Virtual Antenna Research Articles

Cooperative Transmission of Energy-Constrained IoT Devices in Wireless-Powered Communication Networks

In Internet of Things (IoT) systems, a number of sensor devices monitor the physical system states and exchange information with each other. The main limitation is that the IoT devices are generally energy constrained since those are powered with batteries. To address this energy problem, we consider a cooperative wireless-powered communication network (WPCN), which consists of three phases: 1) downlink (DL) energy transfer from a multi-antenna access point (AP); 2) data sharing among IoT devices; and 3) uplink (UL) information transfer from single-antenna IoT devices. Based on the shared data and the harvested energy, the single-antenna IoT devices in the neighborhood cooperate to form a virtual antenna array in order to transmit their information simultaneously to the multi-antenna AP using a multiple-input multiple-output (MIMO) technique in the UL information transfer phase. In this study, the transmit covariance matrices (i.e., beamforming vectors and the corresponding transmit power allocation) used for both DL energy transfer and UL information transfer are jointly designed to maximize the UL capacity based on the Lagrangian method. Furthermore, the time allocation for each phase is optimized based on a stochastic gradient method. In the numerical results, it is shown that our proposed beamforming scheme and the stochastic time allocation can achieve near-optimal performance.

FIELD ENHANCEMENT AND SIZE OF RADIO-FREQUENCY HOTSPOTS INDUCED BY MAXIMUM RATIO FIELD COMBINING IN FIFTH GENERATION NETWORK.

The goal of this paper is to experimentally assess the field enhancement and hotspot size of radio frequency electromagnetic fields created by the Maximum Ratio Combining (MRC) precoding scheme using lab measurements at 3.5, 5.5 and 11GHz. MRC is an adaptive precoding scheme used by Massive Multiple Input Multiple Output systems, one of the enabling techniques of the fifth generation of telecommunications (5G). A virtual antenna array was used to compare MRC with two passive precoding schemes: the Random Phase Model (RPM) and the Centerline Beam Model (CBM). The field enhancement going from CBM to MRC was largest in obstructed line of sight (OLOS), ranging from 1.9 to 7.4dB. The field enhancement going from RPM to MRC was about 9.5dB across frequency bands in both line of sight (LOS) and OLOS. The hotspot size, quantified by the full width at half maximum (FWHM), ranged from 0.5 wavelengths to one wavelength.

Using the Concept of a Virtual Antenna Array in a Mimo Radar in the Presence of Reflections from the Ground Surface

We consider the problem of using the concept of a virtual antenna array in a MIMO radar for estimating the angular location of the target in the presence of signals reflected from the ground surface. The formal criteria of realizability of a virtual antenna array are formulated. Various antenna configurations are analyzed theoretically. The restrictions on the location of the receiving and transmitting antennas of a MIMO radar are established. Using numerical simulation, the influence of the reflected signals on the accuracy of determining the angular location of a target is studied for various antenna configurations.

A joint optimization approach for distributed collaborative beamforming in mobile wireless sensor networks

The nodes in mobile wireless sensor networks (MWSNs) are usually with limited hardware resources, which leads to the limitation of transmission range and energy. To extend the communication distance of a single sensor node, distributed collaborative beamforming (DCB) based on a virtual node antenna array (VNAA) can be used in MWSNs. The locations and excitation current weights are the key factors that affect the performance of DCB, thus the nodes of a MWSN can move to better locations to achieve a lower maximum sidelobe level (SLL) of the beam pattern, thereby reducing the communication interferences and enhancing the directivity. However, the moving energy consumption will be increased. In this paper, a joint optimization problem for optimizing the maximum SLL of beam pattern, transmission power and moving energy consumption of DCB nodes in MWSNs is proposed, and the NP-hardness of the formulated problem is proven. Then, we propose a distributed parallel cuckoo search algorithm (DPCSA), which is a nature-inspired approach, to solve the formulated joint optimization problem. Simulation results verify that the maximum SLL, transmission power and moving energy consumption of DCB nodes can be optimized effectively. Moreover, the performance and stability of the proposed DPCSA are evaluated.

Beamforming Optimization in Internet of Things Applications Using Robust Swarm Algorithm in Conjunction with Connectable and Collaborative Sensors.

The integration of the Internet of Things (IoT) with Wireless Sensor Networks (WSNs) typically involves multihop relaying combined with sophisticated signal processing to serve as an information provider for several applications such as smart grids, industrial, and search-and-rescue operations. These applications entail deploying many sensors in environments that are often random which motivated the study of beamforming using random geometric topologies. This paper introduces a new algorithm for the synthesis of several geometries of Collaborative Beamforming (CB) of virtual sensor antenna arrays with maximum mainlobe and minimum sidelobe levels (SLL) as well as null control using Canonical Swarm Optimization (CPSO) algorithm. The optimal beampattern is achieved by optimizing the current excitation weights for uniform and non-uniform interelement spacings based on the network connectivity of the virtual antenna arrays using a node selection scheme. As compared to conventional beamforming, convex optimization, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the proposed CPSO achieves significant reduction in SLL, control of nulls, and increased gain in mainlobe directed towards the desired base station when the node selection technique is implemented with CB.

Improving Performance of Distributed Collaborative Beamforming in Mobile Wireless Sensor Networks: A Multiobjective Optimization Method

Mobile wireless sensor networks (MWSNs) are resource constrained, and have limited energy and transmission range. Distributed collaborative beamforming (DCB) in MWSNs based on a virtual node antenna array (VNAA) can increase the transmission distance and enhance the energy efficiency of a single sensor node. To achieve a lower maximum sidelobe level (SLL), sensor nodes can move to optimal locations with optimal excitation current weights for DCB. However, this leads to an extra motion energy consumption. In this article, we construct a multiobjective optimization framework (MOF) to jointly optimize the maximum SLL, transmission power, and motion energy consumption of the DCB nodes in MWSNs. Moreover, an improved nondominated sorting genetic algorithm-II (INSGA-II) and a distributed parallel INSGA-II (DPINSGA-II) are proposed for solving the formulated MOF. In addition, a simple but practical DCB scheduling mechanism is proposed. The simulation results show that the maximum SLL, transmission power, and motion energy consumption of the VNAA can be effectively optimized by the proposed algorithms.

Negative feedback concept in tagging: Ghost tags imperil the long-term monitoring of fishes.

Wildlife monitoring using passive telemetry has become a robust method for investigating animal migration. With increased use, this method progressively pollutes the environment with technological waste represented by so called ghost tags (PIT tags ending in the environment due to reproductive expulsions, shedding or animal mortality). However, their presence in the environment may lead to failed detections of living individuals. We used tagging data from studies of the asp Leuciscus aspius and the bleak Alburnus alburnus collected from 2014 to 2018 and located ghost tag positions on the monitored spawning site using portable backpack reader for their detection. We modelled virtual river-wide flat-bed antennas (widths 0.2, 0.4, 0.6 and 0.8 m) representing monitoring effort and estimated the probability of the presence of ghost tags within the antenna field. Of 3724 PIT tags used in the study, we detected on the spawning ground 173 ghost tags originating from long-term monitoring. The ghost tags accumulated in the environment in time, suggesting insufficient degradation rate or shift downstream from the research site. Number of ghost tags present on the spawning ground led to high probability of disabled readings of tagged fish passing through the antenna electro-magnetic field. We demonstrate how accumulated ghost tags may cause detection failures for focal species and incomplete data acquisition. We infer that intensive long-term monitoring using PIT tag technology may encumber future data acquisition or entail additional costs for clean-up.

Virtual Antenna Array for Minimization of DOA Estimation Systematic Error Caused by Scattering of Incident Waves on Antenna Carrier Body

The Direction of Arrival (DOA) estimations of systematic errors are caused by diffraction distortions of the measured spatial structure of a electromagnetic field. These distortions result from scattering of incident waves on the antenna system and nearby scatterers (mobile carrier body, antenna mast, underlying surface, etc.) in wide frequency band, including the resonant frequencies of nearby objects. This article proposes a method for minimizing the DOA estimation systematic error by forming an additional virtual receiving channel—a Virtual Antenna Array (VAA). The VAAs were formed by use of classical apparatus of electrodynamics—the Huygens-Kirchhoff principle, the method of equivalent fields and sources, and the quasistatic approximation of the field based on the theory of analytical functions of the complex variable (Cauchy integral, Laurent series). The proposed method does not require calibration of the antenna system or a priori information about the geometry and material properties of the scatterers (dry or wet soil, opened or closed vehicle doors, etc.). Therefore, it gives good results in cases of mobile and stationary arrays, or changing carrier body geometry.

Distributed Null-Steering Beamformer Design for Physical Layer Security Enhancement in Internet-of-Things Networks

With the rapid proliferation of the Internet of Things (IoT), small devices in various applications generate, process, and exchange security and safety-critical data as well as privacy-sensitive information. However, due to limited hardware capabilities of such small devices, the IoT networks are inherently vulnerable to security attacks. In this context, the analog cooperative beamforming (ACB)-based physical layer security (PLS) technique can be a suitable solution to guarantee security in the IoT networks by creating a virtual antenna array with multiple IoT devices. Nevertheless, such techniques suffer from poor secrecy performance, when an eavesdropper is located within the main beam toward the legitimate receiver. Motivated by this limitation, in this article, we propose a fully distributed null-steering beamformer, which is suitable for IoT networks following decentralized architecture. Through analysis and simulation, we show that the proposed PLS algorithm outperforms the existing ACB-based PLS scheme. Furthermore, we show that there exists an optimal degree of nulling that maximizes the secrecy performance, which can be estimated based on the analytical results.

Signal Emitters Localization by Spectral Methods

Methods are considered of generating signals in a radar sensor receiver provided with a colocated antenna system of Multiple Input Multiple Output (MIMO) configuration when synthesizing virtual antenna arrays. Review of the basic spectral methods used in beamforming with digital automobile radars, such as Capon method, MUSIC and ESPRIT was carried out. Spatial spectra obtained by various methods were constructed for a radar signal model, and comparative spectra characteristic by angular resolution is provided. Output heatmaps in the angle-distance coordinate were constructed to represent methods operation according to the real target situation based on data sampling from the front-mounted automobile radar. Advantages of decomposition methods based on MUSIC and ESPRIT algorithms in solving the problem of a signal emitter localization are presented

MOM/GA-Based Virtual Array for Radar Systems.

This paper introduces a novel antenna array synthesis for radar systems based on the concept of a virtual antenna array (VAA) and the method of moments/genetic algorithm (MoM/GA) synthesis method. The VAA concept is applied to both scanning and fixed radiation pattern arrays. The proposed VAA is introduced to simultaneously support the medium-range radar (MRR) and the long-range radar (LRR) with beam width ±7° for LRR and ±37° for MRR. The proposed VAA is distinguished by its minimum number of antenna elements, simple feeding network, high efficiency, and gain, but all of these are at the expense of a large aperture antenna size compared to the planar antenna array (PAA). The VAA has the ability to have the feeding network and the radiating elements on the same layer, as compared to the multilayer PAA. The newly proposed concept is analyzed and verified analytically and experimentally. Two orthogonal (16 elements) VAAs are designed to operate in the frequency range from 23.55 to 24.7 GHz and to support a flat-shoulder shape (FSS) radiation pattern for LRR/MRR. The antenna was fabricated and tested experimentally, and good agreements between the simulated and measured results were noticed. The proposed VAA is introduced to solve the problems of large size, low isolations, low efficiency, feeding network, low resolution, and small coverage range for the antenna arrays of automotive radars. The proposed antenna array is introduced for automotive radar applications at 24 GHz.

Analysis on a 77 GHz MIMO Radar for Touchless Gesture Sensing

This letter presents a novel analysis on a millimeter-wave 77 GHz multiple-input multiple-output (MIMO) radar with virtual antenna array for touchless gesture sensing for human-computer interaction. The virtual array allows fewer receiving channels to achieve higher spatial resolution, which facilitates the integration of radar technology into compact devices. The theoretical analysis and working principles were introduced. Compared to the conventional analysis of MIMO radar, the analytical model proposed in this letter takes the radiation pattern of each antenna into consideration and reveals the nature of virtual antenna array, e.g., the change of the phase factor. Besides, the radiation pattern of each virtual antenna is also obtained, and two equivalent virtual array models decomposed by the analytical model are also discussed. A 77 GHz 2 × 2 MIMO radar system was designed with a maximum scanning bandwidth of 5 GHz and was employed to validate the application of gesture sensing. Based on frequency-modulated continuous-wave with 4 GHz bandwidth and pulse repetition time of 6 ms, a hand's moving gestures were successfully captured with submillimeter accuracy. Presence detection was also experimentally carried out to detect the approach of the subject person.

Wireless AI in Smart Car: How Smart a Car Can Be?

In the era of the Internet of Things (IoT), billions of smart devices connect, interact, and exchange data with each other. As “things” get connected together, intelligent systems and technologies have been developed to exploit the rich information in the collected data, perceive what is happening in the surroundings, and finally take actions to maximize their own utility. Thanks to the ubiquitous wireless signals and the prevalence of wireless devices, wireless sensing becomes more popular among the various approaches that have been adopted in the IoT to measure the surrounding environment. Because human activities interact with wireless signals and introduce distinct patterns to the propagation, analyzing how wireless channel state information (CSI) responds to human activities enables many IoT applications. Recently, radio analytics has been proposed as a promising technique that exploits multipath as virtual antennas, extracts various features from wireless signals, and reveals rich environmental information. As automobiles continue to play an important role nowadays, manufacturers have been seeking emerging techniques for IoT applications that support drivers and enhance safety. The interior of an automobile can be viewed as a special indoor environment where most of the multipaths are restricted inside by the metal exterior. In this article, we introduce the concept of wireless artificial intelligence (AI) and demonstrate its concept in a smart car scenario where information about drivers and passengers is collected by commercial Wi-Fi devices deployed in the car. The proposed wireless AI system is capable of identifying authorized drivers based on radio biometric information. Vital signals of human introduce periodic patterns to the wireless CSI. By extracting the vital sign from wireless signals, the proposed wireless AI system can monitor the driver's state, count number of people in the car, and detect a child left in an unattended car.

Massive MIMO Radar for Target Detection

Since the seminal paper by Marzetta from 2010, the Massive MIMO paradigm in communication systems has changed from being a theoretical scaled-up version of MIMO, with an infinite number of antennas, to a practical technology. Its key concepts have been adopted in the 5G new radio standard and base stations, where 64 fully-digital transceivers have been commercially deployed. Motivated by these recent developments, this paper considers a co-located MIMO radar with M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> transmitting and M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> receiving antennas and explores the potential benefits of having a large number of virtual spatial antenna channels N = M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">T</sub> M <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</sub> . Particularly, we focus on the target detection problem and develop a robust Wald-type test that guarantees certain detection performance, regardless of the unknown statistical characterization of the disturbance. Closed-form expressions for the probabilities of false alarm and detection are derived for the asymptotic regime N → ∞. Numerical results are used to validate the asymptotic analysis in the finite system regime with different disturbance models. Our results imply that there always exists a sufficient number of antennas for which the performance requirements are satisfied, without any a-priori knowledge of the disturbance statistics. This is referred to as the Massive MIMO regime of the radar system.

Optimizing Wireless Sensor Networks Based on Collaborative Beamforming

Abstract With the expansion of the scale of the Internet of Things, the transmission distance and speed of wireless networks need to be improved. Due to the limitation of power and energy of sensor nodes, data transmission is basically carried out by multi-hop relay. Collaborative beamforming is a technology that uses multiple sensor nodes to form a virtual antenna array to transmit high-gain and directional beams, which greatly enhances the transmission range. Compared with the muilt-hop network, collaborative beamforming can reduce the numbers of hop or even transmit data to the target node at one time, thus reducing the time required for routing and forwarding. This means that collaborative beamforming can transmit data more quickly and improve data throughput. In this paper, a brief introduction of cooperative beamforming is given. Then we propose an algorithm based on Collaborative beamforming. Simulation results show that the Collaborative beamforming wireless sensor networks can achieve better throughput compared with multi-hop networks.

Virtual Antenna Array and Multipath AOA-Delay Fingerprints Based Location for Moving Targets

Multipath effects are the major challenge to the accurate indoor wireless positioning technology and the most viable solutions for overcoming such multipath effects are received signal strength (RSS) or channel status information (CSI) based fingerprinting location methods. However, these fingerprinting methods are usually subject to the RSS/CSI fingerprints’ high variability over space. In this paper, a novel virtual antenna array and multipath angle of arrival (AOA)-delay fingerprints based location method has been proposed. The proposed method employs 2-dimensional inverse Fourier transform on the CFRs (Channel Frequency Responses) at equi-spaced positions on a quasi-straight line moving trajectory, i.e., the CFRs of a virtual uniform linear array (VULA), to extract the equivalent multipaths’ AOAs and delays as the radio fingerprints, which vary much more slowly than the RSS/CSI fingerprints in the space domain. By exploiting the geometric properties of the multipaths’ AOAs and delays, a complete fingerprint database containing fingerprints of moving trajectories in different directions with each RP (reference position) as their midpoints can be constructed based on just two fingerprints of two perpendicular line trajectories with the same RP as the midpoints. Further, a two-step online fingerprinting location method is developed, the multipath delay estimates are used to narrow the scope of positioning in the first step, a modified WKNN (Weighed K-Nearest Neighbors) fingerprinting method, with the reciprocals of the fingerprints’ Euclidean distances adopted as the weighting factors, is then employed on RPs in such a narrowed positioning scope to enhance the positioning accuracy. Experimental results verify that the proposed fingerprinting method outperforms the corresponding traditional RSS/CSI fingerprints based approach.

A Novel High-Resolution Imaging Method Using Reduced-Dimension Beamspace Unitary MUSIC for OFDM-MIMO Radar

Imaging of maneuvering targets has become a challenging topic recently. This study proposes an improved MUSIC-based single-snapshot imaging method for OFDM-MIMO radar. At the transmitter part, for orthogonal waveform generation, the interleaved OFDM structure is developed that each transmitter only radiates at an equidistant set of OFDM subcarriers unique to itself. At the receiver part, a novel preprocessing scheme is presented to separate multiple transmit/receive paths and compensate the reference point. Preprocessed echo matrix can fit the model of two-Dimensional (2D) MUSIC algorithm, except for the coupling between radial/cross-range in the virtual antenna array. Correspondingly, we modify the 2D ElementSpace (ES)-MUSIC. In the meantime, a 2D Reduced-Dimension BeamSpace Unitary-MUSIC (RD-BS-UMUSIC) algorithm is proposed for computational complexity reduction and estimation performance enhancement. Numerical results of a simulated target consists of limited number of scatterers and a complex target (a Boeing 737-800 plane) verify that the proposed algorithm can improve the imaging quality and reduce computational complexity effectively compared with the traditional method.

Radar with increased angular resolution of objects in wide-angle scanning

The parameters of radar antenna systems constructed according to the traditional scheme with phase shifters inserted both in the transmitting and receiving antenna array with the radar in which signal processing is performed only on the receiving side are considered and compared in the paper. In the second case, an additional requirement of orthogonality of the radiated signals is imposed on the radiating system of the transmitter. The characteristics of the radar with three transmitters and four receivers are compared. Two variants of forming a virtual antenna array are considered. In the first case, the radiation of the linear regular antenna array is analyzed, in the second case the thinned one, but with the same number of emitters. We demonstrate that in the second case, it is possible to implement the radar with a better angular resolution. The features of using the radar as a short-range radar for vehicle security systems with a wide-angle view are elaborated. The possibility of false capture of the target is noted. The authors of the research suggest the unambiguous direction finding method.

Angular superresolution of signals using virtual antenna arrays

We analysed existing publications concerning virtual antenna arrays and determined the limitations of using them in radar systems for the case of prior uncertainty regarding angular positions of signal sources. The paper shows that it is possible to increase angular coordinate resolution for the case of prior uncertainty regarding angular positions of signal sources by employing a virtual antenna array at typical signal-to-noise ratios used in radar signal processing. We provide results of simulating the signals numerically, which confirm our analytical calculations.

Energy Efficient Collaborative Beamforming for Reducing Sidelobe in Wireless Sensor Networks

Collaborative beamforming (CB) in wireless sensor networks (WSNs) based on a virtual node antenna array (VNAA) can increase the transmission distance and enhance the energy efficiency of sensor nodes. However, a VNAA cannot be pre-designed like the conventional antenna arrays due to the randomly deployed sensor nodes, thereby causing a high sidelobe level (SLL) which increases the interferences. In this article, we formulate a hybrid discrete and continuous optimization problem (HDCOP) for reducing the maximum SLL. HDCOP requires to solve both the discrete and the continuous problems simultaneously, and we propose both centralized and consensus-based distributed CB strategies for solving HDCOP. For the centralized strategy, we convert HDCOP into two sub-optimization problems, and propose a discrete cuckoo search (CS) algorithm for the node location selection optimization and a continuous CS algorithm to optimize the excitation current weights of the selected nodes. For the distributed strategy, we propose a parallel distributed CS algorithm to solve the discrete and continuous parts of HDCOP simultaneously. Moreover, we propose two operating mechanisms based on these two algorithms. Simulation results verify the effectiveness of the proposed strategies for reducing the maximum SLL of CB in WSNs. Moreover, the proposed CB strategies have better performance in terms of the energy efficiency compared with other approaches such as the cross-entropy optimization-based method.