Large Antenna Arrays Research Articles

MmEye: Super-Resolution Millimeter Wave Imaging

RF imaging is a dream that has been pursued for years yet not achieved in the evolving wireless sensing. The existing solutions on WiFi bands, however, either require specialized hardware with large antenna arrays or suffer from poor resolution due to fundamental limits in bandwidth, the number of antennas, and the carrier frequency of 2.4 GHz/5 GHz WiFi. In this article, we observe a new opportunity in the increasingly popular 60-GHz WiFi, which overcomes such limits. We present mmEye, a super-resolution imaging system toward a millimeter-wave camera by reusing a single commodity 60-GHz WiFi radios. The key challenge arises from the extremely small aperture (antenna size), e.g., < 2 cm, which physically limits the spatial resolution. mmEye’s core contribution is a super-resolution imaging algorithm that breaks the resolution limits by leveraging all available information at both the transmitter and receiver sides. Based on the MUSIC algorithm, we devise a novel technique of joint transmitter smoothing, which jointly uses the transmit and receive arrays to boost the spatial resolution while not sacrificing the aperture of the antenna array. Built upon this core, we design and implement a functional system on commodity 60-GHz WiFi chipsets. We evaluate mmEye on different persons and objects under various settings. Results show that it achieves a median silhouette (shape) difference of 27.2% and a median boundary keypoint precision of 7.6 cm, and it can image a person even through a thin drywall. The visual results show that the imaging quality is close to that of commercial products like Kinect, making for the first-time super-resolution imaging available on the commodity 60-GHz WiFi devices.

Deep Scanning—Beam Selection Based on Deep Reinforcement Learning in Massive MIMO Wireless Communication System

In this paper, we investigate a deep learning based resource allocation scheme for massive multiple-input-multiple-output (MIMO) communication systems, where a base station (BS) with a large scale antenna array communicates with a user equipment (UE) using beamforming. In particular, we propose Deep Scanning, in which a near-optimal beamforming vector can be found based on deep Q-learning. Through simulations, we confirm that the optimal beam vector can be found with a high probability. We also show that the complexity required to find the optimum beam vector can be reduced significantly in comparison with conventional beam search schemes.

Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead

Reconfigurable intelligent surfaces (RISs) are an emerging transmission technology for application to wireless communications. RISs can be realized in different ways, which include (i) large arrays of inexpensive antennas that are usually spaced half of the wavelength apart; and (ii) metamaterial-based planar or conformal large surfaces whose scattering elements have sizes and inter-distances much smaller than the wavelength. Compared with other transmission technologies, e.g., phased arrays, multi-antenna transmitters, and relays, RISs require the largest number of scattering elements, but each of them needs to be backed by the fewest and least costly components. Also, no power amplifiers are usually needed. For these reasons, RISs constitute a promising software-defined architecture that can be realized at reduced cost, size, weight, and power (C-SWaP design), and are regarded as an enabling technology for realizing the emerging concept of smart radio environments (SREs). In this paper, we (i) introduce the emerging research field of RIS-empowered SREs; (ii) overview the most suitable applications of RISs in wireless networks; (iii) present an electromagnetic-based communication-theoretic framework for analyzing and optimizing metamaterial-based RISs; (iv) provide a comprehensive overview of the current state of research; and (v) discuss the most important research issues to tackle. Owing to the interdisciplinary essence of RIS-empowered SREs, finally, we put forth the need of reconciling and reuniting C. E. Shannon's mathematical theory of communication with G. Green's and J. C. Maxwell's mathematical theories of electromagnetism for appropriately modeling, analyzing, optimizing, and deploying future wireless networks empowered by RISs.

Low Complexity Optimization of the Asymptotic Spectral Efficiency in Massive MIMO NOMA

Massive multiple-input multiple-output (MIMO) technology facilitates huge increases in the capacity of wireless channels, while non-orthogonal multiple access (NOMA) addresses the problem of limited resources in traditional orthogonal multiple access (OMA) techniques, promising enhanced spectral efficiency. This work uses asymptotic capacity computation results to reduce the complexity of a power allocation algorithm for small-scale MIMO-NOMA, so that it may be applied for systems with massive MIMO arrays. The proposed method maximizes the sum-capacity of the considered system, subject to power and performance constraints, and demonstrates greater accuracy than alternative approaches despite remaining low-complexity for arbitrarily large antenna arrays.

A Prior Knowledge-Based Algorithm for Robust Design of Array Antennas With Interval Excitation and Position Uncertainties

In this article, the efficiency of the robust design methods for large array antennas with the simultaneous presence of interval amplitude, phase excitation errors, and antenna position errors is addressed. The CPU time for a single iteration of the robust optimization method is greatly reduced by the proposed prior knowledge-based algorithm (PKA). Mathematically, the array factor bounds of array antennas with interval uncertainties can be taken as the bounds of the modulus of the sum of the complex intervals with both the modulus and argument errors (CIMAS). The PKA for the modulus of CIMAS consists of three theorems: 1) the necessary conditions for each complex interval for the upper modulus bound of CIMAS; 2) the method for judging whether the lower modulus bound of CIMAS equals zero; and 3) the necessary conditions for each complex interval for the nonzero lower modulus bound of CIMAS. The efficiency and accuracy of PKA are demonstrated by comparisons with two popular methods. Based on genetic algorithm (GA) and PKA, the robust designs of array antennas under multiple constraints are also presented.

Simulation of Active Reflection Coefficient Phenomena of Large Antenna Array Using FEM Domain Decomposition Methods

This letter proposes the application of the finite element tearing and interconnecting method (FETI-2LM), a domain decomposition method (DDM) for the full-wave simulation of a large antenna array (few thousands of radiating elements). The proposed methodology makes it possible to efficiently calculate in a postprocessing step the antenna patterns for steering directions within the desired field of view while taking into account the active reflection coefficients. The methodology is based on an efficient extraction of the embedded radiating elements far-field radiation patterns as well as the generalized scattering matrix (GSM) of the array by implementing massively parallel computers. The beauty of the GSM is its capability to handle the active S-parameters independently of the steering direction. This permits to generate the angular-dependent active reflection coefficients by postprocessing. This implementation is a step forward to provide us with a tool that permits to evaluate by simulation large antenna array, while taking into account all the phenomena and interactions that may degrade the key performances that are required at a higher level, to specify a global system before fabrication.

Performance analysis of millimeter wave 5G networks for outdoor environment: propagation perspectives

&lt;span&gt;To cope with the massive growth in global mobile data traffic for 2020 and beyond, the Fifth Generation (5G) system is required to be developed as the current 4G system is expected to fall short behind the provision of such growth. 5G systems is anticipated to use millimeter wave (mm-wave) frequency bands (20 to 90) GHz, due to the availability of wide chunk of unexploited bandwidth. This is revolutionary step to use these bands because of their very different propagation conditions, atmospheric absorption and hardware constraints. However, such challenges could be compensated by means of beamforming/beamsteering and larger antenna array. In this paper, a comparative study aided with ray-tracing simulation has been performed to assess the feasibility of mm-wave in 5G system. Propagation characteristics of the 28GHz and 73 GHz bands have been studied and compared in a street canyon outdoor environment to simulate 5G outdoor mobile access. Simulation results were shown along with their comparison for both of the aforementioned frequencies. The results of propagation comparison have been reported in terms of path loss, k-factor, delay spread and received power for both 28 and 73 GHz bands.&lt;/span&gt;

A Fast Parallel Solution Technique for Large Periodic Structures Based on FEM-DDM

In this letter, a fast solution technique based on the finite-element approximation and the domain decomposition method for the analysis of superlarge electromagnetic periodic structures is presented. This technique reduces memory requirements and computational time by decomposing the original periodic structure into several nonoverlapping subdomains according to geometrical repetitions and utilizing the characteristics that most of the subdomains will generate identical system matrices. An adaptive parallel framework considering periodic element features is designed to further accelerate the proposed technique. Through comparisons with existing methods and the commercial software ANSYS HFSS, the benefits and accuracy of the proposed technique are demonstrated. Finally, a microstrip patch antenna array with 10 000 elements and a large waveguide slot antenna array with 4096 slots are simulated showing the power of the presented method.

Design of Ambient Backscatter Training for Wireless Power Transfer

Wireless power transfer (WPT) using energy beamforming is a promising solution for low power Internet of Things (IoT) devices. In this work, we consider WPT from an energy transmitter (ET) employing retrodirective WPT using a large phased antenna array to an energy receiver (ER) capable of ambient backscatter. The advantage of retrodirective WPT is that no explicit channel estimation is needed at the ET and the use of ambient backscattering eliminates the need for active transmission at the ER. We propose a training sequence design, i.e., pattern of varying the reflection coefficient at the ER, to eliminate the direct-link interference from the ambient source. We show that when the ambient symbol duration is known, the ambient interference is fully cancelled by the proposed design. We analytically model the system and find the average harvested power at the ER considering Nakagami-m fading channels and non-linear energy harvesting model. Our results clearly show that the proposed solution is robust to a small timing offset mismatch at the correlator. When interference from undesired neighbouring sources in the ambient environment is not significant, the ER can successfully harvest tens to hundreds of μW of power, which is an important improvement for low-power IoT devices.

Low-Complexity Multicast Beamforming for Millimeter Wave Communications

To develop a low-complexity multicast beamforming method for millimeter wave communications, we first propose a channel gain estimation method in this article. We use the beam sweeping to find the best codeword and its two neighboring codewords to form a composite beam. We then estimate the channel gain based on the composite beam, which is computed off-line by minimizing the variance of beam gain within beam coverage. With the estimated channel gain, we propose a multicast beamforming design method under the max-min fair (MMF) criterion. To reduce the computational complexity, we divide the large antenna array into several small-size sub-arrays, where the size of each sub-array is determined by the estimated channel gain. In particular, we introduce a phase factor for each sub-array to explore additional degree of freedom for the considered problem. Simulation results show that the proposed multicast beamforming design method can substantially reduce the computational complexity with little performance sacrifice compared to the existing methods.

A Dual-Polarized Planar Antenna Array Differentially-Fed by Orthomode Transducer

This article presents a new design of a differentially fed substrate integrated planar antenna array with dual-polarization. Compared with the traditional dual-polarized antenna arrays, the proposed array antenna has the advantages of simple configuration, high cross-polarization discrimination (XPD), and high gain. The 2×2-element subarray design with a via-loaded crossover structure is used, which reduces the complexity of the array antenna. The operation bandwidth is improved by generating three resonances in the subarray. An 8×8 antenna array is designed, prototyped, and tested to exemplify its potential applications in large dual-polarized antenna arrays. A planar orthomode transducer is used to achieve differential excitation for the antenna array. The measured results show that the proposed antenna array has an impedance bandwidth of 19.2-20.7 GHz for |S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">11</sub> | <; -10 dB and port isolation higher than 20 dB. The array antenna exhibits a high XPD of 43 dB and a flat gain of about 22.2 dBi within the bandwidth.

Development and experimental verification of an adaptive structure for phased antenna array using SMA bunch

An adaptive structure for a phased antenna array is proposed using shape memory alloy (SMA) as an actuation component for the plate flatness control. Fiber Bragg Grating (FBG) sensors are designed for plate strain measurement, and a strain displacement transformation method is introduced to obtain the deformation field from the strain measurement data. The deformation field is then used to determine the correction loads of actuation points using integer nonlinear programming analysis. An adaptive prototype for the phased antenna array plate is developed with the distribution of monitored, actuation, and load points. Numerical simulations are performed to demonstrate the detailed process of the strain displacement transformation method. Moreover, the method is further discussed after testing the adaptive plate structure with the digital image correlation (DIC) technology. Finally, the reliability and efficiency of the proposed active control scheme are validated with an experimental setup. The study promotes the engineering application of the active control concept in large scale phased antenna arrays.

An infrared energy harvesting device using planar cross bowtie nanoantenna arrays and diode-less rectification based on electron field emission

ABSTRACT In this paper, we present a rectification process through electron emission from sharp tips under a high electric field of 109–1010 V/m based on the Fowler–Nordheim theory. A large planar array of 104–105 nanoantennas is proposed to achieve the required electric field for electron emission in the nanoantenna gap. Spatial coherence of the incident wave is a prohibitive issue in using large antenna arrays, and it is overcome by choosing proper size for the array. The design starts with a single-element nanoantenna, for which, five different types are considered, namely dipole, spiral, cross bowtie, sinuses and square spiral. Full-wave simulations show that cross bowtie has the highest field enhancement. Moreover, two array configurations, i.e. series and parallel feed networks, are considered and their field enhancement are compared. Moreover, field enhancement in large array configurations is predicted using proposed equations based on curve fitting.

Improved Analog Beamformer Design for Millimeter-Wave Multicast Transmission With Large Antenna Arrays

This study considers the analog beamforming design problem in millimeter-wave single-group and multigroup multicast communication systems, where the base station deploys a large antenna array, and the analog beamformer consists of a network with low-resolution (1–3 bits) phase shifters. This study aims to design an analog beamformer that maximizes the minimum received signal-to-noise ratio (the minimum received signal-to-interference-plus-noise ratio) among users for the single-group (multigroup) multicast communication systems. However, the considered multicast beamforming design problems are NP-hard problems. The problems are tackled by devising a machine learning-inspired algorithm developed from the cross-entropy optimization (CEO) framework to solve the considered problem, where a closed-form expression is derived to facilitate fast evaluation of the learning parameters in the proposed CEO scheme. Simulation results verify the effectiveness of the proposed algorithm for the single-group and multigroup multicast communication systems and reveal that the proposed algorithm significantly outperforms the test algorithms.

Prospective Multiple Antenna Technologies for Beyond 5G

Multiple antenna technologies have attracted much research interest for several decades and have gradually made their way into mainstream communication systems. Two main benefits are adaptive beamforming gains and spatial multiplexing, leading to high data rates per user and per cell, especially when large antenna arrays are adopted. Since multiple antenna technology has become a key component of the fifth-generation (5G) networks, it is time for the research community to look for new multiple antenna technologies to meet the immensely higher data rate, reliability, and traffic demands in the beyond 5G era. Radically new approaches are required to achieve orders-of-magnitude improvements in these metrics. There will be large technical challenges, many of which are yet to be identified. In this paper, we survey three new multiple antenna technologies that can play key roles in beyond 5G networks: cell-free massive MIMO, beamspace massive MIMO, and intelligent reflecting surfaces. For each of these technologies, we present the fundamental motivation, key characteristics, recent technical progresses, and provide our perspectives for future research directions. The paper is not meant to be a survey/tutorial of a mature subject, but rather serve as a catalyst to encourage more research and experiments in these multiple antenna technologies.

Advanced Receiver Architectures for Millimeter-Wave Communications with Low-Resolution ADCs

Employing low-resolution analog-to-digital converters (ADCs) for millimeter-wave receivers with large antenna arrays provides an opportunity to efficiently reduce power consumption of the receiver. Reducing ADC resolution, however, results in performance degradation due to non-negligible quantization error. In addition, the large number of radio frequency chains is still not desirable. Accordingly, conventional low-resolution ADC systems require more efficient designs to minimize the cost and complexity while maximizing performance. In this article, we discuss advanced low-resolution ADC receiver architectures that further improve the spectral and energy efficiency trade-off. To reduce both the numbers of RF chains and ADC bits, hybrid analog and digital beamforming is jointly considered with low-resolution ADCs. We explore the challenges in designing such receivers and present key insights on how the advanced architectures overcome such challenges. As alternative low-resolution ADC receivers, we also introduce receivers with learning-based detection. The receiver does not require explicit channel estimation, and thus is suitable for one-bit ADC systems. Finally, future challenges and research issues are discussed.

True-Time-Delay Beamforming Receiver With RF Re-Sampling

Analog domain true-time-delays (TTD) are desired in hybrid beamforming receivers with large relative bandwidths to mitigate the problem of beam squint. We propose a true-time-delay beamforming receiver architecture which enables squint-free wideband spatial filtering prior to the A/D conversion. The receiver implements true-time-delay with delayed re-sampling of the discrete-time output of a passive mixer. The receiver has the capability to extend the range of the beamforming delays from one to several carrier periods of the RF signal with pulse-skipped local oscillator (LO) signals, thereby enabling TTD beamforming with large antenna arrays. Further, a polyphase structure with parallel mixers is proposed to prevent spectral aliasing resulting from the lowered sample rate of the pulse-skipped LO signals. In addition, the maximum beamforming delay scales with the LO frequency, supporting large arrays also at low frequencies where the antenna separation set by the wavelength is large. We verify the proposed concepts with transistor-level simulation of the receiver implemented with a 28-nm CMOS process. The design achieves a squint-free beamforming for a 400 MHz RF bandwidth, and a maximum beamforming delay of three carrier time periods. The power consumption for a 3 GHz carrier frequency is 4 mW per antenna.

Performance of Uplink Multicell Multiuser Massive SM-MIMO Systems With Imperfect CSI and Pilot Contamination

In this article, the performance of uplink multicell multiuser massive multiple-input multiple-output (MIMO) systems with spatial modulation (SM) is investigated over composite Rayleigh fading channels, where a large number of antennas are deployed at the base station and zero-forcing receiver is utilized to retrieve the transmitted data. Based on imperfect channel state information (CSI) available, the bit error rate (BER) performance of the multicell multiuser massive SM-MIMO system with pilot contamination is analyzed. According to the performance analysis, the error probabilities of the transmitted symbol and transmit antenna index are first derived. Then, with these results, an approximate expression of the overall average BER of the system is attained. Based on this, the asymptotic BER performance at large signal-to-noise ratios (SNRs) is analyzed, and the BER will approach an error floor with the increase of the SNR due to the effects of intercell interference and pilot contamination. Besides, the asymptotic performance of the system for very large antenna arrays is also presented, and the corresponding asymptotical BER expression is deduced. Under this analytical framework, the BER performance of the multicell multiuser massive SM-MIMO systems with perfect CSI can be derived as a special case. Simulation results illustrate that the theoretical analysis is valid, and can match the corresponding simulation well. Thus, the error performance of the system is effectively assessed.

Millimeter Wave Wireless Hadamard Image Transmission for MIMO Enabled 5G and Beyond

The high-speed millimeter wave Wireless Hadamard image transmission technique is studied for the next-generation 5G wireless network and beyond. Cyclic Hadamard transform has been applied to the image, followed by the Hadamard transform sub-sampling for image compression. For regularly sub-sampled Hadamard transform, the Fourier spectrum method can be used to reconstruct the image when it is transmitted to the receiver. For the randomly sub-sampled Hadamard transform, the Compressed Sensing method can be used. The Wireless Hadamard image transmission is compatible with the Multiple Inputs Multiple Outputs technique in mmWave 5G wireless networks. Both software and hardware implementations of the Wireless Hadamard image transmission can be realized through the massive MIMO antenna array. A 94-GHz hardware prototype has been built and tested to demonstrate the performance of the Wireless Hadamard image transmission. It has been shown that image reconstruction has been realized with a hardware sub-sampling ratio of 18 without image loss for digit “1” at a pixel-equiva-lent power SNR of 15 dB, meaning more than an order of magnitude increase in image transmission speed. Furthermore, the upcoming 6G wireless network boasts an even larger antenna array, which allows more image pixels per Hadamard transform frame, making the proposed mmWave Wireless Hadamard image transmission technique work even faster.

Massively Parallel Electromagnetic–Thermal Cosimulation of Large Antenna Arrays

Electromagnetic-thermal cosimulation of large antenna arrays is performed by using a supercomputing-based parallel domain decomposition method. In this letter, frequency-domain electromagnetic and thermal fields are solved self-consistently and then coupled via Joule heat and temperature-dependent material properties. The developed cosimulation solver is first validated with the commercial software COMSOL Multiphysics. Then, the parallel performance of our in-house developed code is examined in terms of scalability and efficiency. Finally, the temperature distributions over large-scale antenna arrays are obtained by our proposed solver in a highly efficient manner.