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In a multiple access spread-spectrum communication system, the bit error performance is usually limited by the mutual interference between users. The use of multi-user detection is an effective method to reduce such interference. In this paper, we consider two linear multi-user detectors, namely, decorrelating detector and minimum mean-square-error detector, applied to a multiple access chaotic-sequence spread-spectrum communication system. An approach to calculate the bit error rate (BER) for such systems is presented. The calculated BERs are compared with those obtained using brute-force computer simulations which give the true system performance. [ABSTRACT FROM AUTHOR]

The article describes a modern system of control and communication integrated in an in-situ soil sensor to make it autonomous in operation, energy and data transfer at low cost. Network of such sensors can monitor continuously soil moisture over a catchment with low maintenance. A recent industrial standard of radio communication, Long Range Wide Area Network (LoRaWAN) is presented. It permits rapid deployment of a sensor in a remote observatory, and the transfer in real time of sensor data to a central web-accessed database, via a LoRaWAN receiver, or gateway, 12 km away. In this situation transmission loss can reach a rate of 30%. Good quality antenna can lower it below 5% without extensive cost. Double messaging and other transmission algorithms are a possibility, taking into account consumption. Currently, sensors measuring one point every ten minutes can last seven months with four cheap AA alkaline batteries. Further gains would increase lifetime in same conditions by 30%. [ABSTRACT FROM AUTHOR]

Signal acquisition and sensing in underwater systems and applications is typically a challenging issue due to the small signal strength within the background noise. Here, we present a ring vector sensor communication receiver that can significantly improve signal acquisition, by utilizing the underwater acoustic vector field components, compared to the scalar component. The vector sensor receiver is a multichannel receiver that measures particle velocities, which are vector components of the underwater acoustic field, in addition to the scalar field component. According to the combination of our measured experimental data with our signal acquisition performance analysis, the introduced ring vector sensor receiver exhibits higher signal acquisition probabilities for the vector components compared to the scalar component. This can be attributed to certain characteristics of the vector field components. Another advantage of this multichannel receiver is that combining all of its channels can further increase the signal acquisition and packet detection probability in underwater communication systems compared to a single-channel approach. [ABSTRACT FROM AUTHOR]

An increase in the size of on-board antenna reflectors is a key technology in providing economical services by miniaturized portable equipment in future mobile satellite communication systems. In practice, a mesh antenna can be used as the on-board antenna. However, since the reflector surface of this antenna is supported by the cable and the mesh, and its size is larger, the surface is subject to larger thermal deformation in orbit than is the solid antenna reflector. Conventional compensation methods such as passive thermal control or rotation of the antenna reflector cannot maintain the required antenna performances. Various methods have been reported to compensate for the deterioration of antenna performance by thermal deformation. This paper describes a static shape control system for a 10-m diameter antenna which actively compensates for the deformation by using a shape-measuring sensor and shape-compensation actuator. The configuration of the sensor and the experimental results by a functional model are described to confirm the design validity. The shape-compensation method by the actuator was cone firmed to be useful in achieving a required surface accuracy. [ABSTRACT FROM AUTHOR]

A significant technological transformation has recently occurred in the agriculture sector. Precision agriculture is one among those transformations that largely focus on the acquisition of the sensor data, identifying the insights, and summarizing the information for better decision-making that would enhance the resource usage efficiency, crop yield, and substantial quality of the yield resulting in better profitability, and sustainability of agricultural output. For continuous crop monitoring, the farmlands are connected with various sensors that must be robust in data acquisition and processing. The legibility of such sensors is an exceptionally challenging task, which needs energy-efficient models for handling the lifetime of the sensors. In the current study, the energy-aware software-defined network for precisely selecting the cluster head for communication with the base station and the neighboring low-energy sensors. The cluster head is initially chosen according to energy consumption, data transmission consumption, proximity measures, and latency measures. In the subsequent rounds, the node indexes are updated to select the optimal cluster head. The cluster fitness is assessed in each round to retain the cluster in the subsequent rounds. The network model's performance is assessed against network lifetime, throughput, and network processing latency. The experimental findings presented here show that the model outperforms the alternatives presented in this study. [ABSTRACT FROM AUTHOR]

Unmanned traffic management (UTM) systems will become a key enabler to the future drone market ecosystem, enabling the safe concurrent operation of both manned and unmanned aircrafts. Currently, these systems are usually tested by performing real scenarios that are costly, limited, hardly scalable, and poorly repeatable. As a solution, in this paper we propose an agent-based simulation platform, implemented through a micro service architecture, which may simulate UTM information sources, such as flight plans, telemetry messages, or tracks from a surveillance network. The final objective of this simulator is to use these information streams to perform a system-level evaluation of UTM systems both in the pre-flight and in-flight stages. The proposed platform, with a focus on simulation of communications and sensors, allows to model UTM actors' behaviors and their interactions. In addition, it also considers the manual definition of events to simulate unexpected behaviors/events (contingencies), such as communications failures or pilots' actions. In order to validate our architecture, we implemented a simulator that considers the following actors: drones, pilots, ground control stations, surveillance networks, and communications networks. This platform enables the simulation of the drone trajectory and control, the C2 (command and control) link, drone detection by surveillance sensors, and the communication of all agents by means of a mobile communications network. Our results show that it is possible to truthfully recreate complex scenarios using this simulator, mitigating the disadvantages of real testbeds. [ABSTRACT FROM AUTHOR]

The normal operations of radar systems and communication systems under the condition of spectrum coexistence are facing a huge challenge. This paper uses game theory to study power allocation problems between multistatic multiple-input multiple-output (MIMO) radars and downlink communication. In the case of spectrum coexistence, radars, base station (BS) and multi-user (MU) have the working state of receiving and transmitting signals, which can cause unnecessary interferences to different systems. Therefore, when they work together, they should try to suppress mutual interferences. Firstly, the signal from BS is considered as interference when radar detects and tracks targets. A supermodular power allocation game (PAG) model is established and the existence and uniqueness of the Nash equilibrium (NE) in this game are proved. In addition, the power allocation problem from BS to MU is also analyzed, and two Stackelberg PAG models are constructed. It is proved that the NE of each game exists and is unique. Simultaneously, two Stackelberg power allocation iterative algorithms converge to the NEs. Finally, numerical results verify the convergence of the proposed PAG algorithms. [ABSTRACT FROM AUTHOR]

For the ultra-wideband chaotic radio pulses an analytical model of an energy detector is designed and closed-form expressions for the optimal threshold and the detection probabilities are derived. The analytical solution is compared with the results of the numerical simulation. The model proves to be well-suited for the chaotic radio pulses with large base B (or processing gain, or the number of freedom degrees), namely, B ≥ 100. Potential applications areas of the proposed model are ultra-wideband communications with chaotic pulse carriers, e.g., ultra-wideband systems of 802.15.x standards, and multi-element chaotic communication systems. [ABSTRACT FROM AUTHOR]

Up-conversion single-photon detectors (UCSPD) are based on sum-frequency generation of the telecom band single-photons to near-infrared wavelengths at which efficient and low-noise silicon single-photon detectors are available. Moreover, because of high dynamic range of silicon single-photon detectors, UCSPD is suitable for high-speed quantum communication. UCSPDs reported to date, however, have a very narrow fixed window of detectable wavelengths, severely limiting their applications in wavelength-multiplexed quantum networks. In this work, we report a tunable UCSPD module that covers the complete telecom C band, making it suitable for quantum communication networks based on sharing wavelength-multiplexed entangled photons. [ABSTRACT FROM AUTHOR]

This paper provides a systematic characterization of Zero-Forcing (ZF) detectors over multiple-input multiple-output (MIMO) channels that experience both small and large-scale fading. In particular, we consider the generic K distribution (Rayleigh/gamma distribution) to model the composite fading fluctuations and also assume the general case of semi-correlated small-scale fading. In the following, novel exact analytical expressions for the achievable sum rate are derived, followed by asymptotic expressions in the high and low Signal-to-Noise ratio (SNR) regimes. In these limiting cases, two common and insightful affine expansions are studied followed by new, closed-form upper and lower bounds on the sum rate that remain tight for all SNRs. In the second part of the paper, we present exact tractable expressions along with first-order expansions for the symbol error rate (SER) and outage probability; we also quantify the performance of ZF detectors in terms of diversity order and array (or coding) gain. The implications of the model parameters on the ZF detector performance are investigated via Monte-Carlo simulations which also validate the theoretical analysis. [ABSTRACT FROM AUTHOR]

In recent years there has been an increasing need for miniature, low-cost, commercially accessible, and user-friendly sensor solutions for wireless body area networks (WBAN), which has led to the adoption of new physical communication interfaces providing distinctive advantages over traditional wireless technologies. Ultra-wideband (UWB) and intrabody communication (IBC) have been the subject of intensive research in recent years due to their promising characteristics as means for short-range, low-power, and low-data-rate wireless interfaces for interconnection of various sensors and devices placed on, inside, or in the close vicinity of the human body. The need for safe and standardized solutions has resulted in the development of two relevant standards, IEEE 802.15.4 (for UWB) and IEEE 802.15.6 (for UWB and IBC), respectively. This paper presents an in-depth overview of recent studies and advances in the field of application of UWB and IBC technologies for wireless body sensor communication systems. [ABSTRACT FROM AUTHOR]

The use of wireless technologies in the field of agriculture, or so-called smart or precision agriculture, is considered as one of the main efforts applied nowadays to multiply the food production on earth. However, wireless sensor network (WSN) technology is still at its early development stage and its application in agriculture and food industry is still rare due to the lack of farmers' awareness and outreach about the matter. This paper presents a new agro-sensor named AgriLogger with an aim to collect, store for long periods and transmit agrometeorological data represented by temperature and relative humidity in remote areas hard to reach and not served by telecommunication networks. The sensor exhibits long battery life, in the order of 10 years, thanks to low consumption technologies and to hardware sleep/wake up approach. It can be remotely placed on preselected sites through a customized drone. This latter, equipped with a dedicated payload, can then return on the sites where sensors have been placed, and, while hovering, wakes up the single devices and uploads their collected data through local wireless network. Field tests have demonstrated that the sensor, after being placed manually in two different positions, inside and outside a vineyard canopy, is able to collect and store successfully agrometeorological data like temperature and relative humidity. Moreover, the use of a drone potentially allows the collection of data from remote areas and, therefore, is able to provide a periodical monitoring of agro-ecological conditions. [ABSTRACT FROM AUTHOR]

We propose a decision feedback (DFB) receiver at the relay of a two-phase (2P) two-way relay (TWR) communication system that employs pilotless orthogonal modulation (such as frequency-shift keying) in the uplink and physical-layer network coding over finite field in the downlink. The proposed relay receiver is able to attain a performance very close to that of an ideal coherent detector in the presence of time-selective Rayleigh fading and additive white Gaussian noise in the uplinks. It exploits the fact that when the uplink symbols from the users are different, then the fading gains affecting these symbols can be separated and individually tracked at the relay. In essence, the proposed receiver performs random channel sounding although no actual pilots are transmitted. The channel estimates obtained this way can then be subsequently used in a coherent detector to improve the reliability of the relay detected data. To ensure fast convergence, we propose to kick start the DFB receiver using a partial-coherent detector developed earlier by the authors. We compare the performance of the proposed system against a similar 2P-TWR system that employs differential phase-shift keying (DPSK) in the uplink and DFB multiple-symbol differential detection at the relay. We found that the proposed pilotless orthogonal modulation system can actually attain a significantly lower bit error rate (BER) than its DPSK counterpart. For static fading and a BER of \mbox10^-3, the signal-to-noise ratio (SNR) gap between the two approaches is 1 dB in the binary case and 8 dB in the quaternary case. These gaps increase further with time-selective fading. [ABSTRACT FROM AUTHOR]

Orthogonal modulation, for example, frequency-shift keying (FSK) or pulse-position modulation (PPM), is primarily used in relatively-low-rate communication systems that operate in the power-limited regime. Optimal noncoherent detection of orthogonally modulated signals takes the form of sequence detection and has exponential (in the sequence length) complexity when implemented through an exhaustive search among all possible sequences. In this work, for the first time in the literature, we present an algorithm that performs generalized-likelihood-ratio-test (GLRT) optimal noncoherent sequence detection of orthogonally modulated signals in flat fading with log-linear (in the sequence length) complexity. Moreover, for Rayleigh fading channels, the proposed algorithm is equivalent to the maximum-likelihood (ML) noncoherent sequence detector. Simulation studies indicate that the optimal noncoherent FSK detector attains coherent-detection performance when the sequence length is on the order of 100, offering a 3–5 dB gain over the typical energy (single-symbol) detector. While the conventional exhaustive-search approach becomes infeasible for such sequence lengths, the proposed implementation requires a log-linear only number of operations, opening new avenues for practical deployments. Finally, we show that our algorithm also solves efficiently the optimal noncoherent sequence detection problem in contemporary radio frequency identification (RFID) systems. [ABSTRACT FROM AUTHOR]

In inter-vehicle communication systems based on dedicated short-range communications (DSRC), frame detection is essential for the correct demodulation of a received frame. Owing to the fast mobility of vehicles and the relatively high radio frequency carrying DSRC signals, the frame detection reliability suffers from low signal-to-interference-plus-noise ratio (SINR) and time-varying noise and interference. To address this issue, this study proposed a new detection method to improve the reliability of DSRC receivers in highly dynamic outdoor environments. Specifically, a novel detection metric based on autocorrelation was first proposed to achieve a low and stable probability of false alarm (PFA). Then, the oversampling technique was employed to improve the detection probability (PD) in low-SINR regimes. Finally, a reference design was also presented on a field-programmable gate array (FPGA) for the proposed scheme. Simulation results demonstrated that both low PFA and high PD can be achieved simultaneously in vehicular communications by using the proposed method. Results given by the hardware implementation based on FPGA agree that the feasibility and complexity of our method is acceptable. [ABSTRACT FROM AUTHOR]

Wireless sensors operating in harsh environments have the potential to be error-prone. This paper presents a distributive model-based diagnosis algorithm that identifies nonlinear sensor faults. The diagnosis algorithm has advantages over existing fault diagnosis methods such as centralized model-based and distributive model-free methods. An algorithm is presented for detecting common non-linearity faults without using reference sensors. The study introduces a model-based fault diagnosis framework that is implemented within a pair of wireless sensors. The detection of sensor nonlinearities is shown to be equivalent to solving the largest empty rectangle (LER) problem, given a set of features extracted from an analysis of sensor outputs. A low-complexity algorithm that gives an approximate solution to the LER problem is proposed for embedment in resource constrained wireless sensors. By solving the LER problem, sensors corrupted by non-linearity faults can be isolated and identified. Extensive analysis evaluates the performance of the proposed algorithm through simulation. [ABSTRACT FROM AUTHOR]

Deep learning (DL) is a powerful technique which has achieved great success in many applications. However, its usage in communication systems has not been well explored. This paper investigates algorithms for multi-signals detection and modulation classification, which are significant in many communication systems. In this work, a DL framework for multi-signals detection and modulation recognition is proposed. Compared to some existing methods, the signal modulation format, center frequency, and start-stop time can be obtained from the proposed scheme. Furthermore, two types of networks are built: (1) Single shot multibox detector (SSD) networks for signal detection and (2) multi-inputs convolutional neural networks (CNNs) for modulation recognition. Additionally, the importance of signal representation to different tasks is investigated. Experimental results demonstrate that the DL framework is capable of detecting and recognizing signals. And compared to the traditional methods and other deep network techniques, the current built DL framework can achieve better performance. [ABSTRACT FROM AUTHOR]

Optimal channel switching that provides the highest performance over a set of Gaussian channels with variable utilization costs is investigated in the presence of average power and average cost constraints. First, generic cost functions are considered, and it is shown that the optimal channel switching strategy performs channel switching (time sharing) among at most three different channels and always operates at the average power and average cost limits. Also, for channel switching between two channels, relations between the optimal power levels are obtained depending on the average power limit, and it is proved that the ratio of the optimal power levels is upper bounded by the ratio of the larger noise variance to the smaller one. In addition, for logarithmic cost functions, the convexity properties of the error probability are investigated as a function of power and cost, and the optimal channel switching strategy is shown to employ at most two channels, which can easily be determined based on specific formulas, when the average power limit is larger than a certain threshold. Numerical examples are presented to provide illustrations of the theoretical results. [ABSTRACT FROM PUBLISHER]

In the last period (last 3 years) the maritime domain, especially the sea transportation and fossil resources exploitation became the most important aspects of the international politics and our lives. Because of the COVID19 situation and now the conflict between Russia and Ukraine, the maritime domain was pushed to its limits. What a few years ago was a safety area of navigation, now this one can be transformed very quickly in a dangerous one. It is important to develop fast, systems for monitoring sea areas and platforms of intervention in case of distress situations. To have a real-time system of monitoring and intervention on sea it is mandatory to have redundant maritime communications. The article presents the most relevant publications related to maritime offshore applications and communications that support them. [ABSTRACT FROM AUTHOR]

Massive multiple-input multiple-output (mMIMO) is a promising technique to realize the ever-increasing demand for high-speed data, quality of service (QoS), and energy efficiency for 5G and beyond wireless systems. However, the increased number of users in mMIMO systems significantly affects performance of the existing approximate matrix inversion based and matrix inversion less iterative symbol detection techniques. Conventional detection algorithms cannot learn the inter-relations of input-output parameters based on available data without having specific mathematical models of communication scenarios. Moreover, existing deep learning (DL) based symbol detection models lack in-network compression, resulting in large training time and high computational load while expected to be deployed in a low latency communication system. In this article, a sparse refinement architecture is proposed for symbol detection in uplink mMIMO. The proposed DL architecture requires less trainable parameters as compared to a conventional fully connected detection network and refines the estimated symbol vector in each layer. Convergence of the proposed symbol detection technique is analytically justified. An expression for the approximate upper bound on the BER is derived which is supported by simulations. The obtained results prove viability of the proposed symbol detection model as compared to the several existing state-of-art uplink mMIMO detection techniques, in terms of superior the error performance and low computational complexity. [ABSTRACT FROM AUTHOR]

Due to the increasing demand for spectrum resources, the co-existence of communications and radar systems has been proposed that allows radar and communications systems to operate in the same frequency band. On the other hand, deep learning has shown great potential in revolutionizing communications systems. In this work, we investigate the use of deep learning in communications systems subject to interference from radar systems. Specifically, we consider a single-carrier communications system. Linear frequency-modulated (LFM) and frequency-modulated continuous-wave (FMCW) are considered for radar. Several important system parameters, including the level of noise and interference, the radar interference coverage, the symbol duration, feature extraction methods and the number of hidden layers are investigated for the performance of the detector. Fully connected deep neural network (FCDNN) and long short-term memory (LSTM) detectors are implemented, where principle component analysis (PCA) is applied to preprocess the observed signals for the FCDNN detector. Numerical results show that the learning-based detector achieves comparable performance in the radar-communication system to the traditional detector but without interference cancellation. Preprocessing the received signals with PCA can improve the performance of FCDNN when interference is strong. Also, LSTM shows more robust performance than FCDNN when the channel has time-related distortion. [ABSTRACT FROM AUTHOR]

We consider realistic long-haul optical links, with linear and nonlinear impairments, and investigate the application of time-frequency packing with low-order constellations as a possible solution to increase the spectral efficiency. A detailed comparison with available techniques from the literature will be also performed. We will see that this technique represents a feasible solution to overcome the relevant theoretical and technological issues related to this spectral efficiency increase and could be more effective than the simple adoption of high-order modulation formats. [ABSTRACT FROM PUBLISHER]

Abstract: Wide-area situational awareness for critical infrastructure protection has become a topic of interest in recent years. As part of this interest, we propose in this paper a smart mechanism to: control real states of the observed infrastructure from anywhere and at any time, respond to emergency situations and assess the degree of accuracy of the entire control system. Particularly, the mechanism is based on a hierarchical configuration of sensors for control, the ISA100.11a standard for prioritization and alarm management, and the F-Measure technique to study the level of accuracy of a sensor inside a neighborhood. [Copyright &y& Elsevier]

In the modern technological world, there are several key factors in the construction of sensor networks. These include maximizing the coverage and minimizing the cost of the network. Like any information system, the sensor network must also meet the conditions of survivability. This is why the development of a method for assessing the survivability of the sensor network is also a key factor. The purpose of this study is to develop a method to establish the maximum coverage of the territory of the sensor network at minimum cost with the ability to assess the survivability of the network. Coverage maximization while minimizing the network's cost is achieved by finding the optimal pair of values of the coverage radius and the level of the intersection of coverage areas. These values are found by solving a nonlinear multicriteria optimization problem with the use of the genetic algorithm. The designed method for estimating the survivability of sensor networks takes into account not only the importance of network components but also the bandwidth of the network elements. The result of using the proposed methods is a set of Pareto optimal pairs of values of the radii of coverage and the value of the intersection of the coverage areas. In the case of network survivability assessment, the result, in addition to the percentage assessment, is a set of vulnerable sensors and network communication channels. The proposed network survivability estimation method improved the estimation accuracy by 18% compared to methods used in previous works. [ABSTRACT FROM AUTHOR]

Continuous phase modulation (CPM) is a widely used modulation scheme in communication systems. However, difficulties arise with the design of CPM receivers, due to the nonlinear nature of CPM. One popular solution is to linearize CPM with pulse amplitude modulation (PAM) representation. In this paper, a reduced-complexity non-data-aided (NDA) timing recovery method for PAM-based M-ary CPM receivers is proposed. The proposed method is based on the PAM representation and maximum likelihood principle. The merits of the proposed method are twofold. On one hand, the proposed method is reduced-complexity in nature for PAM-based CPM receivers, i.e., it shares the match filter bank with PAM-based detectors. On the other hand, it is shown that the performance of the proposed method is better than the existing method with some modulation schemes. Therefore, the proposed method provides an important synchronization component for PAM-based M-ary CPM receivers. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) promises widespread connection of sensors and devices such that smart cities, connected transport and other similar visions can be realised. However, to realise this a new wireless technology is required that is optimised for this particular application, providing very low cost, extremely long battery life and excellent coverage. This wireless technology needs to be an open global standard in order to foster a vibrant eco-system of key players. This paper discusses the issues involved in developing standards in the wireless telecommunications space before using a possible new IoT wireless standard as a case study to illustrate the issues with standardisation. [ABSTRACT FROM AUTHOR]

Wireless Sensor Networks are used in situations where it becomes difficult to deploy and utilize networks with fixed infrastructure. Group Management within such network is an important challenge which is considered as a fundamental objective of such deployment. A good number of schemes have been proposed as a solution to this problem in the existing literature; however it is a well known fact that none of the existing schemes has fully addressed the group management issues. We have proposed a novel mechanism known as Cluster Based Group Management Scheme for Wireless Sensor Networks. Cluster Based Group Management Scheme (CBGMS) adopts an intermediate path in between the known solutions and additional novel features. It is important to mention that CBGMS not only provide a comprehensive Group Management solution but also addresses some of the known inter-related issues of Wireless Sensor Networks which is presented and explained in this paper. [ABSTRACT FROM AUTHOR]

The emerging technologies such as the Internet-of-Things, sensors, communication networks, have been or will be introduced to conventional domotics to provide a wide variety of smart home services to facilitate the household appliances or home cares and improve the lifestyles of people. Currently, smart home system are integrated with different features from product line and equipped with various sensors and actuators to meet the requirements of house occupants by specifying their customised user policies. However, the introduction of features and policies may result in undesired behaviours, and this effect is known as feature interactions. In this study, the authors proposed a Semantic Web-based policy interaction detection method with rules to model smart home services and policies with the aids of ontological analysis in the smart home domain, so as to construct a semantic context for inferring the interaction of policies. The authors focus their work on user policies interaction, which are detected by using the Semantic Web rule language in semantic context. The approach is successfully applied to the smart home system and is able to detect 90 interactions among 32 user policies by automated reasoning with tools support as Protégé and Jess. [ABSTRACT FROM AUTHOR]

Abstract: A wireless sensor network is composed of a large number of sensor nodes that are densely deployed in a sensing environment. The effectiveness of the wireless sensor networks depends to a large extent on the coverage provided by the sensor deployment scheme. In this paper, we present a sensor deployment scheme based on glowworm swarm optimization (GSO) to enhance the coverage after an initial random deployment of the sensors. Each sensor node is considered as individual glowworms emitting a luminant substance called luciferin and the intensity of the luciferin is dependent on the distance between the sensor node and its neighboring sensors. A sensor node is attracted towards its neighbors having lower intensity of luciferin and decides to move towards one of them. In this way, the coverage of the sensing field is maximized as the sensor nodes tend to move towards the region having lower sensor density. Simulation results show that our GSO-based sensor deployment approach can provide high coverage with limited movement of the sensor nodes. [Copyright &y& Elsevier]

A wireless sensor network consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Different approaches have used for simulation and modeling of SN (Sensor Network) and WSN. Traditional approaches consist of various simulation tools based on different languages such as C, C++ and Java. In this paper, MATLAB (7.6) Simulink was used to build a complete WSN system. Simulation procedure includes building the hardware architecture of the transmitting nodes, modeling both the communication channel and the receiving master node architecture. Bluetooth was chosen to undertake the physical layer communication with respect to different channel parameters (i.e., Signal to Noise ratio, Attenuation and Interference). The simulation model was examined using different topologies under various conditions and numerous results were collected. This new simulation methodology proves the ability of the Simulink MATLAB to be a useful and flexible approach to study the effect of different physical layer parameters on the performance of wireless sensor networks [ABSTRACT FROM AUTHOR]

Currently, it is rapidly increasing convergence services based on various mobile devices with sensors like Smart Home. Specifically the mobility of the sensors in Smart Home merged with wireless sensor networks (WSN) brings security issues such as re-authentication and tracing the node movement. We extend our novel and efficient node authentication and key exchange protocol that support Irregular distribution. Compared with previous protocols, our protocol has only a third of communication and computational overhead. We expect our protocol to be the efficient solution that increases the lifetime of sensor network. [ABSTRACT FROM AUTHOR]

With the advancement of computer technologies to faster processors and more memory, the WorldWideWeb, wireless communication, and miniaturization of sensor technology, it is now possible to simulate and execute engineering and science laboratory projects on a remote computer. With Internet connection, students have access to "virtual laboratories" via the www, experiment-oriented problems can be now offered without the overhead incurred when maintaining a full laboratory. This paper investigates the opportunity that a new wireless sensor technology brings to remote laboratories. [ABSTRACT FROM AUTHOR]

Ineffective sensor node (InESN) in a wireless sensor network (WSN) is defined as one whose position cannot be estimated by traditional localisation methods. Incremental localisation method is investigated and the existence of the InESNs is confirmed. By analysing the existing characteristics, the InESNs are classified into three categories: InESNs connecting with one known node, InESNs connecting with two known nodes and InESNs standing alone. It is impossible to locate the InESNs of the third category because they cannot receive any information from the known nodes. With a moving target in the WSN, a constrained least-squares formulation is developed to estimate the InESNs of the first two categories. Numerical evaluations are carried out to examine the performance of the proposed method and show that it is indeed effective for locating the InESNs. By incorporating the InESNs in the tracking applications, the performance of the target tracking can be greatly enhanced. [ABSTRACT FROM AUTHOR]

A scheme for multitarget identification and localization using bistatic MIMO radar systems is proposed. Multitarget can be distinguished by Capon method, as well as the targets angles with respect to transmitter and receiver can be synthesized using the received signals. Thus, the locations of the multiple targets are obtained and spatial synchronization problem in traditional bistatic radars is avoided. The maximum number of targets that can be uniquely identified by proposed method is also analyzed. It is indicated that the product of the numbers of receive and transmit elements minus-one targets can be identified by exploiting the fluctuating of the radar cross section (RCS) of the targets. Cramer-Rao bounds (CRB) are derived to obtain more insights of this scheme. Simulation results demonstrate the performances of the proposed method using Swerling II target model in various scenarios. [ABSTRACT FROM AUTHOR]

An adaptive signal-processing-aided distributed source coding scheme for virtual multiple-input-multiple-output communication-based wireless sensor networks (WSNs) is proposed. A computationally inexpensive distributed compression scheme that exploits the spatiotemporal correlations of sensor data is implemented with the aid of a recursive least squares (RLS)-based adaptive correlation tracking algorithm. The tracked correlation is used to compute side information that assists in distributed source compression. The proposed virtual space-time block coding and RLS-based compression side information are shown to improve energy efficiency at distributed nodes compared to previously proposed schemes with single-input-single-output communication. A semi-analytical approach is developed for energy efficiency analysis over different channel conditions and transmission distances. The energy efficiency performance of the proposed design is evaluated on real WSN data. The results show that the proposed integrated system outperforms conventional designs beyond certain transmission distance thresholds and leads to lower decoding errors, which makes it a good candidate for energy-aware WSNs. [ABSTRACT FROM AUTHOR]

A new procedure for obtaining the equivalent currents on a plane surface from spherical near field measurements is proposed. It uses the modal expansion in spherical waves and the plane wave spectrum to achieve the objective. Some results using real measurements are shown. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 2043–2047, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22575 [ABSTRACT FROM AUTHOR]

We study the performance of differential orthogonal space-time block codes (OSTBC) over independent and semi-identically distributed block Rayleigh fading channels. In this semi-identical fading model, the channel gains from different transmit antennas to a common receive antenna are identically distributed, but the gains associated with different receive antennas are non-identically distributed. Arbitrary fluctuation rates of the fading processes from one transmission block to another are considered. We first derive the optimal symbol-by-symbol differential detector, and show that the conventional differential detector is suboptimal. We then derive expressions of exact bit-error probabilities (BEPs) for both the optimal and suboptimal detectors. The results are applicable for any number of receive antennas, and any number of transmit antennas for which OSTBCs exist. For two transmit antennas, explicit and closed-form BEP expressions are obtained. For an arbitrary number of transmit antennas, a Chernoff bound on the BEP for the optimal detector is also derived. Our results show that the semi-identical channel statistics degrade the error performance of differential OSTBC, compared with the identical case. Also, the proposed optimal detector substantially outperforms the conventional detector when the channel fluctuates rapidly. But in near-static fading channels, the two detectors have similar performances. [ABSTRACT FROM AUTHOR]

A wireless sensor network consists of many low-cost, low-power sensor nodes, which can perform sensing, simple computation, and transmission of sensed information. Long distance transmission by sensor nodes is not energy efficient since energy consumption is a superlinear function of the transmission distance. One approach to prolonging network lifetime while preserving network connectivity is to deploy a small number of costly, but more powerful, relay nodes whose main task is communication with other sensor or relay nodes. In this paper, we assume that sensor nodes have communication range r > 0, while relay nodes have communication range R ≥ r, and we study two versions of relay node placement problems. In the first version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting of relay and/or sensor nodes. In the second version, we want to deploy the minimum number of relay nodes so that, between each pair of sensor nodes, there is a connecting path consisting solely of relay nodes. We present a polynomial time 7-approximation algorithm for the first problem and a polynomial time (5 + ϵ)-approximation algorithm for the second problem, where ϵ > 0 can be any given constant. [ABSTRACT FROM AUTHOR]

This paper presents a framework that addresses Quality of Service (QoS) for industrial wireless sensor networks as a real-time measurable set of parameters within the context of feedback control, thereby facilitating QoS management. This framework is based on examining the interaction between the industrial control processes and the wireless network. Control theory is used to evaluate the impact of the control/communication interaction, providing a methodology for defining, measuring, and quantifying QoS requirements. An example is presented illustrating the wireless industrial sensor network (WISN) QoS management framework for providing dynamic QoS control within WISN. The example focuses on WISN operating in a time-varying RF interference environment in order to manage application-driven QoS latency constraints. [ABSTRACT FROM AUTHOR]

We study the problem of communicating sensor readings over a Gaussian multiaccess channel. We focus on the scenario that each sensor observes a single random variable and transmits it using certain signaling in a shared channel. The objective is the design of channel waveforms (i.e., the signal constellation) to facilitate the estimation of field parameters from the channel output. We propose a communication scheme in which sensors transmit according to the type of their observations—type-based multiple access (TBMA)—and show that the TBMA is asymptotically optimal in the limit of large number of sensors if the sensor channel-gains are identical. In particular, we show that TBMA together with a variant of the maximum-likelihood estimator achieves the Cramer-Rao bound asymptotically. We then extend the asymptotic analysis of TBMA to fading channels and compare the performance of TBMA with other orthogonal allocation methods such as time-division multiple access. [ABSTRACT FROM AUTHOR]

The communication capacity of Cooperative SEnsor Networks with Mobile Access (C-SENMA) is considered when some sensors may be misinformed with erroneous messages. It is assumed that a global message is first distributed to all the nodes, each node receiving the message correctly with probability 1 - β. The nodes cooperate in delivering the global message to the mobile access point. Three system configurations are discussed based on whether a polling channel and/or an energy constraint are present. The first type is C-SENMA with Polling with No Energy constraints (PNE), where the mobile access point has the ability to poll individual sensors. Without energy constraints, each sensor can transmit for an unlimited number of times. The second type is C-SENMA with No Polling with No Energy constraints (NPNE), where adaptive polling is not allowed and sensors have to transmit according to a predetermined schedule. The third type is C-SENMA with No Polling with an Energy constraint (NPE), where each node has a limit on the number of transmissions. The capacities of the three system configurations are analyzed. It is shown that, the capacity for C-SENMA PNE is the same as that when there are no misinformed sensors. For C-SENMA NPNE, with the absence of the polling channel, there is a loss on the achievable rate, proportional to β, the probability that a sensor is misinformed. Results are extended to multiple simultaneous transmissions with the presence of channel fading. The optimal number of simultaneous transmissions is investigated under three different fading situations. [ABSTRACT FROM AUTHOR]

Handling mobility in wireless sensor networks presents several new challenges. Techniques developed for other mobile networks, such as mobile phone or mobile adhoc networks can not be applicable, as in these networks energy is not a very critical resource. This paper presents a new adaptive Mobility-aware Sensor MAC protocol (MS-MAC) for mobile sensor applications. In MS-MAC protocol, a node detects its neighbor’s mobility based on a change in its received signal level from the neighbor, or a loss of connection with this neighbor after a timeout period. By propagating mobility presence information, and distance from the nearest border node, each node learns its relative distance from the nearest mobile node and from the nearest border node. Depending on the mobile node movement direction, the distances from mobile and border nodes, a node may trigger its neighbor search mechanism to quicken the connection setup time. The simulation results show that, the new mobility-aware MAC protocol can work very energy-efficiently when the network is stationary, whereas it performs much better in terms of throughput than the existing sensor MAC (SMAC) protocol in scenarios involving mobile sensors. [ABSTRACT FROM AUTHOR]

The conventional clustering method has the unique potential to be the framework for power-conserving ad hoc networks. In this environment, studies on energy-efficient strategies such as sleeping mode and redirection have been reported, and recently some have even been adopted by some standards like Bluetooth and IEEE 802.11. However, consider wireless sensor networks. The devices employed are power-limited in nature, introducing the conventional clustering approach to the sensor networks provides a unique challenge due to the fact that cluster-heads, which are communication centers by default, tend to be heavily utilized and thus drained of their battery power rapidly. In this paper, we introduce a re-clustering strategy and a redirection scheme for cluster-based wireless sensor networks in order to address the power-conserving issues in such networks, while maintaining the merits of a clustering approach. Based on a practical energy model, simulation results show that the improved clustering method can obtain a longer lifetime when compared with the conventional clustering method. [Copyright &y& Elsevier]

Energy is a critical resource in wireless sensor networks. In this paper, we propose a new approach to maintain network wide energy equivalence and maximize network lifetime. Compared to existing protocols, our approach emphasizes on route maintenance instead of route finding. This means no critical nodes would become the bottleneck of network lifetime. A reroute request packet is sent out from sinks periodically. When the packet reaches a path node, Common Neighbor Switching (CNS) algorithm checks energy difference between the node and its neighbors outside the routing tree. If the difference goes beyond a threshold, double neighbor switching is performed. Two path-rerouting algorithms, namely, Shortest Rerouting (EERS) and Longest Rerouting (EERL), are also presented to show that neighbor switching is better than path rerouting. Simulation results show that CNS outperforms Directed Diffusion in more than 90% cases, while EERS and EERL show only blurry and conditional advantage over directed diffusion. [Copyright &y& Elsevier]

Recent unexpected changes in the Antarctic Ice Sheet, including ice sheet thinning, ice shelf collapse and changes in ice velocities, along with the recent realization that as much as one third of ice shelf mass loss is due to bottom melt, place a new urgency on understanding the processes involved in these changes. Technological advances, including very new or forthcoming satellite-based (e.g. ICESat, CryoSat) remote sensing missions, will improve our ability to make meaningful determinations of changes in Antarctic Ice Sheet mass balance.This paper is the result of a workshop held to develop a strategy for international collaboration aimed at the collection and synthesis of Antarctic Ice Sheet mass balance data, and at understanding the processes involved so that we might predict future change. Nine sets of recommendations are made, concerning the most important and sensitive measurements, temporal ranges and study areas. A final tenth recommendation calls for increased synthesis of ice sheet data and communication between the field measurement, satellite observation and modelling communities. [Copyright &y& Elsevier]

Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detection in large inverse linear problems, e.g., massive MIMO systems. The main motivation behind is that the complexity of Maximum A-Posteriori (MAP) detection grows exponentially with system dimensions. Instead of using DNNs, essentially being a black-box, we take a slightly different approach and introduce a probabilistic Continuous relaxation of disCrete variables to MAP detection. Enabling close approximation and continuous optimization, we derive an iterative detection algorithm: Concrete MAP Detection (CMD). Furthermore, extending CMD by the idea of deep unfolding into CMDNet, we allow for (online) optimization of a small number of parameters to different working points while limiting complexity. In contrast to recent DNN-based approaches, we select the optimization criterion and output of CMDNet based on information theory and are thus able to learn approximate probabilities of the individual optimal detector. This is crucial for soft decoding in today’s communication systems. Numerical simulation results in MIMO systems reveal CMDNet to feature a promising accuracy complexity trade-off compared to State of the Art. Notably, we demonstrate CMDNet’s soft outputs to be reliable for decoders. [ABSTRACT FROM AUTHOR]

Free-space optical (FSO) communications will play an important role in the backhaul of future generation of wireless networks in order to support high data rates. Because of narrow beamwidth inherent to an optical signal, acquisition and tracking form an important component of any FSO communication system. In this study, we have analyzed the optimization of received power allocation between tracking and data channels in an FSO receiver. In this regard, we have carried out a detailed analysis of the error statistics of the centroid estimator that is used for tracking the beam with the help of an array. The objective function that is optimized (minimized) are the probability of error and the probability of outage, and the optimization of power allocation is carried out as a function of parameters such as noise power, pointing error variance, pointing error correlation coefficient, and the threshold of outage. We have analyzed the optimization concerning the lognormal and exponentiated Weibull fading scenarios as well. We learn that the optimal power allocation is a function of the received signal-to-noise ratio: a lower signal-to-noise ratio dictates that a higher fraction of received power should be diverted to the tracking channel and vice versa. [ABSTRACT FROM AUTHOR]

Proposes a one-shot linear decorrelating detector with pre-selection diversity combining and post-maximal ratio combining for random code division multiple access. System description; Performance analysis; Computer simulations and mathematical results.

Proposes an iterative multiuser detectors for asynchronous code-division multiple-access (CDMA) with parallel and serially concatenated convolutional codes. Structures of iterative multiuser detectors for turbo-coded CDMA; Development of reduced-complexity techniques for detection; Background on multiuser detectors.