MIMO Beamforming Research Articles

Hybrid MVDR-LMS beamforming for Massive MIMO

<p>With the high speed of communication in LTE-5G, fast beamforming techniques need to be adopted. The training time required to form and steer the main lobes toward 5G multiple users must be short. Least-Mean-Square (LMS) training time is not suitable to work with in LTE-5G, but it has a good performance in forming multiple beams to large number of users and producing nulls in the interference direction. In this paper, an optimized hybrid MVDR-LMS beamforming algorithm is proposed to reduce the time required to estimate the antenna’s weights. This optimization is made by the benefit of previously set weights calculated using MVDR algorithms. The performance of the proposed hybrid MVDR-LMS algorithm tested using MATLAB 2016a.</p>

3D‐MIMO beamforming realised by AQPSO algorithm for cylindrical conformal phased array

Three-dimensional (3D)-MIMO beamforming realised by adaptive quantum particle swarm optimisation (AQPSO) algorithm for the 36-element cylindrical conformal phased array is proposed in this study. The cylindrical conformal phased array consists of 36 circularly polarised microstrip antenna elements with ultra-wideband and high gain characteristics. The conformal array is divided into 12 subarrays using reconfigurable technology, and each subarray produces six beams to cover the corresponding spatial area. The 3D-MIMO beam is formed by AQPSO, and the active element pattern data of array elements is introduced to AQPSO to improve the accuracy of the algorithm. The simulated and measured results show that the cylindrical conformal phased array can achieve 3D-MIMO beam coverage from 0° to 360° in the azimuth plane and from 67.5° to 112.5° in the elevation plane. It can be applied for satellite communication and fifth-generation base station communication.

MIMO Beamforming Schemes for Hybrid SIC FD Radios With Imperfect Hardware and CSI

We study a multiple-input multiple-output (MIMO) full-duplex (FD) radio system, aiming to increase the feasibility of this technology in bi-directional communications. In particular, we consider that the FD radios are equipped with the State-of-the-Art (SotA) hybrid SI cancellation (SIC) capabilities, but must cope with hardware (HW) and channel state information (CSI) imperfections, contributing four new MIMO beamforming (BF) schemes for such systems. The first is a transmit (TX) beamforming scheme designed via a Fractional Programming (FP) approach, matched with a minimum mean square error (MMSE) beamformer at the receiver. In this benchmark, the FP-based method, the signal to interference-plus-noise ratio (SINR) constraints are relaxed via the quadratic transform (QT), which allows for the SINR-constrained TX-power minimization problem to be solved using interior point methods. Motivated by the high complexity of the latter, three low-complexity alternatives are then derived, in which power minimization is performed via the Perron–Frobenius (PF) approach, while the TX-BF vectors are obtained, respectively, via direct Gradient Projection (GP), QT-relaxation, and via a Double Rayleigh Quotient (DRQ) reformulation of the original optimization problem. The simulation results confirm the significant gains achieved by all four schemes over the SotA, revealing the GP and DRQ as the overall best alternatives depending on power limitation, and HW/CSI qualities.

High Speed Mobility Experiments on Distributed MIMO Beamforming for 5G Radio Access in 28-GHz Band

High Speed Mobility Experiments on Distributed MIMO Beamforming for 5G Radio Access in 28-GHz Band

Area Energy Efficiency of Antenna Selection in Limited Feedback Device-to-Device Networks

We analyze the area energy efficiency of a device-to-device communication network with limited feedback employing antenna selection (AS). By considering that devices are distributed according to a homogeneous Poisson point process, we derive expressions for the AS and an MIMO beamforming (BF) scheme, used as a performance benchmark. Numerical results show that AS is more energy efficient for shorter transmission distances, even if BF employs a theoretically infinite number of feedback bits. On the other hand, BF outperforms AS in terms of spectral efficiency, even using the same number of feedback bits.

Transceiver Design With UCD-Based Hybrid Beamforming for Millimeter Wave Massive MIMO

Hybrid transceiver designs for millimeter wave massive multiple-input multiple-output systems are feasible candidates to reduce the volume of radio frequency (RF) chains, decomposing the signal processing into the analog and digital domains. The existing schemes heavily depend on the singular value decomposition to obtain subchannels with uneven power gains, causing bit error rate (BER) performance degradation. In this paper, we propose a hybrid transceiver design based on the uniform channel decomposition (UCD), yielding subchannels with identical gains to improve the BER performance. Inspired by the UCD concept, we derive an equivalent optimization problem and propose two schemes, namely, phase-extraction and iterative update, to determine the RF beamformers, yielding an effective baseband channel with the greatest possible geometric mean of singular values. We apply the UCD with a minimum mean squared error criterion to complete the baseband beamforming. Finally, we combine the hybrid UCD beamforming with the vertical-Bell Labs layered space-time and dirty paper coding, to eliminate the inter-subchannel interference. An asymptotic analysis of the scheme performance is also pursued. The simulation results show that the proposed hybrid scheme outperforms the conventional schemes on the transmission BER, which achieves a spectral efficiency close to that of the fully-digital counterpart.

A Correlation Theory of Antenna Directivity With Applications to Superdirective Arrays

We develop a general approach to antenna directivity by combining the infinitesimal dipole model (IDM) and the cross-correlation Green's function (CGF) in a new formulation. The theory is deployed for the analysis and synthesis of antenna systems via the proposed IDM-CGF method after integration with global optimization algorithms. The IDM-CGF theory opens the door for hitherto unexplored connections between applications involving antenna gain engineering on one side, and multiple-input–multiple-output (MIMO) and diversity methods on the other, helping to devise new techniques for applications like massive MIMO and millimeter-wave beamforming algorithms, wireless power transfer, in-package antennas, and full three-dimensional isotropicity.

Observation-Based Optimization for POMDPs With Continuous State, Observation, and Action Spaces

This paper considers the optimization problem for partially observable Markov decision processes (POMDPs) with the continuous state, observation, and action spaces. POMDPs with the discrete spaces have emerged as a promising approach to the decision systems with imperfect state information. However, in recent applications of POMDPs, there are many problems that have continuous states, observations, and actions. For such problems, due to the infinite dimensionality of the belief space, the existing studies usually discretize the continuous spaces with the sufficient or nonsufficient statistics, which may cause the curse of dimensionality and performance degradation. In this paper, based on the sensitivity analysis of the performance criteria, we have developed a simulation-based policy iteration algorithm to find the local optimal observation-based policy for POMDPs with the continuous spaces. The proposed algorithm needs none of the specific assumptions and prior information, and has a low computational complexity. One numerical example of the complicated multiple-input multiple-output beamforming problem shows that the algorithm has a significant performance improvement.

Maximizing Information Extraction of Extended Radar Targets Through MIMO Beamforming

We jointly design an information-theoretic transmit and receive radar beamformers for spatially near multiple extended targets. We maximize the mutual information (MI) between the received signals and the targets signatures that allows the extraction of the unknown features, which may include shape, dimensions, and material. However, high interference caused by spatially near targets might obstruct the information extraction, and directing the beamformers toward the steering vector as done in conventional beamformers does not solve this problem, especially for extended targets. In this letter, an iterative algorithm is presented to solve this problem using alternative minimization, dividing it into two blocks. The first block is solving for the transmit beamformers successively using block coordinate descent, and the second one is solving for the receiver beamformers using the minimum variance distortionless response. We also show the effect of using our beamformers on the waveform design problem. Numerical results indicate that this algorithm can achieve substantially higher MI than the existing conventional methods. Thus, except for some degenerate cases, having fixed beamformers instead of optimized ones lead to significant performance degradation.

Modified Conjugate Beamforming for Cell-Free Massive MIMO

We present a modification of conjugate beamforming for the forward link of cell-free massive MIMO networks. This modification eliminates the self-interference and yields a performance that, without forward pilots, closely approaches what would be achieved with such pilots in place. The simplicity of conjugate beamforming is preserved, with no need for matrix inversions, at the expense of fading-rate coordination among the access points.

Coulomb Gas Analogy: A Statistical Physics Approach to Performance Analysis of MIMO Systems

In this correspondence, by adopting the Coulomb gas analogy that is an analytical approach from statistical physics, we derive a closedform approximation of the cumulative distribution function (CDF) of the largest eigenvalue of a random Gram matrix H <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H</sup> H, where H denotes the channel matrix of a multiple-input multiple-output (MIMO) system. The expression of approximation has a simple structure in terms of several elementary functions, which is derived by assuming that the entries of H have Nakagami-m distributed amplitude with an independent phase. This assumption is made because it applies in two common cases of the Nakagami-m distributions, i.e., with a uniformly distributed phase and a complex signal model. Simulation results indicate that the theoretical expression also provides a good approximation to the CDF for Rice and Hoyt distributions when the CDF is within a near-one range. This range takes the form of (P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">no</sub> ,1), where we assume P <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">no</sub> = 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> by default in this study. The derived approximation can find many uses for the performance analysis of MIMO beamforming and singular value decomposition MIMO systems, e.g., evaluating the outage probability for these systems.

Reducing the Codeword Search Complexity of FDD Moderately Large MIMO Beamforming Systems

It is of great interest to develop larger scale multiple-input multiple-output (MIMO) technology based on frequency division duplexing (FDD) for backward compatibility with existing standards and already deployed cellular networks. One hindrance to the FDD approach is the complexity of the codeword search performed by the receiver, which is known to scale with the number of transmit antennas $N_{t}$ in a system. The codeword search complexity does not scale linearly and soon becomes infeasible even for the not-so-massive MIMO systems expected in the very near future. We address this problem by proposing a natural sequence-based orthogonal codebook and an intra-array interference magnitude (IIM) framework for MIMO beamforming based on quantized equal gain transmission that altogether tremendously simplifies the codeword search problem. We also present an assessment on the quality of the codeword selected by the proposed framework that explains it’s near optimal performance, and, provide detailed codeword search complexity quantification. Finally, we provide simulation analyses of beamforming gain under time selective fading channels and an FDD MIMO system transmit delay model. Our analyses indicate that despite significantly reducing complexity, the proposed IIM framework executed by already commercialized processors is capable of approaching the ideal performance of an static system even in the presence of time-selectivity inherent to high-speed mobile communications. Our analyses also quantify the impact of feedback delay on average beamforming gain of moderately large transmit arrays.

On Measuring Electromagnetic Fields in 5G Technology

At the awakening of the new 5G network as the network of services, issues related to electromagnetic fields (EMFs) will become one of the key aspects for the cost-effective establishment of the 5G infrastructure. The new 5G services will meet the rigorous demand for bandwidth through the implementation of a large number of densely located base stations operating in the millimeter-wave range. Introduction of new emission sources, working in parallel with already existing 2G/3G/4G mobile technologies, raises concerns about exceeding the admissible EMF exposure limits. This paper analyzes issues and challenges related to EMF measurements in 5G technology, which are crucial for the assessment of EMF compliance with regulatory limits. We point out that the existing methodologies, dedicated to EMF measurements in 2G, 3G, and 4G networks, are not suitable for 5G. The reason is the use of new techniques, such as massive MIMO and precise beamforming together with higher frequency bands so that the existing measurement methods can lead to significantly overestimated results when they will be applied to 5G networks. Such results, in conjunction with the restrictive legislation on the EMF limits that apply in some countries, may have the negative impact on 5G network deployment, making it difficult to achieve the intended 5G network capabilities. We also propose an alternative method of EMF exposure assessment that is based on calculations and simulations and allows obtaining an accurate estimation of the EMF distribution in the 5G environment.

The Design and Applications of High-Performance Ray-Tracing Simulation Platform for 5G and Beyond Wireless Communications: A Tutorial

The application scenarios and requirements are more diverse in the fifth-generation (5G) era than before. In order to successfully support the system design and deployment, accurate channel modeling is important. Ray-tracing (RT) based deterministic modeling approach is accurate with detailed angular information and is a suitable candidate for predicting time-varying channel and multiple-input multiple-output (MIMO) channel for various frequency bands. However, the computational complexity and the utility of RT are the main concerns of users. Aiming at 5G and beyond wireless communications, this paper presents a comprehensive tutorial on the design of RT and the applications. The role of RT and the state-of-the-art RT techniques are reviewed. The features of academic and commercial RT based simulators are summarized and compared. The requirements, challenges, and developing trends of RT to enable the visions are discussed. The practices of the design of high-performance RT simulation platform for 5G and beyond communications are introduced, with the publicly available high-performance cloud-based RT simulation platform as the main reference. The hardware structure, networking, workflow, data flow and fundamental functions of a flexible high-performance RT platform are discussed. The applications of high-performance RT are presented based on two 5G scenarios, i.e., a 3.5 GHz Beijing vehicle-to-infrastructure scenario and a 28 GHz Manhattan outdoor scenario. The questions on how to calibrate and validate RT based on measurements, how to apply RT for mobile communications in moving scenarios, and how to evaluate MIMO beamforming technologies are answered. This tutorial will be especially useful for researchers who work on RT algorithms development and channel modeling to meet the evaluation requirements of 5G and beyond technologies.

A Deep-Learning-Based Radio Resource Assignment Technique for 5G Ultra Dense Networks

Recently, deep learning has emerged as a state-of-the-art machine learning technique with promising potential to drive significant breakthroughs in a wide range of research areas. The application of deep learning for network traffic control, however, remains immature due to the difficulty in uniquely characterizing the network traffic features as an appropriate input and output dataset to the learning structures. The network traffic features are anticipated to be even more dynamic and complex in the UDNs of the emerging 5G networks with high traffi c demands coupled with beamforming and massive MIMO technologies. Therefore, it is critical for 5G network operators to carry out radio resource control in an efficient manner instead of adopting the simple conventional F/TDD. This is because the conventional uplink-downlink configuration change in the existing dynamic TDD method, typically used for resource assignment in beamforming and massive-MIMO-based UDNs, is prone to repeated congestion. In this article, we address this issue and discuss how to leverage the deep LSTM learning technique to make localized prediction of the traffic load at the UDN base station (i.e., the eNB). Based on localized prediction, our proposed algorithm executes the appropriate action policy a priori to avoid/alleviate the congestion in an intelligent fashion. Simulation results demonstrate that our proposal outperforms the conventional method in terms of packet loss rate, throughput, and MOS.

MIMO Beamforming Design in Nonorthogonal Multiple Access Downlink Interference Channels

Nonorthogonal multiple access (NOMA) has been considered as a promising technology for fifth-generation wireless communication systems. In this paper, we consider a two-cell multiple-input-multiple-output NOMA downlink interference channel with one multiantenna base station (BS) and multiple multiantenna users in each cell. Each user treats interferences from adjacent cell as additional noises and does not attempt to decode them. This paper aims to design interference channel beamformers to maximize weighted sum capacity of the strongest users in two cells under quality of service requirements at other users and transmit power budget constraint at each BS. Such problem is complicated and nonconvex due to the expression of a logarithm of a determinant $(\log \det)$ minus $\log \det$ in the objective function and constraints. For the nonconvex problem, we put forward a successive convex approximation (SCA) based iterative algorithm. Since the computational complexity of SCA-based iterative algorithm is high, we also put forward an efficient majorization-minimization based iterative algorithm. Based on simulation results, we show that our developed NOMA schemes are superior to the zero-forcing-based NOMA, orthogonal-NOMA, and orthogonal multiple access schemes.

BER minimisation via optimal power allocation and eigenbeamforming in MIMO systems

In this contribution, the convex optimisation technique is deployed to optimize the data transmission in MIMO systems operating via eigenbeamforming. Initially, we study three optimal Power Allocation (PA) policies: the first one is used for maximising the total capacity, the equal power allocation and a PA proportional to the channel gains. In the sequence and more importantly, we propose a PA capable of minimising the average Bit Error Rate (BER) with a variable number of transmit antennas. In order to do so, the optimisation problem is first stated in the standard form; then the convexity of the problem will be proven; and finally, the optimisation problem is solved by using the Karush–Kuhn–Tucker conditions. Numerical results corroborate the analytic solution. Moreover, simulation results for both the average BER and sum capacity performance metrics demonstrate the effectiveness of the proposed beamforming MIMO power allocation schemes in terms of system capacity maximisation or alternatively the BER minimisation (reliability).

MIMO beamforming system for speech enhancement in realistic environment with multiple noise sources

Multiple noise sources in a realistic environment severely degrade the quality and intelligibility of the desired speech signal, thus posing a severe problem for many speech applications. Several noise reduction algorithms have been proposed with a main goal to solve this problem. However, the good performances of such algorithms are severely impaired in realistic environment under multi-noise sources condition. In this paper, the author treats the noise cancellation system as a multiple-input multiple-output (MIMO) beamformer system. The proposed approach consists of two steps. First, the noise signals are generated by applying the white noise sources to a MIMO AR system. Then, the noisy microphone signals are sequentially processed by employing multi-channel linear prediction error filters (MCLPEFs) and multi-channel adaptive noise estimation filters (MCANEFs) in the lower path of the proposed beamformer. The MCLPEFs are used to whiten the input signals, while the MCANEFs are used as a MIMO system identification to perform the modeling process of the noise signals. Finally, the noise signals in the upper path are subtracted from the estimated noises in the lower path to recover an enhanced speech signal. Moreover, the performance of the proposed MIMO approach was validated under a realistic environment with real noise sources.

A Performance Study of Massive MIMO Heterogeneous Networks with Ricean/Rayleigh Fading

Massive multiple-input and multiple-out (massive MIMO) systems and heterogeneous networks (HetNet) are envisioned to meet the new performance objectives of evolving networks. Now, the main challenge of massive MIMO with HetNet in two-tier networks is how to alleviate interference generated by the randomly deployed femtocells to the macro cells. In this paper, we investigate massive MIMO with HetNet, where the intended macro base station (MBS) transmission follows Ricean fading and interfering femto BS transmissions follow Rayleigh fading. Then, by exploiting matrix and stochastic geometric tools, we derive tight approximations for the intended signal power and aggregated interfering power signal. And derive the signal-to-interference (SIR) with the convolution of the two power signals. Then, we obtain the performance objectives: coverage and outage probabilities, and area spectral efficiency. Further, to reduce the cell edge effects and improve the SIR, we study the role of massive MIMO beamforming coordination with the high-powered MBSs. Thus, we develop maxi-min optimization to control the MBS transmit power. Numerical results show that the coverage and outage performance converge for different user locations, pathloss and Ricean factor. The monotonic increase in Ricean factor improves the SIR of a user located within coverage region. Optimal values of macro BS antenna and transmit power guarantee rate-fairness between the coordinating MBSs, and avoid strong Ricean channel correlation. Also, the performance gain is dependent on the user location, but independent of the cell size.

A Compact, Scanning Tightly Coupled Dipole Array With Parasitic Strips for Next-Generation Wireless Applications

A wideband one-dimensional tightly coupled dipole array (TCDA) with enhanced impedance matching is presented in this letter, which consists of eight printed dipole units, a coplanar waveguide with ground feeding network, and two rows of parasitic strips. The feed structure is simple and small with good ports isolation. A $1\times 8$ prototype was fabricated and tested. A four-channel phase-amplitude control board was designed to validate the beam-steering function of the proposed TCDA. This array has a height of only $0.176\;\lambda_{\text{low}}$ , and it exhibits a measured 10 dB return-loss operating bandwidth of 92.7% from 2.2 to 6.0 GHz for the scan angle up to $\pm 45^{\circ }$ broadside radiation. The cross-polarization suppression level is better than 15 dB in the whole scanning range. The measured results show high gains $>$ 6.9 dBi, high efficiency $>$ 67%, and low sidelobe level (SLL) $ $-$ 10 dB over the operating band and scanning angles. This antenna array can be applied in the future massive multiple-input–multiple-output beamforming systems for 5G and other applications.