Wireless Links Research Articles

Resource-Aware Time Series Imaging Classification for Wireless Link Layer Anomalies.

The number of end devices that use the last-mile wireless connectivity is dramatically increasing with the rise of smart infrastructures and requires reliable functioning to support smooth and efficient business processes. To efficiently manage such massive wireless networks, more advanced and accurate network monitoring and malfunction detection solutions are required. In this article, we perform a first-time analysis of image-based representation techniques for wireless anomaly detection using recurrence plots (RPs) and Gramian angular fields and propose a new deep learning architecture enabling accurate anomaly detection. We elaborate on the design considerations for developing a resource-aware architecture and propose a new model using time series to image transformation using RPs. We show that the proposed model: 1) outperforms the one based on Gramian angular fields by up to 14% points; 2) outperforms classical ML models using dynamic time warping by up to 24% points; 3) outperforms or performs on par with mainstream architectures, such as AlexNet and VGG11 while having <10x their weights and up to ≈ 8% of their computational complexity; and d) outperforms the state of the art in the respective application area by up to 55% points. Finally, we also explain on randomly chosen examples how the classifier takes decisions.

R&amp;D of a low-complexity acoustic communication payload for small-size AUV

Due to its features of low-cost, deployment-convenience and low detection probability, small size AUV is drawing more and more attention from diverse marine fields. While the technique of acoustic communication is capable of enabling wireless link of small size AUV, difficulties caused by adverse underwater acoustic mobile channel such as multipath, Doppler and noise pose significant challenges. Moreover, extremely strict constaints in terms of size, power supply and real-time caculation capability means that R&amp;D of acoustic communication payload need to seek a tradeoff between the algorithm performance and system overhead. To deal with the abovementioned hurdles, a lightweight acoustic communication payload for small-size AUV is designed. Specifically, the proposed payload adopts symbol-wise low-complexity Doppler estimation and compenstaion process, which is incorporated with a compact channel equalizer to achieve reliable mobile communication under Doppler and multipath conditions. The hardware and software design associated with the efficient system implementation of the proposed scheme is given. Finally, lake trial results performed based on small size AUV equiped with the proposed acoustic communication payload is presented to verify its effectiveness.

An Efficient Multi-Beam Generation Method for Millimeter-Wave Reconfigurable Intelligent Surface: Simulation and Measurement

Reconfigurable intelligent surface (RIS) is a promising technology for controlling wireless signals. In particular, it has the potential to provide remarkable performance improvements for wireless links, which is especially appealing for millimeter-wave (mmWave) communications. With this purpose, a proper design of the RIS's reflection beam patterns is highly required. In this paper, a direct method is firstly introduced for multi-beam generations based on RIS. Then, equipped with the artificial bee colony (ABC) algorithm, an efficient multi-beam generation method is proposed to configure RIS for high-performance multi-beam patterns on top of the direct method as the initial design. Finally, by employing a fabricated mmWave RIS, we conduct numerical simulations and experimental measurements, and the measured results validate that the proposed method can obtain higher-quality RIS-based multi-beam patterns with an average 7.96 dB side-lobe level reduction, which may provide an efficient way to enhance the capacity of mmWave communications.

A Protocol for Reliable Real-Time Wireless Communication of Large Data Samples

In this paper, we present a middleware protocol, that transmits larger-than-a-frame data samples within application real-time and reliability requirements over a lossy wireless channel. The protocol efficiently deploys an intelligent retransmission control that exploits the extended deadline requirements of a sample for frame-level scheduling. The transmission of such samples is placed in the context of the necessary integration of such external sensor data into the decision-making process of an autonomous vehicle. Therefore, we provide parameterization and access rules for communication links in resource-managed scenarios and lay out how to integrate the protocol into the popular DDS middleware. The performance of the parameterized links to satisfy their reliability requirements is studied and compared to error protection protocols in the current software stack. We base the evaluation on an OMNeT++ simulation, whereby an established wireless error model is used. The use case is placed in the context of collaborative sensing in a valet parking environment, where external infrastructure sensor data augments the autonomous vehicle's data processing chain via a lossy wireless link. Thereby, the use case adheres to the underlying safety requirements. Results show that if the protocol's awareness of the application requirements is used for parameterization, guarantees for reliability can be provided that outperform existing solutions.

무선통신링크용 다중빔수신 능동위상배열 안테나 시스템 개발

무선통신링크용 다중빔수신 능동위상배열 안테나 시스템 개발

A Concept for Setting Up Jam-Resistant Radio Links for Sonar Systems in Prospective Aircraft Patrol Complexes of the Russian Navy

A Concept for Setting Up Jam-Resistant Radio Links for Sonar Systems in Prospective Aircraft Patrol Complexes of the Russian Navy

Feasibility study of eigenmode propagation through 2D models of vegetation

PurposeThis study aims to model and investigate low-loss wave-propagation modes across random media. The objective is to achieve better channel properties for applying radio links through random vegetation (e.g. forest) using a beamforming approach. Thus, obtaining the link between the statistical parameters of the media and the channel properties.Design/methodology/approachA beamforming approach is used to obtain low-loss propagation across random media constructed of long cylinders, i.e. a simplified two dimensional (2D) model of agroforests. The statistical properties of the eigenmode radio wave propagation are studied following a Monte Carlo method. An error quantity is defined to represent the robustness of an eigenmode, and it is shown that it follows a known Lognormal statistical distribution, thereby providing a base for further statistical investigations.FindingsIn this study, it is shown that radio wave propagation eigenmodes exist based on a mathematical model. The algorithm presented can find such modes of propagation that are less affected by the statistical variation of the media than the regular beams used in radio wave communication techniques. It is illustrated that a sufficiently chosen eigenmode waveform is not significantly perturbed by the natural variation of the tree trunk diameters.Originality/valueAs a new approach to obtain low-loss propagation in random media at microwave frequencies, the presented mathematical model can calculate scattering-free wave-propagation eigenmodes. A robustness quantity is defined for a specific eigenmode, considering a 2D simplified statistical forest example. This new robustness quantity is useful for performing computationally low-cost optimization problems to find eigenmodes for more complex vegetation models.

The Impact of Denial-of-Service Attacks and Queue Management Algorithms on Cellular Networks

In today's digital landscape, Distributed Denial of Service (DDoS) attacks stand out as a formidable threat to organisations all over the world. As known technology gradually advances and the proliferation of mobile devices, cellular network operators face pressure to fortify their infrastructure against these risks. DDoS incursions into Cellular Long-Term Evolution (LTE) networks can wreak havoc, elevate packet loss, and suboptimal network performance. Managing the surges in traffic that afflict LTE networks is of paramount importance. Queue management algorithms emerge as a viable solution to wrest control over congestion at the Radio Link Control (RLC) layer within LTE networks. These algorithms work proactively, anticipating, and mitigating congestion by curtailing data transfer rates and fortifying defences against potential DDoS onslaughts. In the paper, we delve into a range of queue management methods Drop-Tail, Random Early Detection (RED), Controlled Delay (CoDel), Proportional Integral Controller Enhanced (PIE), and Packet Limited First In, First Out queue (pFIFO). Our rigorous evaluation of these queue management algorithms hinges on a multifaceted assessment that encompasses vital performance parameters. We gauge the LTE network's resilience against DDoS incursions, measuring performance based on end-to-end delay, throughput, packet delivery rate (PDF), and fairness index values. The crucible for this evaluation is none other than the NS3 simulator, a trusted platform for testing and analysis. The outcomes of our simulations provide illuminating insights. CoDel, RED, PIE, pFIFO, and Drop-Tail algorithms emerge as top performers in succession. These findings underscore the critical role of advanced queue management algorithms in fortifying LTE networks against DDoS attacks, offering robust defences and resilient network performance.

Resource Allocation of Multiple Base Stations for Throughput Enhancement in UAV Relay Networks

An unmanned aerial vehicle (UAV), with the advantages of mobility and easy deployment, serves as a relay node in wireless networks, which are known as UAV relay networks (URNs), to support user equipment that is out of service range (Uo) or does not have a direct communication link from/to the base station (BS) due to severe blockage. Furthermore, URNs have become crucial for delivering temporary communication services in emergency states or in disaster areas where the infrastructure is destroyed. The literature has explored single transmissions from one BS to a UAV to establish a wireless backhaul link in the URN; however, there exists a possibility of Uo outages due to severe interference from an adjacent BS, causing an overall throughput degradation of user equipment (UE) in the URN. In this paper, to improve the signal-to-interference-plus-noise ratio (SINR) of a wireless backhaul link, avoid an outage of Uo, and guarantee a reliable relay transmission, simultaneous transmissions from multiple BSs (e.g., macrocell BSs (mBSs) and small cell BSs (sBSs)) is considered. An outage probability is analyzed, and an optimal transmit time allocation algorithm is proposed to maximize the throughput of the UE and guarantee a reliable relay transmission. Simulation results demonstrate that simultaneous transmissions from multiple BSs in the URN leads to higher throughput and reliable transmission without an Uo outage compared to a single transmission in the URN from a single BS (e.g., mBS or sBS), and the optimization of transmit time allocation is essential in the URN.

Framework for fast and low-complexity deployment of UAVs-assisted communication

Unmanned Aerial Vehicles (UAVs) can work as aerial base stations along with the ground base stations to enhance capacity and provide ubiquitous coverage in 5G and beyond communication systems. UAVs have numerous features that distinguish them from the traditional fixed ground network infrastructure. These features include more flexibility, lower costs, faster integration, and better channel conditions with users owing to the UAVs maneuverability and adaptability to varying network conditions. This paper addresses UAVs positioning and radio resource management, which are two critical design issues that greatly impact the system performance and user experience in UAVs-assisted communication scenarios. Our objective is maximizing the achieved sum rate of a system consisting of a ground base station and a number of UAVs operating as aerial base stations under constraints on the minimum rate requirements of users, the capacity of wireless backhaul links between the UAVs and the ground base station, and the power budgets of the base stations. In doing so, we optimize the UAVs locations, the users-to-base stations association, the access link channels assignment, and the power allocation. The problem is a mixed-integer non-convex optimization, which is NP-hard to solve, and consequently we propose a fast low-complexity algorithm that achieves high performance compared to the common block coordinate descent-based solution approach and at much less execution time.

A Quad-Port Nature-Inspired Lotus-Shaped Wideband Terahertz Antenna for Wireless Applications

This article is aimed at designing an inventive compact-size quad-port antenna that can be operated within terahertz (THz) frequency spectra for a 6G high-speed wireless communication link. The single-element antenna comprises a lotus-petal-like radiating patch and a defected ground structure (DGS) on a 20 × 20 × 2 µm3 polyamide substrate and is designed to operate within the 8.96–13.5 THz frequency range. The THz antenna is deployed for a two-port MIMO configuration having a size of 46 × 20 × 2 µm3 with interelement separation of less than a quarter-wavelength of 0.18λ (λ at 9 THz). The two-port configuration operates in the 9–13.25 THz frequency range, with better than −25 dB isolation. Further, the two-port THz antenna is mirrored vertically with a separation of 0.5λ to form the four-port MIMO configuration. The proposed four-port THz antenna has dimensions of 46 × 46 × 2 µm3 and operates in the frequency range of 9–13 THz. Isolation improvement better than −25 dB is realized by incorporating parasitic elements onto the ground plane. Performance analysis of the proposed antenna in terms of MIMO diversity parameters, viz., envelope correlation coefficient (ECC) &lt; 0.05, diversity gain (DG) ≈ 10, mean effective gain (MEG) &lt; −3 dB, total active reflection coefficient (TARC) &lt; −10 dB, channel capacity loss (CCL) &lt; 0.3 bps/Hz, and multiplexing efficiency (ME) &lt; 0 dB, is performed to justify the appropriateness of the proposed antenna for MIMO applications. The antenna has virtuous radiation properties with good gain, which is crucial for any wireless communication system, especially for the THz communication network.

Location Aware Beamforming in Millimeter-Wave Band Ultra-Dense Radio Access Networks. Part 1. Model of Two Links

The evolution of 1G to 4G radio access networks (RANs) over the past 40 years has shown that beamforming (BF) capabilities add an additional spatial dimension to traditional device multiplexing methods. When base stations (gNodeB - gNB) and user equipment (UE) form narrow antenna radiation patterns (APPs), in addition to frequency, time and code division of channels, an additional spatial dimension appears that implements spatial multiplexing. This concept has been known for quite a long time, but the full implementation of its capabilities in practice is expected with the widespread adoption of millimeter wave (mmWave) ultra-dense networks (UDN) of the fifth (5G) and subsequent (B5G) generations. To control APP, the approach of preliminary analysis of training sequences about the current situation in the radio channel - CSI (Channel State Information) - can be used, but its overhead costs become unacceptably high in conditions of ultra-dense distribution of devices. An alternative approach is positioning-based BF. The validity, relevance and prospects of this approach are determined by the fact that for 5G networks, unlike previous generations, for the first time the requirements for UE positioning accuracy up to one meter are formalized. Initial research in the field of location-aware BF has already been carried out over the past years, however, mainly for particular scenarios of one or more radio links between gNBs and fixed UEs. In this work, for the first time, a scientifically based methodology for controlling the beam pattern of a stationary gNB based on the positioning of a mobile UE for a two-radio link scenario is formalized and implemented in software. The problem of practical implementation of BF is the difficulties to predict level of interference due to the mutual influence of radio links with mobile UEs. When estimating the instantaneous signal-to-interference ratio in a two-radio link scenario between two fixed gNBs that perform BF based on the current location of mobile UEs as they move, it is necessary to take into account the mutual influence of each other's radio links on each other. In such a scenario, a transmitter on one radio link acts both as a source of a wanted signal for one UE and as a source of an interfering signal for another UE. The task of assessing interference for such a scenario is complicated by the nonlinearity of the transmitter and/or receiver ARPs. The model developed and implemented in software in this work uses the functions of the Phased Array System Toolbox Matlab extension package. The simulation results show a significant scatter (tens of dB) of the instantaneous signal-to-interference ratio depending on the territorial separation of devices and can be used to justify scenarios for the construction and operation of 5G/B5G UDN.

Decentralized piggybacking-based dissemination of Cooperative Awareness Messages in vehicular ad-hoc networks

Vehicle-to-Vehicle (V2V) communication has shown great promise to improve road safety and traffic efficiency via the periodic broadcasting of Cooperative Awareness Messages (CAMs), in which traffic information could be exchanged among adjacent vehicles. Since each CAM contains local-observed traffic information such as geolocation, speed, and safety alerts, frequent CAM losses will decrease the reliability on avoiding crashes and injuries on the road. Existing solutions tend to recover the lost CAMs through either source-based re-transmission or neighbor-based forwarding, which may suffer from significant performance degradation due to the fast movement of vehicles and high dynamic network topology. In this paper, we develop a decentralized cooperative broadcasting protocol for CAM dissemination, where each vehicle can piggyback some received CAMs in its routine broadcasting to help others recover their lost CAMs. To promote cooperation of CAM piggybacking, a new data structure called bitmap is introduced to record the packet receiving status at each vehicle, based on which time slots could be allocated to vehicles with low data collisions, lost CAMs could be detected only using each vehicle’s local information, and the qualities of wireless links could be estimated dynamically. Then, we propose two piggybacking schemes, Benefit-based Piggybacking (BP) and Suggestion-based Piggybacking (SP), aiming to maximize the average CAM delivery ratio. We evaluate the proposed schemes in simulations with realistic vehicle mobility traces and channel models. Simulation results show that our bitmap-based lost CAM detection has superior performance than traditional request-based solutions. In comparison with forwarding-based schemes, our schemes can achieve much higher CAM broadcast reliability with short time delay and small communication overhead.

An intelligent encryption decision method for autonomous domain of multilayer satellite network

Multi-layer satellite network (MLSN) is an important part of the Space-Air-Ground Integrated Network (SAGIN), it has obvious advantages in coverage density, business processing, service efficiency and other comprehensive capabilities compared with ordinary single-layer satellite networks. However, due to the fact that many space nodes, highly dynamic topology changes and wireless links scattered in free space, MLSNs are facing the dual challenges of inefficient organization and lack of security. In this case, this paper considers providing secure encryption decision support for the return of data obtained by low earth orbit (LEO) observation satellites relying on the local autonomous region of multi-layer satellite space. By quantifying the security strength of encryption algorithms, the work to be optimized is described as the problem of maximizing the security strength under the constraint of return delay of the data. This paper thus proposes a solution based on deep reinforcement learning (DRL), which relies on reasonably setting the key supporting elements such as state, action and reward closely related to the problem to achieve fast and reliable decision output, and the simulation results show that the proposed method has better performance than many comparison methods.

Captive Animal Behavior Study by Video Analysis.

Three video analysis-based applications for the study of captive animal behavior are presented. The aim of the first one is to provide certain parameters to assess drug efficiency by analyzing the movement of a rat. The scene is a three-chamber plastic box. First, the rat can move only in the middle room. The rat's head pose is the first parameter needed. Secondly, the rodent could walk in all three compartments. The entry number in each area and visit duration are the other indicators used in the final evaluation. The second application is related to a neuroscience experiment. Besides the electroencephalographic (EEG) signals yielded by a radio frequency link from a headset mounted on a monkey, the head placement is a useful source of information for reliable analysis, as well as its orientation. Finally, a fusion method to construct the displacement of a panda bear in a cage and the corresponding motion analysis to recognize its stress states are shown. The arena is a zoological garden that imitates the native environment of a panda bear. This surrounding is monitored by means of four video cameras. We have applied the following stages: (a) panda detection for every video camera; (b) panda path construction from all routes; and (c) panda way filtering and analysis.

Movement Recognition through Inductive Wireless Links: Investigation of Different Fabrication Techniques.

In this paper, an inductive wireless link for motion recognition is investigated. In order to validate the feasibility of a wearable implementation, the use of three different materials is analyzed: a thin copper wire, a conductive yarn, and a conductive non-woven fabric. Results from the application of the developed devices on an arm are reported and discussed. It is demonstrated that the proposed textile inductive resonant wireless links are well suited for developing a compact wearable system for joint flexion recognition.

Energy-Efficient Emerging Optical Wireless Links

In recent years, the tremendous increase in data traffic carried by wireless communication networks has generated the urgent need for establishing more energy-efficient wireless communication systems. Recent advances in semiconductor and light devices have triggered remarkable research interest to the development of these optical wireless communication (OWC) links. Among them, free-space optical (FSO) links and, more recently, ultraviolet links which operate within the (UV-C) spectral band, have been considered as prime candidates to create both high speed and power effective line-of-sight (LOS) and non-light-of-sight (NLOS) free-air communication links, respectively. Moreover, transdermal optical wireless (TOW) links for telemetry with medical implants minimize the expense of power for the implant. In the current review, a background on the energy efficiency challenges in wireless communication is presented. Each of these OWC technologies is mainly discussed in terms of key energy consumption requirements and major limiting factors that affect their power performance. Energy-efficient modulation formats as well as other powerful techniques for performance enhancement such as diversity and relaying are assessed. The survey is concluded with a discussion regarding their future energy consumption requirements and trends.

Channel characterization and modeling for wireless communication link planning and design in the tropics

&lt;p&gt;Channel model provides basis in the link budgetary for planning and design of low margin systems of communication links. This paper proposed a simple and efficient channel model for wireless channel path loss characterization and modeling. Free space channel was characterized and modelled to account for both static and dynamic changes of signal that propagates through it. Correction factors in the model account for the losses due to refraction effects, as a result of abnormal refractivity condition frequent in tropical regions. The model was validated via measurement data from experiment conducted in a tropical region and a high level of agreement was observed. The proposed model can be deployed during link planning and budgetary for ultra high frequency (UHF) wireless radio services.&lt;/p&gt;

Performance Analysis of Cellular Ultradense IoT Networks With Wireless Backhauls

The rising era of smart living requires unprecedented advancements in cellular networks to support the communications of the Internet of Things (IoT), referred to as Machine-Type Communication (MTC). Hence, we consider an Ultra-Dense Network (UDN) environment supported by wireless backhaul links and investigate the achievable performance gains for MTC. By doing so, we avoid the complexity, cost, and/or infeasibility of providing fiber backhaul links for the massive number of Small Cells (SCs) found in UDNs. We utilize the Millimeter Wave (mmWave) band to support the communications between the IoT Devices (IoTDs) and their serving SCs. By doing so, the excess available bandwidth can be used to support a massive number of IoTDs while the propagation characteristics of the mmWave signals can be exploited to mitigate the severe Inter-Cell Interference (ICI) found in UDNs. In this regard, we formulate a mathematical framework using tools from stochastic geometry to derive analytical expressions for the density of supported IoTDs and the average capacities per SC on both the Access Link (AL) and the Backhaul Link (BH). In addition, we obtain a tight lower bound of the average capacity per SC under the considered wireless limited-capacity backhaul links. The obtained results show the existence of an optimal active SC density that maximizes SC utilization.

Rotating-Coordinate-Based Mutual Inductance Estimation for Drone In-Flight Wireless Charging Systems

This article proposes a fast and real-time mutual inductance estimation method for drone in-flight wireless charging systems against the continuous varying of relative position between coupling coils. In previous studies, many efforts have been made to achieve accurate mutual inductance estimation when fixed misalignment occurs in coupling coils. However, the critical challenge for in-flight wireless charging systems is to track variations of mutual inductance caused by continuously changed misalignments between coupling coils, which is rarely explored in previous studies. Accordingly, this article proposes a rotating-coordinate-based mutual inductance estimation method to track the variation of the mutual inductance timely. By applying the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">dq</i> dynamic model, the proposed estimation method is effectively enhanced in terms of rapidity and implemented simply as well as eliminating wireless communication links. With the salient features of accuracy, rapidity, and real time, it can be an ideal solution against the continuous disturbance of mutual inductance, especially for drone in-flight wireless charging systems. In this article, both simulated and experimental results are given to verify the validity of the proposed rotating-coordinate-based estimation method, wherein the relative error of the mutual inductance estimation is within 1%, and the estimation rapidity is less than 4 ms.