signal processing. Performance of the proposed UWB sensor network with reference to probability of detection, false alarm, and error are analyzed over the standard IEEE 802.15.4a multipath channels and results are validated using simulations. We have also analyzed the impact of various design parameters, such as the number of sensors, receiver antennas, sensor quality, and integration interval, on the system performance.

Single-Anchor Localization and Orientation Performance Limits Using Massive Arrays: MIMO vs. Beamforming

In the next generation of cellular networks, it is desirable to use single access points both for communication and localization. This could be made possible thanks to the combination of femtocells, mm-wave technology and massive antenna arrays, and would overcome the problem of having an over-sized infrastructure for positioning which is, nowadays, the bottleneck for the widespread diffusion of indoor localization systems. In this context, our paper aims at investigating the localization and orientation performance limits employing massive arrays both at the access point and mobile side. To this end, we first asymptotically demonstrate the tightness of the Cramer-Rao bound (CRB) in the massive array regime and that the effect of multipath can be made negligible even for practical values of SNR levels. Successively, we propose a comparison between two different transmitter configurations, namely multiple-input multiple-output (MIMO), where orthogonal waveforms are sent, and beamforming, which takes advantage of highly correlated waveforms and directive array patterns. We also consider random weighting as a trade-off between the diversity gain of MIMO and the high directivity guaranteed by the beamforming. CRB results show the interplay between diversity and beamforming gain as well as the benefits achievable by varying the number of antennas in terms of localization accuracy and multipath mitigation.

Time Varying Channel Tracking With Spatial and Temporal BEM for Massive MIMO Systems

In this paper, we design a channel tracking method for massive multiple-input multiple-output systems under both time-varying and spatial-varying circumstances. By exploiting the characteristics of massive antenna array, a spatial-temporal basis expansion model is proposed to reduce the effective dimension of uplink/downlink channel, which decomposes channel state information into time-varying spatial information and gain information. We first model the user’s movement as the one-order unknown Markov process, whose parameters are blindly obtained by expectation and maximization learning. Then, the uplink time-varying spatial information can also be blindly tracked by unscented Kalman filter and Taylor series expansion of the steering vector, while the rest of uplink channel gain information can be trained by only a few pilot symbols. Due to physical angle reciprocity, the spatial information of the downlink channel can be immediately computed from the uplink counterpart, which greatly reduces the complexity of downlink channel tracking. Various numerical results are provided to demonstrate the effectiveness of the proposed method.

Low-Complexity and High-Accuracy Semi-blind Joint Channel and Symbol Estimation for Massive MIMO-OFDM

In order to fully exploit the scarce spectrum, antenna arrays are incorporated into wireless communication devices in 4G and 5G communication networks to deploy MIMO-OFDM systems. Recently, the least squares Khatri–Rao factorization has been applied to MIMO-OFDM systems for semi-blind joint channel and symbol estimation. Its cubic computational complexity is prohibitive when the number of transmit and receive antennas is very large. Therefore, the average vector and Hadamard ratio rank one approximation has been proposed for MIMO-OFDM systems, showing a linear complexity, but being limited to channels and transmitted symbols with offsets. In this paper, we present four novel MIMO-OFDM algorithms for massive antenna array systems that outperform the state-of-the-art approaches in terms of complexity and/or accuracy. The four proposed schemes are the alternating least squares with vector selection initialization, the vector projection rank one approximation including vector selection rank one initialization, the factorization based on eigenvalue decomposition with eigenvector projection and the factorization based on sectional truncated singular value decomposition and vector projection. Our analytical complexity analysis and numerical results corroborate the trade-offs offered by the different receiver algorithms in terms of complexity, parallelism and performance.

The off‐grid frequency selective millimeter wave channel estimation

SummaryBroadband millimeter wave (mmW) systems are a promising pioneer of cellular communication for next generation which is utilizing the hybrid baseband/analog beamforming structures along with the miniature massive antenna arrays at both sides of the communication link. mmW channel with an available unlicensed spread spectrum is frequency selective because the signal bandwidth can be larger than the coherence bandwidth. Due to the sparse nature of mmW channel, extracting compressive sensing model of the system is preferable. In fact, exploiting the sparse structure will lead to the reduction of the computational complexity, because there is a reduction in the channel training length compared with the conventional methods such as least square estimation. Most of the prior works have considered on‐grid quantized departure/arrival angles in the input/output antennas to obtain a sparse virtual channel model. However, the sparse angles in the physical channel model are continuous where this continuity indicates a mismatch between the physical angles and the on‐grid angles. Such a mismatch will contribute to unwanted components in the virtual channel model. Given these extra components, the conventional compressive sensing tools are unable to recover the channel. In this paper, we propose two solutions for overcoming the problem caused by off‐grid angle selection. The first is based on the vector shaping, and the second one is based on the sparse total least square concepts. Simulation results demonstrate that the proposed methods both could obtain an adequate channel recovery and are preferable regarding computational complexity concerning the newly developed surrogate method.

Noncoherent IR-UWB Receiver Using Massive Antenna Arrays for Wireless Sensor Networks

Noncoherent impulse radio ultrawideband (UWB) receivers do not require channel state information and are also robust against pulse shape distortions. However, their performance is suboptimal, especially at low signal-to-noise ratios. In this article, we propose simple noncoherent UWB receivers for wireless sensor network applications using massive antenna arrays. Two receivers are proposed: based on instantaneous received UWB signal energy and based on weighted instantaneous received UWB signal energy. The proposed receivers use the law of large numbers resulting from the massive receiver arrays and utilize the large degrees of freedom available in a UWB multipath channel. Furthermore, the proposed receivers do not require training symbols for the estimation of decision threshold. Both these receivers outperform the existing noncoherent receivers as verified using simulation results on the standardized IEEE 802.15.4a UWB multipath channel.

Link Budget Analysis for Massive-Antenna-Array-Enabled Terahertz Satellite Communications

Broadband satellite communications can enable a plethora of applications in customer services, global nomadic coverage and disaster prediction and recovery. Terahertz (THz) band is envisioned as a key satellite communication technology due to its very broad bandwidth, astrophysical observation advantages and device maturing in recent years. In this paper, a massive-antenna-array-enabled THz satellite communication system is proposed to be established in Tanggula, Tibet, where the average altitude is 5.068 km and the mean-clear-sky precipitable water vapor (PWV) is as low as 1.31 mm. In particular, a link budget analysis (LBA) framework is developed for THz space communications, considering unique THz channel properties and massive antenna array techniques. Moreover, practical siting conditions are taken into account, including the altitude, PWV, THz spectral windows, rain and cloud factors. On the basis of the developed link budget model, the massive antenna array model, and the practical parameters in Tanggula, the performances of signal-to-noise ratio (SNR) and capacity are evaluated. The results illustrate that 1Tbit/s is attainable in the 0.275—0.37 THz spectral window in Tanggula, by using an antenna array of the size 64.

Beam Tracking for UAV Mounted SatCom on-the-Move With Massive Antenna Array

Unmanned aerial vehicle (UAV)-satellite communication has drawn dramatic attention for its potential to build the integrated space-air-ground network and the seamless wide-area coverage. A key challenge to UAV-satellite communication is its unstable beam pointing due to the UAV navigation, which is a typical SatCom on-the-move scenario. In this paper, we propose a blind beam tracking approach for Ka-band UAV-satellite communication system, where UAV is equipped with a hybrid large-scale antenna array. The effects of UAV navigation are firstly released through the mechanical adjustment, which could approximately point the beam towards the target satellite through beam stabilization and dynamic isolation . Specially, the attitude information for mechanical adjustment can be realtimely derived from data fusion of low-cost sensors. Then, the precision of beam pointing is blindly refined through electrically adjusting the weight of the massive antennas, where an array structure based simultaneous perturbation algorithm is designed. Simulation results are provided to demonstrate the superiority of the proposed method over the existing ones.

Millimeter-Wave Massive MIMO Communication for Future Wireless Systems: A Survey

Several enabling technologies are being explored for the fifth-generation (5G) mobile system era. The aim is to evolve a cellular network that remarkably pushes forward the limits of legacy mobile systems across all dimensions of performance metrics. One dominant technology that consistently features in the list of the 5G enablers is the millimeter-wave (mmWave) massive multiple-input-multiple-output (massive MIMO) system. It shows potentials to significantly raise user throughput, enhance spectral and energy efficiencies and increase the capacity of mobile networks using the joint capabilities of the huge available bandwidth in the mmWave frequency bands and high multiplexing gains achievable with massive antenna arrays. In this survey, we present the preliminary outcomes of extensive research on mmWave massive MIMO (as research on this subject is still in the exploratory phase) and highlight emerging trends together with their respective benefits, challenges, and proposed solutions. The survey spans broad areas in the field of wireless communications, and the objective is to point out current trends, evolving research issues and future directions on mmWave massive MIMO as a technology that will open up new frontiers of services and applications for next-generation cellular networks.

Improved Design of an Adaptive Massive MIMO Spherical Antenna Array

Massive capacity and connectivity are the main boundaries towards standing the Internet of Everything (IoE) basis and defining modern wireless generation requirements. These needs cannot be achieved by already deployed phased array antenna in terms of distributed and oriented geometry, dimensions and design. We propose in the present paper an innovating massive multiple input multiple output (MIMO) spherical array network aiming to draw a new three-dimensional configuration to enhance the beam steering, improve bandwidth, total capacity and the scan flexibility. Resolved issues in concordance with 5G requirements are adaptive massive MIMO by using millimeter-wave antenna arrays, small cell design and definition of recommended operational frequency considering the International Telecommunication Union (ITU) norms and directives. The new geometric forms of spherical smart antenna could easily scan all 3D space, ensure higher capacity and reach tens of Giga bit per second (Gbps) value besides eradicating energy wastage aspect of Beam Division Multiple Access (BDMA) in base stations. Mathematical design is detailed and performed simulation results are presented using MATLAB software Tool.

A Framework to Channel Feedback and Reconstruction using Matrix Completion in Massive MIMO Systems

In this paper, we are interested in the problem of channel feedback and reconstruction in frequency division duplexing (FDD)-based massive multiple-input-multiple-output (MIMO) systems. We propose a general framework that allows reducing the overhead significantly in the uplink feedback control channel when assuming massive antenna arrays at both ends of the wireless link. We investigate the methods capitalize on matrix completion to reducing the feedback overhead. The fundamental idea of the proposed method is to explore the low-rank structure of the channel for its accurate reconstruction at the transmitterside (Tx) with very few uplink feedback information, using matrix completion technique. The proposed framework consisting of two stages. First, upon reception of downlink pilots, the receiver side (Rx) undersamples either the received pilot data matrix or the estimated channel matrix and feeds back only a fraction of their entries to the Tx, throwing away the remaining ones. Then, under the assumption of reduced scattering propagation, the Tx capitalizes on matrix completion to recover either the downlink pilots or directly reconstruct the downlink channel. We consider two application examples: i) backhauling communication and ii) a multi-user equipment (UE) scenario with perfect andimperfect instantaneous channel knowledge. Due to data/channel undersampling, energy consumption at a receiver can be reduced during the uplink feedback transmission. Simulation results show that, compared to the conventional full-feedback approach, which requires feedback of the entire matrix, the proposed solution can decrease the feedback overload in more than 90% for low-rank channels, while providing good channel estimation accuracy, bit error rate (BER) under maximum ratio transmission (MRT) precoding and goodput.