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Radar-embedded communication (REC) is a new type of covert communication whereby communication signals are embedded in radar backscattered echoes. Conventional REC waveform design strategies generally involve transforming the radar sampling sequence into a square matrix that can be eigenvalue decomposed; however, it may lose some original characteristics of the radar signal during this process. In this paper, we propose two REC waveform design methods based on singular value decomposition (SVD), namely, SVD-NDP (non-dominant-processing waveform based on SVD) and SVD-SNDP (shaped-non-dominant-processing waveform based on SVD), and derive the similarities between the radar signal and the proposed waveforms. We then simulate the anti-detection performance, anti-interception performance, and communication reliability of the proposed waveforms and analyze the degrees of freedom and computational complexity of their design. The results show that, compared with conventional REC waveforms, the proposed waveforms could improve communication reliability without sacrificing low probability of intercept (LPI) performance and at least double the design degrees of freedom. SVD-NDP and SVD-SNDP algorithms can reduce computational complexity by more than 30% compared with conventional waveform design algorithms based on eigenvalue decomposition when the number of communication waveforms (symbols) is set to 4 (2 bits), and the proportion of the dominant subspace is set to 50%. [ABSTRACT FROM AUTHOR]

Nonfungible tokens have a wide variety of applications in diverse settings. This article analyzes their potential benefits to companies and customers. It also highlights how they can be used in companies' product and marketing communication strategies. [ABSTRACT FROM AUTHOR]

Parameter server architecture has been identified as an efficient framework for scaling DNNs training on clusters. For large-scale deployment, communication becomes the bottleneck, and the parameter updating strategy strongly impacts the training performance and accuracy. Recent state-of-art solutions have adopted the local SGD approach, which enables workers to update their local version of models and only aggregate them to update the global parameters after finishing a number of iterations, to alleviate heavy communication pressure on the parameter server and improving the training performance. We identify three limitations of these works. First, these works do not provide an approach for determining when the worker is to update the parameter with the server under asynchronous communication strategies that can guarantee the training performance. Second, local SGD suffers from the problem of unbounded gradient delay. Previous work works well for a short delay while can not guarantee the performance with an increase of gradient delay. Third, they do not consider the system performance when determining the update interval of the local SGD, including the CPU, memory, and network, which affects the training performance extremely. We provide a self-adaptive parameter updating strategy called SaPus, which allows each worker to detect their training results through quantification of the accumulated gradient updates and determine when to update the parameter with the server adaptively and individually. Theoretical lower and upper bound of the update interval is also provided. We also propose a weighted aggregation algorithm based on a global-loss window, which is used to collect the most recent loss value of other workers to calculate a weight for the accumulated gradients of each worker to solve the unbounded delay problem in asynchronous local SGD. To increase the robustness of our parameter updating strategy, a performance model is built to provide a resource-aware lower bound for the update interval. Extensive experimental results generated on GPU cluster indicate that our model improves the training performance of DNNs, achieving up to $66.67\%$ 66. 67 % speedup as compared with state-of-art solutions. Further, results show the CPU utilization of server dropped by up to $81.1\%$ 81. 1 % and network bandwidth usage reduced to less than $1~Gbps$ 1 G b p s on an average during the training. [ABSTRACT FROM AUTHOR]

This article addresses the problem of stabilizing a continuous-time switched system affected by a completely unknown disturbance, data quantization, and time-varying delay. In the sense of combined dwell-time and average dwell-time, it is assumed that the switching is slow enough. Suppose that the bound of delay is known but the one of disturbance is unknown. An estimation for the bound of disturbance is used to counteract the unknown disturbance. By extending the approach of the delay-free case, a communication and control strategy is developed by introducing a virtual system. On this basis, the exponential decay and practical stability of the closed-loop system are guaranteed by using a Lyapunov function. Two examples are illustrated to show the usefulness of the proposed framework for stability analysis of some classes of switched systems. [ABSTRACT FROM AUTHOR]

Industrial wireless control systems are mainly designed on the premise of time-sensitive ultra-reliable low-latency communications (URLLC). With the introduction of survival time to the quality of service requirements of such systems, the design paradigm has evolved from typical link reliability (i.e., minimizing packet error rate), to service availability, that is, minimizing the chance of burst errors, which can cause loss of communication for longer than survival time. In this article, we address the implications of this evolution and present a set of survival time strategies that are designed to guarantee end-to-end dependable industrial wireless control. To ensure service availability, transmissions are divided into normal and survival modes. The presented strategies include scheduling and link adaptation that are designed to target the differences between these modes of operation, traffic prioritization to enhance service availability for users in survival mode, and more efficient multi-node, multi-path, and multi-carrier communications techniques. [ABSTRACT FROM AUTHOR]

High resolution analog to digital converters (ADCs) are conventionally used at the receiver terminals to store an accurate digital representation of the received signal, thereby allowing for reliable decoding of transmitted messages. However, in a wide range of applications, such as communication over millimeter wave and massive multiple-input multiple-output (MIMO) systems, the use of high resolution ADCs is not feasible due to power budget limitations. In the conventional fully digital receiver design, where each receiver antenna is connected to a distinct ADC, reducing the ADC resolution leads to performance loss in terms of achievable rates. One proposed method to mitigate the rate-loss is to use analog linear combiners leading to design of hybrid receivers. Here, the hybrid framework is augmented by the addition of delay elements to allow for temporal analog processing. Two new classes of receivers consisting of delay elements, analog linear combiners, and one-bit ADCs are proposed. The fundamental limits of communication in single and multi-user (uplink and downlink) MIMO systems employing the proposed receivers are investigated. In the high signal to noise ratio regime, it is shown that the proposed receivers achieve the maximum achievable rates among all receivers with the same number of one-bit ADCs. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) communications is an important technology in vehicular ad hoc network (VANET) to support autonomous data exchange among vehicles. Multiple V2V communications modes have been investigated for VANET, including dedicated short-range communications (DSRC) based on IEEE 802.11p and LTE-V2X, which are suitable for different packet transmission cases. In order to fully exploit the strengths of various modes, hybrid V2V communications strategies are designed in this paper, where each vehicle is allowed to choose different modes for different kinds of transmissions in separate frequency bands for transmission throughput improvement. Furthermore, since it is usually impractical to decide all the vehicles’ communications strategies globally due to high computational complexity and heavy overhead to broadcast the decisions, we model the selection of hybrid V2V communications strategies for vehicles as an evolutionary game. A strategy selection algorithm is then proposed, where each vehicle can select its hybrid V2V communications strategy locally based on its evaluation of the payoffs for different strategies and limited signalling from the base station. Simulation results demonstrate that the proposed algorithm can converge to an asymptotic stable state, which can improve the transmission throughput of vehicles, and is robust to the slight evaluation errors of payoffs and the strategy mutations of a few vehicles. [ABSTRACT FROM AUTHOR]

Covert wireless communications aim to hide the existence of transmission behavior from watchful adversaries to enhance security. In this paper, we propose a spectrum mask based covert communication strategy in Internet of Things (IoT) networks, where the overt channels are leveraged to enhance the covertness. Specifically, the legitimate IoT transmitter superimposes its own message on the overt channel to avoid being detected by the warden. We assume that proper Gaussian signaling (PGS) is adopted at the overt channel, and improper Gaussian signaling (IGS) is adopted at the legitimate transmitter to improve the covert transmission performance. To maximize the covert rate of the legitimate IoT system, a joint transmit power and IGS factor optimization problem is formulated under the constraints of covertness requirement. The metric of minimum error detection probability, that represents the worst-case for the legitimate transmitter, is utilized to measure the covertness. By exploiting the piece-wise monotonic properties of the objective function and the constraints, we derive the optimal transmit power and IGS factor pairs in both the IGS and PGS schemes. Finally, extensive numerical results are presented to demonstrate that the IGS scheme can improve the covert rate compared to the PGS scheme under a given covertness constraint. [ABSTRACT FROM AUTHOR]

In this article, we consider a scenario of cooperative task servicing, with a team of heterogeneous robots with different maximum speeds and communication radii, in charge of keeping the network intermittently connected. We abstract the task locations into a one-dimensional cycle graph that is traversed by the communicating robots, and we discuss intermittent communication strategies so that each task location is periodically visited, with a worst-case revisiting time. Robots move forward and backward along the cycle graph, exchanging data with their previous and next neighbors when they meet, and updating their region boundaries. Asymptotically, each robot is in charge of a region of the cycle graph, depending on its capabilities. The method is distributed, and robots only exchange data when they meet. [ABSTRACT FROM AUTHOR]

In this article, a novel distributed attitude coordination control scheme is proposed for a group of rigid spacecraft with unknown disturbances. The communication topology is described by a general directed graph, and the leader's attitude is available to only a small fraction of followers. Different from existing attitude coordination control schemes, here an event-triggered communication strategy without Zeno phenomenon is designed, which avoids continuous communication between neighboring spacecraft and considerably reduces the communication burden. Moreover, a nonlinear observer is constructed for each follower, which enables us to estimate and compensate for a large class of disturbances exactly. The proposed scheme is able to ensure the boundedness of all closed-loop signals and steer the attitude tracking errors into an arbitrarily small residual set, regardless of the intermittent communication. Simulation results illustrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Imperfect Channel State Information at the Transmitter (CSIT) is inevitable in modern wireless communication networks, and results in severe multi-user interference in multi-antenna Broadcast Channel (BC). While the capacity of multi-antenna (Gaussian) BC with perfect CSIT is known and achieved by Dirty Paper Coding (DPC), the capacity and the capacity-achieving strategy of multi-antenna BC with imperfect CSIT remain unknown. Conventional approaches therefore rely on applying communication strategies designed for perfect CSIT to the imperfect CSIT setting. In this work, we break this conventional routine and make two major contributions. First, we show that linearly precoded Rate-Splitting (RS), relying on the split of messages into common and private parts and linear precoding at the transmitter, and successive interference cancellation at the receivers, can achieve larger rate region than DPC in multi-antenna BC with partial CSIT. Second, we propose a novel scheme, denoted as Dirty Paper Coded Rate-Splitting (DPCRS), that relies on RS to split the user messages into common and private parts, and DPC to encode the private parts. We show that the rate region of DPCRS in Multiple-Input Single-Output (MISO) BC with partial CSIT is enlarged beyond that of conventional DPC and that of linearly precoded RS. Gaining benefits from the capability of RS to partially decode the interference and partially treat interference as noise, DPCRS is less sensitive to CSIT inaccuracies, networks loads and user deployments compared with DPC and other existing transmission strategies. [ABSTRACT FROM AUTHOR]

Due to the openness of the transmission medium, it is necessary for radio systems to have anti-jamming abilities. Traditional anti-jamming methods such as sequence-based frequency hopping and direct sequence spread spectrum have shortcomings of low spectral efficiency and fixed communication patterns. With the development of software-defined radio, jamming devices are increasingly advanced and efficient. In this article, we propose a new paradigm for anti-jamming called DSAJ. With the help of cognitive radio and machine learning, the aim of DSAJ is to learn the dynamic and complex spectrum environment and obtain an optimal communication strategy. We first introduce the basic concept of anti-jamming communications and provide a brief summary of anti-jamming methods. Then, through a case study, mathematical modeling and applications of DSAJ are discussed for both single-user and multi-user systems. A real-life DSAJ testbed is described, and some potential research directions are discussed. [ABSTRACT FROM AUTHOR]

This article proposes beamforming strategies for multiuser communication networks by jointly considering the data rate and battery lifetime of each user. We consider a practical power consumption model, where the decoding power of each user device is a nonlinear function of the data rate. We assume each user device is powered by a battery with limited capacity. The power consumption of the user device determines the expected battery lifetime which conforms to Peukert's law. Two non-convex optimization problems are considered based on two criteria: maximizing the minimum of user throughputs (MaxMin) and maximizing the weighted sum of user throughputs (MaxSum), during the battery lifetime. For the MaxMin problem, we solve it by using a bisection search algorithm. For the MaxSum problem, we propose an algorithm based on the successive convex approximation, which can find a stable point that approximates the optimum solution. Numerical simulations verify that the expected data throughput of the multiuser system can be greatly improved by properly choosing the beamforming strategies using the proposed algorithms. [ABSTRACT FROM AUTHOR]

We consider a dual-hop, decode-and-forward network, where the relay can operate in full-duplex (FD) or half-duplex (HD) mode (X-duplex relay). We model the residual self-interference as an additive Gaussian noise with variance proportional to the relay transmit power, and we assume a Gaussian input distribution at the source. Unlike previous work, we assume that the source is only aware of the transmit power distribution adopted by the relay, but not of the symbols that the relay is currently transmitting. This assumption better reflects the practical situation, where the relay node forwards data traffic but modifies physical-layer or link-layer control information. We then identify the optimal power allocation strategy at the source and relay, which in some cases coincides with the HD transmission mode. We prove that such strategy implies either FD transmissions over an entire time frame or FD/HD transmissions over a variable fraction of the frame. We determine the optimal transmit power level at the source and relay for each frame, or fraction thereof. We compare the performance of our scheme against reference FD and HD techniques, which assume that the source is aware of the symbols instantaneously transmitted by the relay, and show that our solution closely approaches such strategies. [ABSTRACT FROM AUTHOR]

Objective: The purpose of this contribution is to estimate the path loss of capacitive human body communication (HBC) systems under practical conditions. Methods: Most prior work utilizes large grounded instruments to perform path loss measurements, resulting in overly optimistic path loss estimates for wearable HBC devices. In this paper, small battery-powered transmitter and receiver devices are implemented to measure path loss under realistic assumptions. A hybrid electrostatic finite element method simulation model is presented that validates measurements and enables rapid and accurate characterization of future capacitive HBC systems. Results: Measurements from form-factor-accurate prototypes reveal path loss results between 31.7 and 42.2 dB from 20 to 150 MHz. Simulation results matched measurements within 2.5 dB. Comeasurements using large grounded benchtop vector network analyzer (VNA) and large battery-powered spectrum analyzer (SA) underestimate path loss by up to 33.6 and 8.2 dB, respectively. Measurements utilizing a VNA with baluns, or large battery-powered SAs with baluns still underestimate path loss by up to 24.3 and 6.7 dB, respectively. Conclusion: Measurements of path loss in capacitive HBC systems strongly depend on instrumentation configurations. It is thus imperative to simulate or measure path loss in capacitive HBC systems utilizing realistic geometries and grounding configurations. Significance: HBC has a great potential for many emerging wearable devices and applications; accurate path loss estimation will improve system-level design leading to viable products. [ABSTRACT FROM AUTHOR]

Mobile robots that wish to communicate wirelessly often suffer from fading channels. They need to devise an energy-efficient strategy to search for a high-channel-gain position in a near vicinity from which to begin communications. Such a strategy has recently been introduced through the mobility diversity with multithreshold algorithm (MDMTA). In this paper, we establish the theoretical framework for a generalized version of the MDMTA. This allows improved wireless communications in fading channels for mobile robots via intelligent robotic motion with low mechanical energy expenditure. [ABSTRACT FROM AUTHOR]

We study a multinode network, where a multiantenna transmitter \textT_\mathrmx communicates with its desired receiver \textR_\mathrmx, whereas a cluster \mathcalP\triangleq\\textP\mathrm{x,n, \ n=1,\ldots,N\} of unintended nodes is disturbed by the \textT_\mathrmx– \textR_\mathrmx (TR) communication. To prevent severe performance degradation, we impose a constraint on the total interference that is inflicted at the nodes of \mathcalP . The TR link contains a line-of-sight component, whereas the propagation environment for each \textT_\mathrmx– \textP\mathrm{x,n} link is shadowed. The \textT_\mathrmx node is preprocessing the information sequence by means of a precoding matrix that is optimized to achieve the ergodic capacity under a constraint on the maximum admissible ergodic interference power, arriving on \mathcalP . In this paper, we show that the optimum precoding strategy involves the transmission of a single stream over the precoding direction, i.e., the eigenvector of the precoding matrix, which corresponds to beamforming along the instantaneous direction of the TR-link channel. The solution of the remaining power allocation problem yields the optimal precoding matrix. For this setup, we provide an efficient stochastic characterization of the network, which allows us to obtain an analytical expression for the TR-link ergodic capacity; this problem has been previously open, even for the case of a single-antenna node \textT_\mathrmx and a single-element set \mathcalP . We complement the analysis by deriving the TR-link signal-to-noise ratio and the average bit error rate, which are associated with our transmission scheme. Numerical results corroborate the theoretical analysis and reveal an interplay between the network parameters and their impact on the TR-link performance. [ABSTRACT FROM AUTHOR]

Global virtual teams provide numerous benefits for corporations employing virtual organizational and for individual teams and team members. However, virtual collaboration also presents some well-recognized challenges. A growing body of research has examined the process of virtual teaming and the challenges inherent that process. This study seeks to address some of the gaps in the existing literature. Specifically, it examines leadership roles, socioemotional communication strategies, and the use of technology to establish relational among team members. The study focuses on virtual-team collaboration among technical communication students University of Limerick, Limerick, Ireland, and at the University of Central Florida, Orlando, Florida. [ABSTRACT FROM AUTHOR]

Provides a listing of board members, committee members and society officers. [ABSTRACT FROM PUBLISHER]

A decade of research on traffic classification has provided various methodologies to investigate the traffic composition in data communication networks. Many variants or combinations of such methodologies have been introduced continuously to improve the classification accuracy and efficiency. However, the level of classification details is often bounded to identifying protocols or applications in use. In this article, we propose a fine-grained traffic classification scheme based on the analysis of existing classification methodologies. This scheme allows to classify traffic according to the functionalities in an application. In particular, we present a traffic classifier which utilizes a document retrieval technique and applies multiple signatures to detect the peer-to-peer application traffic according to different functionalities in it. We show that the proposed scheme can provide more in-depth classification results for analyzing user contexts. [ABSTRACT FROM PUBLISHER]