Beamspace MIMO Research Articles

Hybrid Precoding for mmWave Massive Beamspace MIMO System with Limited Resolution Overlapped Phase Shifters Network

Hybrid Precoding for mmWave Massive Beamspace MIMO System with Limited Resolution Overlapped Phase Shifters Network

Beam-space MIMO-NOMA Technique for mm-Wave Communication Systems

The multi-input-multi-output-antenna Scheme is regarded as the most promising method for next-generation wireless communication networks that employ millimeter-wave (mm-wave) frequencies and enable them to have a large information throughput. As a result of the large number of radio frequency chains, MIMO mm-wave technology has difficulty with energy consumption. The beam space MIMO (or BS-MIMO for short) reduces the total number of radio frequency components or chains (RF-Chains) without degrading performance significantly. Yeti, VS-MIMO restricts the number of clients that can be supported at the same time-frequency domain (cannot exceed the overall RF-chains number ). In order to cope with such problems, it has been intended to include the NOMA technique (which stands for Non-Orthogonal-Multiple-Access) with the concept of beam space to create the extra model of Non-Orthogonal beam space-MIMO (NOMA-BS-MIMO). With such a scheme the base station can support the service for more than one client (supposed to have correlated channels) through the same beam employing the same radio frequency chain, causing the total clients number greater than the number of employed radio chains in the system. In this research, the Spectral Efficiency of a proposed Non-Orthogonal beam space-MIMO has been considered. More specifically, the research proposes and develops a simple iterative algorithm with near-perfect performance in terms of system Spectral Efficiency. To achieve rate balancing across users, the proposed method, SLNR-IV, employs the signal-to-leakage-plus-noise ratio (SLNR) and the intermediate value method. Considering algorithm validity and a particular parameter setting scenario, the proposed strategy improves bandwidth efficiency by around 15% in comparison to the conventional approach based on OFDM and Zero-forcing digital precoder.

Analyses of Beamspace MIMO Channels at 142 GHz

Analyses of Beamspace MIMO Channels at 142 GHz

Beam-Space MIMO Radar for Joint Communication and Sensing With OTFS Modulation

Motivated by automotive applications, we consider joint radar sensing and data communication for a system operating at millimeter wave (mmWave) frequency bands, where a Base Station (BS) is equipped with a co-located radar receiver and sends data using the Orthogonal Time Frequency Space (OTFS) modulation format. We consider two distinct modes of operation. In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Discovery</i> mode, a single common data stream is broadcast over a wide angular sector. The radar receiver must detect the presence of not yet acquired targets and perform coarse estimation of their parameters (angle of arrival, range, and velocity). In <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Tracking</i> mode, the BS transmits multiple individual data streams to already acquired users via beamforming, while the radar receiver performs accurate estimation of the aforementioned parameters. Due to hardware complexity and power consumption constraints, we consider a hybrid digital-analog architecture where the number of RF chains and A/D converters is significantly smaller than the number of antenna array elements. In this case, a direct application of the conventional MIMO radar approach is not possible. Consequently, we advocate a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">beam-space approach</i> where the vector observation at the radar receiver is obtained through a RF-domain beamforming matrix operating the dimensionality reduction from antennas to RF chains. Under this setup, we propose a likelihood function-based scheme to perform joint target detection and parameter estimation in Discovery, and high-resolution parameter estimation in Tracking mode, respectively. Our numerical results demonstrate that the proposed approach is able to reliably detect multiple targets while closely approaching the Cramér-Rao Lower Bound (CRLB) of the corresponding parameter estimation problem.

Beamspace MIMO Systems With Reduced Beam Selection Complexity

Beamspace multiple-input multiple-output (B-MIMO) systems with proper beam selection (BS) promise to lower the radio-frequency (RF) chains overhead with no noticeable degradation in performance. Most of the existing BS schemes are not practical due to the computational cost arising from iterative search or alternating optimization. Hence, this letter examines the complexity reduction of the existing BS with incremental QR precoder (I-QR-P) and decremental QR precoder (D-QR-P). The proposed two-stage and three-stage algorithms reduce the complexity of D-QR-P and I-QR-P, respectively. Both aim to lower complexity by decreasing the candidate beam size by eliminating the beams with no contribution to any user and using matrix perturbation theory to update QR decompositions. Numerical results reveal that the proposed algorithms considerably reduce the complexity while maintaining a similar sum-rate with baseline algorithms.

Threshold-Based User-Assisted Cooperative Relaying in Beamspace Massive MIMO NOMA Systems.

The incorporation of user-assisted cooperative relaying into beamspace massive multiple-input multiple-output (mMIMO) non-orthogonal multiple access (NOMA) system can extend the coverage area and improve the spectral and energy efficiency for millimeter wave (mmWave) communications when a dynamic cluster of mobile user terminals (MUTs) is formed within a beam. We propose threshold-based user-assisted cooperative relaying into a beamspace mMIMO NOMA system in a downlink scenario. Specifically, the intermediate MUTs between the next-generation base station (gNB) and the cell-edge MUT become relaying MUTs after the successful decoding of the signal of the cell-edge MUT only when they meet the predetermined signal-to-interference plus noise ratio (SINR) threshold. A zero forcing (ZF) precoder and iterative power allocation are used to minimize both inter- and intra-beam interferences to maximize the system sum rate. We then evaluate the performance of this system in a delay-intolerant cell-edge MUT scenario. Moreover, the outage probability of the cell-edge MUT of the proposed scheme is investigated and an analytic expression is derived. Simulation results confirm that the proposed threshold-based user-assisted cooperative relaying beamspace mMIMO NOMA system outperforms the user-assisted cooperative relaying in beamspace mMIMO NOMA, beamspace MIMO-NOMA, and beamspace MIMO orthogonal multiple access (OMA) systems in terms of spectrum efficiency, energy efficiency, and outage probability.

Over-the-Air Design of GAN Training for mmWave MIMO Channel Estimation

Future wireless systems are trending towards higher carrier frequencies that offer larger communication bandwidth but necessitate the use of large antenna arrays. Signal processing techniques for channel estimation currently deployed in wireless devices do not scale well to this “high-dimensional" regime in terms of performance and pilot overhead. Meanwhile, training deep learning-based approaches for channel estimation requires large labeled datasets mapping pilot measurements to clean channel realizations, which can only be generated offline using simulated channels. In this paper, we develop a novel unsupervised over-the-air (OTA) algorithm that utilizes noisy received pilot measurements to train a deep generative model to output beamspace MIMO channel realizations. Our approach leverages Generative Adversarial Networks (GAN), while using a conditional input to distinguish between Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) channel realizations. We also present a federated implementation of the OTA algorithm that distributes the GAN training over multiple users and greatly reduces the user side computation. We then formulate channel estimation from a limited number of pilot measurements as an inverse problem and reconstruct the channel by optimizing the input vector of the trained generative model. Our proposed approach significantly outperforms Orthogonal Matching Pursuit on both LOS and NLOS channel models, and EM-GM-AMP – an Approximate Message Passing algorithm – on LOS channel models, while achieving comparable performance on NLOS channel models in terms of the normalized channel reconstruction error. More importantly, our proposed framework has the potential to be trained online using real noisy pilot measurements, is not restricted to a specific channel model and can even be utilized for a federated OTA design of a dataset generator from noisy data.

On the Complexity Reduction of Beam Selection Algorithms for Beamspace MIMO Systems

Beamspace multiple-input multiple-output (B-MIMO) provides a promising solution for reducing the number of required expensive radio frequency (RF) chains without obvious performance loss. However, the high computational complexities of beam selection algorithms prohibits their practical applications in 5G millimeter wave (mmWave) massive MIMO communication systems. Reviewing existing beam selection procedures and using the matrix perturbation theory, the complexity reduction on beam selection for beamspace MIMO is considered in this letter. Two beam selection algorithms, one for B-MIMO systems with classic zero-forcing (ZF) precoder and the other for the systems with QR precoder are proposed. Theoretical analyses and numerical simulations all show that the proposed beam selection algorithms possess a much lower complexity than conventional ones.

Design Simulation and Performance Assessment of Improved Channel Estimation for Millimeter Wave Massive MIMO Systems

In this paper, we have optimize specificities with the use of massive MIMO in 5 G systems. Massive MIMO uses a large number, low cost and low power antennas at the base stations. These antennas provide benefit such as improved spectrum performance, which allows the base station to serve more users, reduced latency due to reduced fading power consumption and much more. By employing the lens antenna array, beam space MIMO can utilize beam selection to reduce the number of required RF chains in mm Wave massive MIMO systems without obvious performance loss. However, to achieve the capacity-approaching performance, beam selection requires the accurate information of beam space channel of large size, which is challenging, especially when the number of RF chains is limited. To solve this problem, in this paper we propose a reliable support detection (SD)-based channel estimation scheme. In this work we first design an adaptive selecting network for mm-wave massive MIMO systems with lens antenna array, and based on this network, we further formulate the beam space channel estimation problem as a sparse signal recovery problem. Then, by fully utilizing the structural characteristics of the mm-wave beam space channel, we propose a support detection (SD)-based channel estimation scheme with reliable performance and low pilot overhead. Finally, the performance and complexity analyses are provided to prove that the proposed SD-based channel estimation scheme can estimate the support of sparse beam space channel with comparable or higher accuracy than conventional schemes. Simulation results verify that the proposed SD-based channel estimation scheme outperforms conventional schemes and enjoys satisfying accuracy even in the low SNR region as the structural characteristics of beam space channel can be exploited.

Energy efficient transmit antenna selection scheme for correlation relied beamspace mmWave MIMO system

mmWave communication system that offers high datarate are accompanied by massive number of antennas for high gain transmission. These large array of antennas requires special beamforming schemes and also requires large number of RF chains. Beamspace MIMO is a beamforming architecture that employs large antenna array and supports limited number of RF chains by converting conventional mmWave channel into sparse channel. Multiple antenna array system are susceptible to antenna correlation effect thereby reducing the system capacity. Transmit antenna selection methods considering the effect of antenna correlation provides feasible solution by maximising the system capacity and energy efficiency. In order to improve the energy efficiency of the transmitted signal three new transmit antenna selection schemes are proposed by considering the effects of antenna correlation. The simulation results demonstrate that the proposed methods improve energy efficiency and sum rate.

Energy-Efficient Power Allocation and Splitting for mmWave Beamspace MIMO-NOMA With SWIPT

Non-orthogonal multiple access (NOMA) has recently been employed into millimeter wave (mmWave) beamspace MIMO to further improve connection density and spectrum efficiency for the emerging cellular internet of things (IoT) with massive IoT sensors and devices. Meanwhile, to achieve energy-efficient green communication, an advanced energy harvesting technique named simultaneous wireless information and power transfer (SWIPT) has been regarded as a promising solution. In this paper, we study the integration of SWIPT in mmWave beamspace MIMO-NOMA system. To improve the energy efficiency while guaranteeing the minimum rate and harvested energy requirements at each IoT node, we analyse the energy efficiency maximization via power allocation at the base station and power splitting at each IoT node. The challenge is that this joint optimization problem is non-convex and intractable due to the presence of intra-beam and inter-beam interference. To tackle it, we propose a two-layer iterative algorithm by leveraging Dinkelbach method and alternating optimization (AO) framework. Specifically, the original fractional objective function is transformed to an equivalent subtractive one via Dinkelbach method at the outer layer, whereas in the inner layer, AO is adopted to address the transformed optimization problem. Numerical results indicate that: 1) the proposed joint power allocation and splitting algorithm can converge within five iterations; 2) the proposed scheme can achieve higher energy efficiency and achievable sum rate compared with the existing scheme and conventional beamspace MIMO with SWIPT.

DESIGN OF CHANNEL FEED-BACK CODEBOOK AND ADDRESSING POWER LEAKAGE PROBLEM IN MM- WAVE MASSIVE MIMO SYSTEM WITH LENS ANTENNA ARRAYS

Objective The modernistic theory of beamspace MIMO, which involves millimeter wave (mm-Wave) and massive MIMO system depending on lens antenna array (LAA) can efficiently decrease the count of power consuming radio frequency (RF) chains. Hence, it is perceived as an optimistic approach for the 5G technology and its successors. Research in beamspace (BmSp) MIMO has yet to be taken into debate the issues of power leakage in channels, therefore resulting in remarkable deterioration in SNR and the sum-rate (SR). A precoding technique for beam aligning and to tackle power leakage issue has been proposed. Initially a network using phase shifters has been designed, which helps RF chains choose beams and collect leaked power in beamspace MIMO. An algorithm based on rotation for precoding, for the available phase shift networks is proposed to align the gains of the channels in the same direction to maximize SNR received by the users. In systems that employ frequency division duplexing (FDD), it is necessary that the channel is fed back to the base station (BS) via feedback based on codebook. There is no devoted codebook for the LAA dependent mm-Wave systems. The codebook design is proposed to address the gap for these systems. In this codebook, initially a large dimension vectors based on recent idea involving angle coherence time are generated. Then relying on obtained vectors in channel subspace, codebook is created by considering lens and beam selection. After that the channel is quantized and given as feedback to the BS. Results Simulation results conveys that the overhead in feedback is proportional to dominant paths for each user which are few and the proposed approach with uniform linear array (ULA) attains the near optimal performance in SR comparing to ideal case of zero power leakage and also obtains superior Energy efficiency (EE) than existing single beam precoding and Multiple beam via multiple RF (MBMRF) structure precoding methods.

GA-MIMO: Genetic Algorithm for Optimization of ESPAR Antenna on Beamspace MIMO

An electronically steerable passive array radiator (ESPAR) antenna can be used on a beamspace (BS)-multiple input multiple output (MIMO) system to reduce the device complexity. An ESPAR antenna has beamforming ability with single RF chain. However, antenna structure and channel conditions affect the number of orthogonal basis pattern which generated using Gram-Schmidt method. Based on this problem, reactance value at each parasitic element need to be optimized to form radiation pattern that required by the BS-MIMO. In this research, Genetic Algorithm (GA) is used to optimize reactance value which represented by the correlation between the desired and achieved radiation pattern, in different number of elements and different channel condition. GA is selected because this problem can be modeled as chromosome and several individual. Furthermore, the result shows in channel-ignorant and channel-aware, antenna with seven elements has a correlation in median value of 99.46% and 90.58%, respectively. Antena electronically steerable passive array radiator (ESPAR) dapat digunakan dalam sistem beamspace (BS)-multiple input multiple output (MIMO) dalam mengatasi kompleksitas perangkat. Antena ESPAR memiliki kemampuan untuk membentuk pola radiasi pada arah tertentu dengan menggunakan terminal tunggal, namun struktur antena dan kondisi kanal mempengaruhi pola dasar ortogonal yang dihasilkan melalui metode Gram Schmidt. Berdasarkan permasalahan tersebut, nilai reaktansi pada setiap elemen parasit perlu dioptimasi sehingga dapat menghasilkan pola radiasi yang dibutuhkan oleh sistem BS-MIMO. Pada penelitian ini, Algoritma Genetika digunakan untuk mengoptimasi nilai reaktansi yang direpresentasikan melalui korelasi antara pola radiasi yang dibutuhkan dengan pola radiasi yang dihasilkan, dalam jumlah elemen yang berbeda dan kondisi kanal yang berbeda. AG dipilih karena permasalahan ini dapat dimodelkan sebagai kromosom dan beberapa individual. Hasil analisis pada kondisi channel-ignorant dan channel-aware menunjukkan bahwa antena dengan tujuh elemen memiliki korelasi nilai median sebesar 99,46% dan 90,58%.

Hybrid Precoding for Beamspace MIMO Systems With Sub-Connected Switches: A Machine Learning Approach

By employing lens antenna arrays, the number of radio frequency (RF) chains in millimeter-wave (mmWave) communications can be significantly reduced. However, most existing studies consider the phase shifters (PSs) as the main components of the analog beamformer, which may result in a significant loss of energy efficiency (EE). In this paper, we propose a switch selecting network to solve this issue, where the analog part of the beamspace MIMO system is realized by a sub-connected switch selecting network rather than the PS network. Based on the proposed architecture and inspired by the cross-entropy (CE) optimization developed in machine learning, an optimal hybrid cross-entropy (HCE)-based hybrid precoding scheme is designed to maximize the achievable sum rate, where the probability distribution of the hybrid precoder is updated by minimizing CE with unadjusted probabilities and smoothing constant. Simulation results show that the proposed HCE-based hybrid precoding can not only effectively achieve the satisfied sum-rate, but also outperform the PSs schemes concerning energy efficiency.

Optically Upconverted, Spatially Coherent Phased-Array-Antenna Feed Networks for Beam-Space MIMO in 5G Cellular Communications

The densification of cellular networks and their soon-to-increase operational frequency is forcing new topological considerations in 5G networks. In particular, networks that enable extreme spatial discrimination are being considered as a means to significantly increase data capacity by realizing spatial-spectral channels that offer frequency reuse without co-channel or adjacent-channel interference. In this paper, we present a new approach to realizing such a capability based on optically upconverted, spatially coherent phased-array feed networks. The details of our approach, presented herein, include the design and initial demonstration of both transmit (Tx) and receive (Rx) array systems that are used in tandem to form a down-/up-link for the purpose of characterizing both array and link performance. Design parameters and initial link characterization results are presented.

Channel estimation for interference mitigation in millimeter-wave multi-cell beamspace MIMO systems

This paper deals with the inter-cell interference (ICI) mitigation in the channel estimation process of millimeter-wave multi-cell beamspace multiple-input multiple-output systems. The known channel estimation approaches cannot distinguish the ICI channels and the in-cell channels. In contrast, the in-cell channels and the ICI channels are estimated together and distinguished with the beam information in this paper. In addition, the beamspace channels are estimated with small error by utilizing the asymptotic property of the beamspace channels. As a result, the ICI can be efficiently suppressed. Performance analysis and numerical results show that the proposed approach outperforms the existing channel estimation approaches.

The Maximal SINR Selection Mode for 5G Millimeter-Wave MIMO: Model Systems and Analysis

&lt;span&gt;In mmWave massive MIMO systems, the lens antenna array and beam selection by beamspace MIMO are employed to target the number of required RF chains reduced without obvious performance loss. For cost – effective, the number of RF chain is an allowable limitation, however, to obtain the near-optimal capacity efficiently, beam selection must require the exact information of the wide size of beamspace channel. Solution to this problem, in this paper we suggest analyzing whole beamspace based on maximal SINR. &lt;/span&gt;&lt;span class="fontstyle01"&gt;&lt;span&gt;More specicfically, it is confirmed that the proposed beam selection algorithms achieve higher power efficiencies than a full system where all beams are employed.&lt;/span&gt;&lt;/span&gt;

Spatial Multiplexing of QPSK Signals With a Single Radio: Antenna Design and Over-the-Air Experiments

The paper describes the implementation and performance analysis of the first fully-operational beam-space MIMO antenna for the spatial multiplexing of two QPSK streams. The antenna is composed of a planar three-port radiator with two varactor diodes terminating the passive ports. Pattern reconfiguration is used to encode the MIMO information onto orthogonal virtual basis patterns in the far-field. A measurement campaign was conducted to compare the performance of the beam-space MIMO system with a conventional 2-by-?2 MIMO system under realistic propagation conditions. Propagation measurements were conducted for both systems and the mutual information and symbol error rates were estimated from Monte-Carlo simulations over the measured channel matrices. The results show the beam-space MIMO system and the conventional MIMO system exhibit similar finite-constellation capacity and error performance in NLOS scenarios when there is sufficient scattering in the channel. In comparison, in LOS channels, the capacity performance is observed to depend on the relative polarization of the receiving antennas.

Five‐element ESPAR antenna using the annular ring slot active element

ABSTRACTThis study proposes a five‐element electric steerable parasitic array radiator (ESPAR) antenna that uses annular ring slot feeding and can be applied to Beamspace MIMO communication. A typical dipole active element that can be applied to the ESPAR antenna usually has a cylindrical structure. Since the coaxial cable is located inside the cylinder, it is restricted by the diameter of the dipole. In the proposed annular ring slot active element, the annular ring slot is formed on the outer conductor, and then the inner conductor is put into the outer conductor to be fed. The typical dipole active element currently takes a cylindrical shape, and therefore has a omnidirectional pattern. Therefore, it generates identical radiation patterns, regardless of the number of parasitic elements. Moreover, in the proposed method, it is easy to undertake impedance matching that controls the length, diameter, and thickness of the slot, outer conductor, and inner conductor. Furthermore, since the dielectric cylinder is located between the outer and inner conductors, it is structurally solid. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2800–2804, 2016

Near-Optimal Beam Selection for Beamspace MmWave Massive MIMO Systems

The recent concept of beamspace MIMO can utilize beam selection to reduce the number of required radio-frequency (RF) chains in mmWave massive MIMO systems without obvious performance loss. However, as the same beam in the beamspace is likely to be selected for different users, conventional beam selection schemes will suffer from serious multiuser interferences, and some RF chains may be wasted since they have no contribution to the sum-rate performance. To solve these problems, in this letter, we propose an interference-aware (IA) beam selection. Specifically, by considering the potential multiuser interferences, the proposed IA beam selection first classifies all users into two user groups, i.e., the interference-users (IUs) and noninterference-users (NIUs). For NIUs, the beams with large power are selected, while for IUs, the appropriate beams are selected by a low-complexity incremental algorithm based on the criterion of sum-rate maximization. Simulation results verify that IA beam selection can achieve the near-optimal sum-rate performance and higher energy efficiency than conventional schemes.