Multi-antenna Systems Research Articles

Multi-Antenna System for In-Line Food Imaging at Microwave Frequencies

This work presents the design and numerical assessment of a novel microwave imaging (MWI) system, capable of providing a full 3-D image of food/beverage products content in order to disclose the possible presence of physical contaminants, such as plastic fragments. The system here presented exploits the dielectric contrast between the food content and possible intrusions at microwave frequencies; it is based on an antenna array architecture inspecting the items in motion along a conveyor belt without interrupting the production process. The inversion problem is solved by means of linearization, assuming the viability of the Born approximation thanks to the localized intrusions, and regularization, based on the singular value decomposition of the discretized scattering operator. Furthermore, an algorithm, to balance the illumination of the considered scenario due to the nonuniform radiation of the employed antennas, is presented to enhance imaging. The system is first assessed considering an ideal case and then extended to a more realistic approach, for two different kinds of food products, with completely different dielectric properties and considering the performance of existing instrumentation for the purpose. The obtained results lay the foundations for the realization of an actual prototype.

Collaborative Beamforming for UAV Networks Exploiting Swarm Intelligence

Unmanned aerial vehicle (UAV)-enabled communication is an essential component of the promising next generation networks owning to its advantages of high maneuverability and low cost. However, the limited onboard energy and weak communication ability of the UAV, as well as the open nature of the wireless networks, may result in the insufficient service time, low coverage and worrying security. Collaborative beam-forming is an effective technique for boosting the communication performance of the multi-antenna systems, which is able to achieve an energy-efficient, long-range and secure transmission. In this work, we focus on the UAV-enabled collaborative beamforming via swarm intelligence approaches. First, we present some preliminaries such as collaborative beamforming, swarm intelligence and multi-objective optimization, and artificial intelligence (AI)-enabled UAV swarm networks. Then, several typical applications of UAV-enabled collaborative beamforming are briefly presented. Subsequently, we propose two UAV communication schemes via collaborative beamforming to enhance communication performance. Specifically, we jointly optimize the schedules of UAVs and the communication order of multiple base stations (BSs) to achieve a secure and energy-efficient transmission. Moreover, we also deploy the UAVs and configure the communication order of the BSs for a time and energy minimization communication via collaborative beamforming. Visualization and numerical results are provided to verify the performance of the proposed schemes. Finally, we also point out some future directions worthy of further investigation.

A Planar Low-Profile Meander Antenna Design for Wireless Terminal Achieving Low RF Interference and High Isolation in Multi-Antenna Systems

In this article, a meander line internal antenna used for wireless terminal is proposed. The current of this antenna is mostly distributed on the antenna radiator itself, rather than on the main board of the wireless device. As a result, the chance of having radio-frequency (RF) interference issues, which usually result in receiver desensitization in wireless radios, can be significantly reduced. The antenna has good radiation performance in the vertical polarization with a low physical profile, compared with the existing antenna designs for typical wireless terminals. The antenna has efficiency similar to the monopole antenna with much less reference/ground plane dependence, achieving lower RF interference, which is demonstrated by the noise coupling measurements in a predefined digital clock - antenna configuration. Furthermore, the mutual coupling (i.e., isolation) between two such antennas is studied and the envelope correlation coefficient between the two antennas is found to be low. A router assembled with the two proposed antennas is tested, and the total isotropic sensitivity is found lower compared with monopole antennas, due to the characteristics of low RF interference and high isolation of the proposed antenna.

Experimental and Theoretical Analysis of Throughput of MIMO PLC Network

In this study, we mainly focused on a theoretical analysis of HomePlug 1.0 and an experimental analysis of modem data rates through a section of a PLC network with several configurations. We introduce the utilization of the MIMO technique to increase the throughput over a PLC channel. Besides, we propose a MIMO PLC channel model to evaluate the channel transfer function of MIMO PLC. We used an equivalent per-unit-length model of the indoor power line network to characterize the three-conductor cable. Based on this mathematical model, we analyzed the throughput of the PLC network with different household appliances. The equivalent circuit of each appliance is also given. The simulation results showed that the throughput is influenced by household appliances connected to the sockets of a MIMO PLC network. Moreover, we also compared the throughput between single and multi-antenna systems. Based on the simulation results, we found that the data rate increased with frequency. In addition, the performance of the MIMO PLC system was almost 90% higher than that of a SISO PLC system in terms of channel capacity.

A coding layer robust reversible watermarking algorithm for digital image in multi-antenna system

Although existing robust reversible watermarking (RRW) schemes are robust to image processing attacks, they do not consider the effect of noise on the encoded digital images when they are transmitted in the wireless channel. In this paper, we propose a coding layer robust reversible watermarking (CL-RRW) algorithm for digital images in multi-antenna system. Through the specially designed preprocessing steps for the encoded carrier image and the embedding method of secret information, the scheme makes full use of the error correction capability of channel coding, and makes the impact of the embedding of secret information on the carrier approximate to natural noise. We analyse the proposed scheme based on multi-antenna systems and Rayleigh fading channels, which can simulate more realistic wireless communication scenarios. The analysis shows that in this scenario, the embedding capacity (EC) can reach the upper bound more quickly as the signal-to-noise ratio (SNR) increases. Within the deduced EC, the difference in peak signal-to-noise ratio (PSNR) between the original and stego images does not exceed 10%. Experimental results show that the proposed algorithm is entirely resistant to image processing attacks, while enabling the receiver to obtain high-quality carrier images and low bit error rate (BER) secret information.

A Unified Framework for Precoding and Pilot Design for FDD Symbol-Level Precoding

Large-scale antenna array techniques are key enablers for modern wireless communication systems. Channel state information (CSI) is indispensable for large-scale multi-antenna systems, but is challenging to obtain. To tackle this issue, in this paper we propose a unified precoding and pilot design frame-work, that allows minimal and precoding-sensitive modified CSI (mCSI) to be collected. This results in a significant reduction in the CSI overheads and complexity compared to classical physical CSI (pCSI) estimation. Based on this unified framework, we further propose an intelligent pilot (IP) approach that senses and selects the mCSI to be collected. The IP approach utilizes a compressive sensing formulation to attach sensing and selection of significant mCSI to precoding optimization. We apply the above techniques to the multi-user frequency division duplexing (FDD) downlink as an example. Our study shows that the advantages of the IP approach are three-fold. First, in contrast to the pCSI, precoding-sensitive information is only captured, which reduces the training and feedback overheads. Second, the precoders are optimized directly based on the mCSI, which avoids recovering the pCSI of high-dimension. Third, since the mCSI of reduced dimension is utilized, the scale of the problem to optimize the precoder is also reduced and thus it is much easier to solve.

Multi-antenna 3D pattern design for millimeter-wave vehicular communications

The transformation of the automotive industry towards ubiquitous connection of vehicles with all kind of external agents (V2X) motivates the use of a wide range of frequencies for several applications. Millimeter-wave (mmWave) connectivity represents a paramount research field in which adequate geometries of antenna arrays must be provided to be integrated in modern vehicles, so 5G-V2X can be fully exploited in the Frequency Range 2 (FR2) band. This paper presents an approach to design mmWave vehicular multi-antenna systems with beamforming capabilities considering the practical limitations of their usage in real vehicular environments. The study considers both the influence of the vehicle itself at radiation pattern level and the impact of the urban traffic on physical layer parameters. Connectivity parameters such as Signal-to-Interference-plus-Noise Ratio (SINR) and outage probability are optimized based on the array topology. A shaped beam in the vertical plane based on three preset radiating elements is proven to be robust enough against self-scattering effects on the vehicle body. Regarding the horizontal geometry, four panels on the roof's edges provide good coverage and link quality. The number of horizontal antennas per panel tightly depends on the required values of the link quality metrics, potentially leading to a non-uniform geometry between sides and front or back panels.

Design of a Transparent System for Mutual Coupling Reduction of Microstrip Array Antennas with Confined Water

Herein, a new method for minimizing mutual coupling of an antenna array with confined water is proposed. In multiantenna systems, mutual coupling reduction is needed to sustain array signal processing efficiency. There are currently a variety of ways to suppress coupling, including defected ground, electromagnetic (EM) bandgaps, and advanced structures. The water absorption characteristic is devised in this innovative approach to minimize mutual coupling without a permanent alteration in the structure. Surface current between two antennas is cancelled using permittivity and water depth in a new configuration. A plexi‐glass confined water is added between the propagating elements to achieve this aim. The rectangular microstrip patch of transparent conducting components serves as the antenna array. Using scattering theories, numerical EM calculations, and anechoic chamber tests, the suggested technique shows a 15 dB decrease in coupling at center frequency (7 GHz). Other propagating functions have also been improved. The suggested framework can be used in multifunction communication networks, aerial vehicle antennas, solar panels, and naval communications because of its optical transparency.

Performance Evaluation of the MU-MIMO Precoding Using the QuaDRiGa Channel Model

The article presents the analysis of characteristics of algorithms of signal precoding in a multi-antenna system with many users (MU-MIMO). This paper presents the numerical evaluation of the multiuser MIMO beamforming algorithms ZF and DFT codebook based on a QUADRIGA channel model, taking into account the real conditions of signal propagation. The generated channels are used to calculate SINR and the spectral efficiency values of each user using the conventional ZF and DFT beamforming codebook. The eigenvalues of the MIMO channel are important in evaluating the MU-MIMO transmission performance characteristics, such as the spectral efficiency of a precoded system. The obtained performance of MU-MIMO ZF and DFT codebook-based beamforming in spatially correlated channels are compared based on the empirical cumulative density function of the sum rate of multiple users. Spatial correlation degrades capacity performance, and in the channels, the DFT precoder has a more robust performance and outperforms the ZF precoder in spectral efficiency. Obtained results can be used by the algorithm evaluation in the system-level simulations.

Throughput modeling of cellular network systems with spatial precoding

The paper discusses wireless cellular radio communication systems along highways using Multiple-input Multiple-output (MIMO, multiple transmit / receive antennas) technologies, in particular spatial multiplexing and diversity reception, and also proposes a model for assessing the potential gains in a multi-antenna system from MIMO, which takes into account the multipath of the channel and the relative orientation of the antennas. The work was carried out by transferring the results of the calculated correlation matrix from stochastic channel model into the physical layer simulator of the cellular system protocol. A methodology for evaluating the performance of multi-antenna systems using spatial multiplexing for roadside cellular networks has been developed. The correlation properties of the channel between the antennas of the two roadside units (RSU), each of which has two perpendicular linearly polarized antennas and a user terminal with the same two orthogonally polarized antennas, have been investigated. A prediction scheme for the type of correlation matrix has been developed, which makes it possible to more accurately set the correlation matrix in simulators of the physical layer. The obtained results showed that for properly designed systems the throughput will be close to the throughput of low spatial correlation, and the case of high correlation proposed by the standard does not need to be modeled. It is also shown that the channels between Tx / Rx pairs that undergo similar polarization changes (the same relative spatial rotation of the antennas) will be strongly correlated, which must be taken into account when developing MIMO systems.

Artificial-Noise-Aided Coordinated Secure Transmission Design in Multi-Cell Multi-Antenna Networks With Limited Feedback

In this paper, we consider secure communications in a multi-cell downlink multi-antenna system, where each multi-antenna base station (BS) sends confidential messages to one intended legitimate user (LU) with a passive multi-antenna eavesdropper trying to intercept the messages in this cell. To enhance the secure communications of the cell-edge users, the multiple BSs employ coordinated beamforming with the aid of artificial-noise (AN) beamforming. We conduct a mathematically rigorous secrecy performance analysis of the considered system and obtain new accurate closed-form expressions of a lower bound on the ergodic rate of each LU and an upper bound of the ergodic rate of each eavesdropper without assuming asymptotes for any system parameter (except for the “worst-case” scenario with zero noise power). Then, a lower bound on the ergodic secrecy rate (ESR) of each LU follows. Based on the derived analytical results, we propose a low-complexity algorithm to optimize the channel sate information (CSI) feedback bits allocation for the channels of target signal link and inter-cell interference links. Furthermore, we develop explicit sufficient conditions on the set of system parameters under which there are at least two BSs to coordinated secure transmission. Through both theoretical analysis and numerical results, we can verify that the obtained analytical lower bound on ESR of each LU as a function of the set of power allocation coefficients is generally <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">neither convex nor concave</i> . Thus, we propose to employ some numerical method to find a sub-optimal power allocation solution. Finally, numerical results are also provided to validate our theoretical results and the proposed feedback bits and power allocation methods.

A Compact Low-Profile Hybrid-Mode Patch Antenna With Intrinsically Combined Self-Decoupling and Filtering Properties

A new type of patch antenna with intrinsically combined self-decoupling and filtering properties is first proposed to address the mutual coupling between elements of the same bands and adjacent bands. By specially engineering the metallic patch of a conventional microstrip antenna into two tightly connected radiators, i.e., a primary patch radiator and a secondary stub-loaded inverted-F radiator, this novel hybrid-mode patch antenna under dual closely located resonances of a TM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">01</sub> patch resonator mode and an inverted-F resonator mode is favorably achieved. More importantly, the stub-loaded inverted-F radiator could not only introduce two radiation nulls allocated at both the lower and upper passband edges, leading to a good filtering response with a sharp band skirt and good selectivity in the boresight gain curve, but also function as an effective isolator that suppresses its near-field coupling, endowing its intrinsic self-decoupling property. Moreover, the developed patch antenna maintains the geometrical advantages of the typical microstrip antenna, including compact size, low profile, and single-layer configuration. In particular, the unique self-decoupling and filtering properties of the developed patch antenna make it a good candidate for multiantenna systems consisting of antenna elements operating at both the same bands and adjacent bands. Prototypes of the self-decoupled filtering patch antenna alone and two types of two-element arrays operating at the same band and adjacent bands, respectively, have been designed, fabricated, and measured. The measured results, in good agreement with their simulated values, validate its low mutual coupling performance for multi-antenna applications.

EC Analysis of Multi-Antenna System over 5G and Beyond Networks and its Application to IRS-Assisted Wireless Systems

EC Analysis of Multi-Antenna System over 5G and Beyond Networks and its Application to IRS-Assisted Wireless Systems

Periodic Updates for Constrained OCO with Application to Large-Scale Multi-Antenna Systems

In many dynamic systems, decisions on system operation are updated over time, and the decision maker requires an online learning approach to optimize its strategy in response to the changing environment. When the loss and constraint functions are convex, this belongs to the general family of online convex optimization (OCO). In existing OCO works, the environment is assumed to vary in a time-slotted fashion, while the decisions are updated at each time slot. However, many wireless communication systems permit only periodic decision updates, <i>i.e.</i> each decision is fixed over multiple time slots, while the environment changes between the decision epochs. The standard OCO model is inadequate for these systems. Therefore, in this work, we consider periodic decision updates for OCO. We aim to minimize the accumulation of time-varying convex loss functions, subject to both short-term and long-term constraints. Feedback information about the loss functions within the current update period may be delayed and incomplete. We propose an efficient algorithm, termed Periodic Queueing and Gradient Aggregation (PQGA), which employs novel periodic queues together with possibly multi-step aggregated gradient descent to update the decisions over time. We derive upper bounds on the dynamic regret, static regret, and constraint violation of PQGA. As an example application, we study the performance of PQGA for network virtualization in a large-scale multi-antenna system shared by multiple wireless service providers. Simulation results show that PQGA converges fast and substantially outperforms the current best alternative.

Beyond 5G Without Obstacles: mmWave-over-Fiber Distributed Antenna Systems

Beyond-5G wireless systems require significant improvement to enable the Internet of Everything, offering ultra-reliability, ultra-low-latency and high data-rates for holographic telepresence, immersive augmented and virtual reality, and cyber-physical systems in Industry 4.0. The mmWave frequency band (30–300 GHz) provides the required bandwidths, but very challenging propagation conditions exist. Conventional co-located multi-antenna systems counter higher path loss, but are insufficient in challenging real-life scenarios with frequent non-line-of-sight conditions. For distributed massive MIMO systems or large intelligent surfaces, we advocate optically-enabled distributed antenna systems (DAS) to alleviate these issues. To ensure tight synchronization and scalability, we propose a mmWave-over-fiber based architecture with low-complexity high-performance remote antenna units (RAUs). Strategically distributing and integrating RAUs in the user equipments' environment yield high throughput and reliable coverage. We demonstrate a mmWave-over-fiber DAS yielding multi-Gb/s mmWave communication in a harsh indoor environment with non-line-of-sight conditions, measuring wireless data rates up to 24 Gb/s, by selecting the RAU yielding the best link quality, and up to 48 Gb/s, by leveraging distributed MIMO techniques.

Prediction Over Estimation: A Novel Energy Efficient Approach to Channel Learning

This letter highlights the importance of channel prediction during channel estimation (CE) in an energy efficient wireless communication system. Specifically, an energy beamforming-assisted multi-antenna system is considered in which energy receiver sends pilot signal to energy transmitter for CE. A long-short term memory based neural network is then utilized for predicting channel characteristics with respect to past CEs. Performance of learning strategy is evaluated, and efficacy of proposed approach is verified by varying number of estimations against predictions and observing maximum energy harvested at receiving antenna. Proposed scheme is also compared and found to outperform two existing benchmarks.

Design and analysis of Maxwell fisheye lens based beamformer

Antenna arrays and multi-antenna systems are essential in beyond 5G wireless networks for providing wireless connectivity, especially in the context of Internet-of-Everything. To facilitate this requirement, beamforming technology is emerging as a key enabling solution for adaptive on-demand wireless coverage. Despite digital beamforming being the primary choice for adaptive wireless coverage, a set of applications rely on pure analogue beamforming approaches, e.g., in point-to-multi point and physical-layer secure communication links. In this work, we present a novel scalable analogue beamforming hardware architecture that is capable of adaptive 2.5-dimensional beam steering and beam shaping to fulfil the coverage requirements. Beamformer hardware comprises of a finite size Maxwell fisheye lens used as a scalable feed network solution for a semi-circular array of monopole antennas. This unique hardware architecture enables a flexibility of using 2 to 8 antenna elements. Beamformer development stages are presented while experimental beam steering and beam shaping results show good agreement with the estimated performance.

A Cross-Correlation-Based Approach to Pattern Distortion and Mutual Coupling for Shared-Aperture Antennas

This paper proposes a pattern distortion coefficient as a new figure of merit to quantitatively evaluate both mutual coupling and pattern distortions in multi-antenna systems. The proposed coefficient is defined as a cross correlation between unaffected and affected far-field patterns of antennas under test, and the input patterns are weighted using a Gaussian function to consider the target operation angle. The feasibility of the proposed approach is validated using a two-antenna system composed of an inverted-F antenna and a microstrip patch antenna, and the amount of mutual coupling is adjusted by changing the distance between the two antennas. The evaluation is further extended to a single-antenna system with a conducting wall that produces strong platform effects with serious pattern distortions. The results demonstrate that the proposed figure of merit provides quantitative insight into the amplitude and phase distortions of far-field patterns that can be caused by both mutual coupling and platform effects.

Multi-Label Learning Based Antenna Selection in Massive MIMO Systems

Antenna selection (AS) is a signal processing technology that can greatly reduce the hardware complexity of multi-antenna systems. Specifically, AS can decrease the number of required radio frequency chains by activating only a subset of the available antennas in each transmission slot. However, optimal AS suffers from a high computational complexity that increases exponentially with the scale of the antenna array. In this paper, we propose a low-complexity AS algorithm based on multi-label learning (MLL), where a deep neural network is employed to determine the set of selected antennas for a given channel matrix. Specifically, the MLL network combines deep canonical correlation analysis and an autoencoder in a unified network structure, which can extract the low dimensional features of channel matrix as well as the interdependency among selected antennas, so as to achieve an accurate prediction of the set of selected antennas with a relatively small-scale learning model. Simulation results show that, in comparison with the convex relaxation based method, our proposed MLL-based method can achieve comparable capacity with significantly reduced computation time.

Distributed mechanism design for multi‐cell communications aided by multiple reconfigurable intelligent surfaces

Reconfigurable intelligent surface (RIS) has drawn great attention as a promising technique that triggers a revolution in multi-antenna systems. It can intelligently reconstruct the propagation environments passively without extra hardware or power consumption. In this paper, the multi-RIS aided downlink multi-cell communication systems are considered. Adjacent base stations (BSs) are allowed to share and jointly control the same RISs to mitigate the influence brought by the inter-cell interference. For the sum-rate maximisation, a distributed negotiation mechanism is designed where each BS only communicates with its neighbours to reach a consensus on the RIS-based analogue beamforming. Meanwhile, given the incomplete knowledge of other cells, each BS independently optimises its digital beamformer based on its iteratively updated estimates over the other cells without revealing any location and channel information of its own serving users. Simulation results show that the proposed scheme achieves a close performance compared to the centralised scheme, and much better than the traditional no-RIS system. The influence of the discrete phase shifts and the RIS size on the system performance are also evaluated.