Small Number Of Antennas Research Articles

Joint design of transmit precoding and antenna selection for multi-user multi-target MIMO DFRC

Dual-function radar and communications (DFRC) systems based on multiple-input multiple-output (MIMO) arrays have received considerable attention in recent years due to their excellent ability to alleviate spectrum congestion. The MIMO DFRC systems enable high-resolution detection of multiple targets while communicating with multiple users simultaneously. However, MIMO arrays require numerous radio frequency (RF) units and suffer a strong mutual coupling among antennas, resulting in significant system overhead and performance degradation, respectively. In light of this, this paper investigates the joint optimization of transmit precoding and antenna selection for MIMO DFRC systems, aiming to improve the angular ambiguity function with a guaranteed communication quality of service (QoS) using a small number of antennas. To address the resultant non-convex optimization problem, both the indirect and direct precoding methods are proposed. In the former, the waveform covariance and antenna selection vector are first jointly optimized via a promoted sparsity along the covariance diagonal, followed by the precoding matrix indirectly derived from the optimal covariance. In the latter, the precoding matrix is directly optimized via an imposed group sparsity under the communication QoS and power constraints. Simulation results demonstrate that the proposed sparse MIMO DFRC system with fewer active antennas can achieve comparable dual-functional performance to that of the full array system.

Performance Analysis of Artificial Noise-Assisted Location-Based Beamforming in Rician Wiretap Channels.

This paper studies the performance of location-based beamforming with the presence of artificial noise (AN). Secure transmission can be achieved using the location information of the user. However, the shape of the beam depends on the number of antennas used. When the scale of the antenna array is not sufficiently large, it becomes difficult to differentiate the performance between the legitimate user and eavesdroppers nearby. In this paper, we leverage AN to minimize the area near the user with eavesdropping risk. The impact of AN is considered for both the legitimate user and the eavesdropper. Closed-form expressions are derived for the expectations of the signal to interference plus noise ratios (SINRs) and the bit error rates. Then, a secure beamforming scheme is proposed to ensure a minimum SINR requirement for the legitimate user and minimize the SINR of the eavesdropper. Numerical results show that, even with a small number of antennas, the proposed beamforming scheme can effectively degrade the performance of eavesdroppers near the legitimate user.

Concurrent Spoofing-Jamming Attack in Massive MIMO Systems With a Full-Duplex Multi-Antenna Eavesdropper

In this paper, we evaluate the ultimate severity of a concurrent spoofing-jamming un-detected attack from a full-duplex (FD) multi-antenna eavesdropper (EV) on a legitimate user equipment (UE) in a massive multiple-input multiple-output (MIMO) system. The FD EV can concurrently exploit its antennas to spoof one UE pilot and to estimate its link to the same UE in the uplink, and then to eavesdrop the UE's data and perform directional jamming in the downlink. From the perspective of the EV, we derive an expression for the ergodic rate difference, which is general for any possible overlap between spoofing and jamming antenna subsets. Residual spoofing and jamming self-interferences and their statistical dependencies are accounted for in the derived expression. The EV optimizes the trade-off between both spoofing-jamming powers, and antenna subsets to minimize the ergodic rate difference. Numerical results show that the EV is capable of destroying the security of the legitimate communication with a small number of antennas and a power budget equal to that of the attacked UE. The severity of the attack depends on the EV's knowledge of the power allocation strategies used at the base station (BS).

Capacity Analysis and Data Detection of OvTDM-MIMO System

It is well known that the channel capacity of traditional MIMO systems is positively correlated with the number of antennas, so MIMO systems usually use more antennas to meet higher system capacity requirements, which is increasingly conflicting with the miniaturization requirements of portable devices. To overcome the above problems, a new OvTDM-MIMO system is proposed, which can effectively improve the capacity of the system. This system introduces the overlapped time division multiplexing (OvTDM) technology into the MIMO system, which can further improve the channel capacity of the MIMO system by using a smaller number of antennas. This paper introduces the transceiver model of the OvTDM-MIMO system in detail and derives the channel capacity of the system based on mutual information theory. Compared with a conventional MIMO system, the OvTDM-MIMO system has the ability to improve channel capacity. Then, this paper proposes an OvTDM-MIMO symbol detection scheme based on an improved low-complexity Orthogonal Approximate Message Passing (OAMP) algorithm to solve the symbol detection problem caused by symbol correlation. The main design idea of this scheme is to use symbol correlation as the detection constraint and realizes joint symbol detection by combining adjacent symbols, avoiding the problem of excessive matrix size caused by Kronecker product operation. The simulation results show that the proposed detection algorithm can achieve similar performance to traditional MIMO system detection algorithms with low computational complexity.

Beam Selection for Two-Step Random Access in MTC With a Small Number of Antennas

Beam Selection for Two-Step Random Access in MTC With a Small Number of Antennas

Uplink Spectral Efficiency of Large, Distributed Antenna Systems With MMSE Processing

The spectral efficiency of a representative uplink in a wireless network with spatially distributed antennas and linear minimum-mean-square-error processing is found to approach an asymptote with a simple form as the number of antennas increases. These results generalize prior work which was applicable to systems with small numbers of base stations with large numbers of antennas each, to systems with large numbers of spatially distributed access points with small numbers of antennas each, and systems between these extremes. Additionally, these results are applied to systems where mobiles have multiple transmit antennas, and are used to characterize systems with both disjoint and user-centric clustering of cooperating base stations. Among other conclusions, these results indicate that with the same density and number of antennas cooperating to serve a mobile user, the uplink spectral efficiency with all antennas randomly distributed is several-fold higher than the case when the antennas are concentrated at one base station. These findings help improve our understanding of the tradeoffs involved in distributed antenna systems which have the potential to significantly increase data rates, but at a higher cost.

Device-Free Indoor Location Estimation System Using Commodity Wireless LANs

In recent years, propagation channel characteristics have been effectively used in several applications such as motion sensing and position detection. Considerable attention has been paid to channel-sounding methods that are easy to utilize using low-cost devices. This paper presents a device-free indoor location estimation method using the spatio-temporal features of radio propagation channels using a 2.4 GHz-band three-by-three multiple-input-multiple-output (MIMO) channel sounder developed using commodity wireless local area network (WLAN). The measurement results demonstrated a reasonable performance of the proposed method with a small number of antennas.

Rate-Energy Tradeoffs of Wireless Powered Backscatter Communication With Power Splitting and Time Switching

We consider a monostatic wireless powered backscatter communication (WPBC) system, where a device performs backscatter modulation and energy harvesting (EH) using the received signal from a multi-antenna hybrid access point. The rate-energy regions of the WPBC are studied for power splitting (PS) and time switching (TS) receivers in a comprehensive way by using the rate and EH functions reflecting the effects of practical systems. For both linear and nonlinear EH models, we analyze the rate-energy regions of the static PS and TS strategies and optimize the dynamic strategies exploiting the channel state information (CSI) to extend the regions. The regions with the static strategies are obtained in closed-form expressions and the dynamic strategies are obtained in explicit forms as a function of a dual variable, by approximating the nonlinear EH model to a piecewise linear EH (PLEH) model. The results show that the dynamic PS and TS strategies outperform their static counterparts and their gains are more prominent in the sensitivity region of a nonlinear EH circuit and with a smaller number of antennas. It is also observed that the dynamic PS strategy provides the best performance but can be replaced by the static one for a large number of antennas to avoid the CSI. The strategies obtained explicitly by using the PLEH model are also shown to work well with a practical EH model without a noticeable loss in the performance.

Solar image deconvolution by generative adversarial network

With aperture synthesis (AS) technique, a number of small antennas can be assembled to form a large telescope whose spatial resolution is determined by the distance of two farthest antennas instead of the diameter of a single-dish antenna. In contrast from a direct imaging system, an AS telescope captures the Fourier coefficients of a spatial object, and then implement inverse Fourier transform to reconstruct the spatial image. Due to the limited number of antennas, the Fourier coefficients are extremely sparse in practice, resulting in a very blurry image. To remove/reduce blur, “CLEAN” deconvolution has been widely used in the literature. However, it was initially designed for a point source. For an extended source, like the Sun, its efficiency is unsatisfactory. In this study, a deep neural network, referring to Generative Adversarial Network (GAN), is proposed for solar image deconvolution. The experimental results demonstrate that the proposed model is markedly better than traditional CLEAN on solar images. The main purpose of this work is visual inspection instead of quantitative scientific computation. We believe that this will also help scientists to better understand solar phenomena with high quality images.

High-Resolution Angle-of-Arrival and Channel Estimation for mmWave Massive MIMO Systems With Lens Antenna Array

Lens antenna array (LAA), as a promising architecture in millimeter-wave (mmWave) massive MIMO systems, which can considerably reduce the number of required radio-frequency (RF) chains. In this article, we propose a high-resolution channel or angle-of-arrival (AoA) estimation scheme while taking into account the power leakage problem. Specifically, the criterion function is constructed based on DFT beam difference (DBD) to infer the real position of arrived signal. Subsequently, the novel antenna selection and path number estimation algorithms are proposed without prior knowledge of channel. A few groups of antennas are selected to connect to the RF chains, where each group contains only a small number of antennas. Thus, the beamspace multiple signal classification (MUSIC) algorithm can be implemented in low dimensional space to estimate the AoA(s) for each group. Then the channel estimation can be obtained by least square method after the reconstructions of steering vectors using the AoA estimations. Furthermore, the corresponding spatial smoothing algorithm is leveraged to tackle rank deficient problem at the scenario of constant path gains. Simulation results verify the effectiveness of the proposed scheme.

MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges

Important requirements for automotive radar are high resolution, low hardware cost, and small size. Multiple-input, multiple-output (MIMO) radar technology has been receiving considerable attention from automotive radar manufacturers because it can achieve a high angular resolution with relatively small numbers of antennas. For that ability, it has been exploited in the current-generation automotive radar for advanced driverassistance systems (ADAS) as well as in next-generation highresolution imaging radar for autonomous driving. This article reviews MIMO radar basics, highlighting the features that make this technology a good fit for automotive radar and reviewing important theoretical results for increasing the angular resolution. The article also describes challenges arising during the application of existing MIMO radar theory to automotive radar that provide interesting problems for signal processing researchers.

Developing the First mmWave Fully-Connected Hybrid Beamformer With a Large Antenna Array

Millimeter wave (mmWave) systems with effective beamforming capability play a key role in fulfilling the high data-rate demands of current and future wireless technologies. Hybrid analog-to-digital beamformers have been identified as a cost-effective and energy-efficient solution towards deploying such systems. Most of the existing hybrid beamforming architectures rely on a subconnected phase shifter network with a large number of antennas. Such approaches, however, cannot fully exploit the advantages of large arrays. On the other hand, the current fully-connected beamformers accommodate only a small number of antennas, which substantially limits their beamforming capabilities. In this article, we present a mmWave hybrid beamformer testbed with a fully-connected network of phase shifters and adjustable attenuators and a large number of antenna elements. To our knowledge, this is the first platform that connects two RF inputs from the baseband to a $16\times 8$ antenna array, and it operates at 26 GHz with a 2 GHz bandwidth. It provides a wide scanning range of 60°, and the flexibility to control both the phase and the amplitude of the signals between each of the RF chains and antennas. This beamforming platform can be used in both short and long-range communications with linear equivalent isotropically radiated power (EIRP) variation between 10 dBm and 60 dBm. In this article, we present the design, calibration procedures and evaluations of such a complex system as well as discussions on the critical factors to consider for their practical implementation.

Калибровка антенных решёток с малым числом элементов: проблемы и их решения

Калибровка антенных решёток с малым числом элементов: проблемы и их решения

Variable-channel Threshold-based Hybrid AF-DF Cooperative Communications with Packet Splitting

Cooperative communications has been widely researched as an attractive way to improve wireless communications systems with a small number of antennas and low power consumption. However, forward processing in the relay terminals means consuming the power of relays in other terminals. Therefore, the waste of electricity from forwarding is to be reduced as much as possible. In this paper, we propose and analyze a new relay system for three-node, hybrid, cooperative communications systems, where the relay terminal may choose to transmit messages using amplifyand-forward (AF) with expansion of the channel matrix or using decode-and-forward (DF) with packet-splitting transmission. This is based on the qualities of the channels in the source–relay and source–destination links. Then, in the proposed system, the decision on the forwarding scheme is made in order to calculate a threshold based on the equation of the channel capacity. From the simulation results, the proposed system can improve the bit error rate and reduce the load from forward processing latency at the relay.

Phase Shifters Versus Switches: An Energy Efficiency Perspective on Hybrid Beamforming

Hybrid beamforming architectures provide promising solutions to harness the benefits of massive multi-input multi-output systems by incorporating phase shifters, switches, or their combinations. This letter addresses the design of such architectures from an energy efficiency (EE) perspective. We provide closed-form expressions to compare several promising hybrid beamforming architectures, and also derive optimal numbers of antennas required for maximizing the EE. Our results indicate that the asymptotic closed-forms provide a good approximation even for a relatively small number of antennas. Moreover, the combination of phase shifters and switches offers significantly higher EE versus conventional phase shifter-only architectures, while nearly preserving spectral efficiency.

MIMO radar pseudo-orthogonal waveform generation by a passive 1 ×Mmode-mixing microwave cavity

Multiple Input Multiple Output (MIMO) Radar has many advantages compared with conventional Radars including improved target parameters estimation, improved angular resolution while keeping a small number of antennas. Nevertheless, these advantages can be obtained when probing simultaneously the scattering matrix with orthogonal transmit signals. Recently, a passive orthogonal waveform generation technique was introduced using a 1 × M ports Mode-Mixing microwave cavity whose transfer functions are uncorrelated. This approach makes MIMO Radar system able to satisfy transmit beamforming constraint with a cost-efficient architecture. In this paper, more conceptual clarifications are brought and the orthogonality metrics are assessed. Furthermore, the proposed method is experimentally compared with a conventional MIMO Radar based on frequency hopping waveforms.

Low complexity performance assessment of a sensor array via unscented transformation

Due to the advances on electronics, applications of antenna array signal processing are becoming more frequent. When employing antenna arrays for beamforming, the signal to interference and noise ratio (SINR) should be assessed. Many factors can affect the SINR such as the array element positioning error and the direction of arrival (DOA) estimation error. In these cases, the assessment is traditionally performed via the SINR average obtained using Monte Carlo (MC) simulations. However, this approach requires a great amount of realizations that demand a high computational effort and processing time due to its slow convergence. In this paper, we propose a low complexity performance assessment of the average SINR via unscented transformation. Compared to MC simulations, our proposed method requires only a few trials and has a negligible computational complexity, yet giving a comparable SINR when the DOA estimation is perturbed. When the antenna elements positioning is perturbed, a multivariate scenario arises. For multivariate scenario the proposed scheme has an exponential increase in complexity, therefore, still being advantageous for a small number of antennas.

Nonregenerative Cellular Two-Way Relaying With Large-Scale Antenna Arrays

In this paper, we consider a cellular two-way relay channel (cTWRC) where multiple mobile stations (MSs) exchange information with a base station (BS) via a relay station (RS). Both the BS and the RS are equipped with a very large-scale antenna array, whereas each MS is equipped with a small number of antennas. We investigate two zero-forcing (ZF)-based nonregenerative relaying schemes for cTWRCs, namely, signal-alignment-based ZF (SA-ZF) and antenna-selection-based ZF (AS-ZF). We focus on analyzing the impact of large antenna arrays on the performance of these low-complexity nonregenerative relaying protocols, and we derive closed-form asymptotic expressions for the signal-to-interference-plus-noise ratio (SINR) and the achievable sum rate when the numbers of antennas at the BS and the RS go large simultaneously. We show that with large-scale antenna arrays, ZF-based relaying can achieve the sum-rate capacity of the cTWRC, either when the RS is located much closer to the BS than to the MSs or when the number of antennas at the BS far exceeds that at the RS. We further show that, with large-scale antenna arrays, the transmit power of the BS and each MS can be made inversely proportional to the number of relay antennas while maintaining a given achievable rate for each end node. Numerical results are provided to verify our analysis.

Design and Performance Analysis of Noncoherent Detection Systems With Massive Receiver Arrays

Harvesting the gain of a large number of antennas in a mmWave band has mainly been relying on the costly operation of channel state information (CSI) acquisition and cumbersome phase shifters. Recent works have started to investigate the possibility to use receivers based on energy detection (ED), where a single data stream is decoded based on the channel and noise energy. The asymptotic features of the massive receiver array lead to a system where the impact of the noise becomes predictable due to a noise hardening effect. This in effect extends the communication range compared to the receiver with a small number of antennas, as the latter is limited by the unpredictability of the additive noise. When the channel has a large number of spatial degrees of freedom, the system becomes robust to imperfect channel knowledge due to channel hardening. We propose two detection methods based on the instantaneous and average channel energy, respectively. Meanwhile, we design the detection thresholds based on the asymptotic properties of the received energy. Differently from existing works, we analyze the scaling law behavior of the symbol-error-rate (SER). When the instantaneous channel energy is known, the performance of ED approaches that of the coherent detection in high SNR scenarios. When the receiver relies on the average channel energy, our performance analysis is based on the exact SER, rather than an approximation. It is shown that the logarithm of SER decreases linearly as a function of the number of antennas. Additionally, a saturation appears at high SNR for PAM constellations of order larger than two, due to the uncertainty on the channel energy. Simulation results show that ED, with a much lower complexity, achieves promising performance both in Rayleigh fading channels and in sparse channels.

An Expanded Trilinear Model-Based Angle Estimation Algorithm for MIMO Radar with Small Number of Transmit/Receive Antennas

In this paper, we address the problem of angle estimation in a bistatic multiple-input multiple-output (MIMO) radar which exploits nonuniform linear array at both the transmitter and the receiver with small number of antennas. It is demonstrated that the conventional trilinear decomposition-based angle estimation algorithm can identify only a comparatively small number of targets under this condition. In order to increase the number of identifiable targets, we derive an expanded trilinear decomposition-based angle estimation algorithm for MIMO radar, which can expand the size of the trilinear model. The proposed algorithm not only has the advantages of not requiring spectral peak searching, nor additional pair matching and being suitable for nonuniform arrays, but also identifies more targets than the conventional trilinear decomposition-based angle estimation algorithm under the same conditions. Moreover, the angle estimation performance of the proposed algorithm is better than that of the conventional trilinear decomposition-based angle estimation algorithm and the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. Simulation results illustrate the effectiveness and improvement of the proposed algorithm.