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Some passive sensors can provide only relative angles of a signal source. To obtain the signal source location, multiple passive sensors can be constructed into a passive sensor network through communication links. This paper investigates the source localization problem with angle-only measurements in three-dimensional space. First, we present an intersection localization method, which estimates the target position by minimizing the sum of distances between lines formed by angle-only measurements. It has the same target position estimate as the widely used least-squares (LS) method, but with a lower computational cost. Furthermore, considering the differences in measurement accuracy of sensors, the weighted least-squares (WLS) algorithm can achieve better localization performance than the LS method. Unfortunately, since the coefficient matrix and the noise vector are correlated, the WLS method is biased. The bias-compensation WLS (BCWLS) method is also presented in this paper to reduce the bias by estimating the correlation between the coefficient matrix and the pseudolinear noise vector. To evaluate the performance of the presented algorithms, numerical simulations are conducted, indicating that the superiority of the intersection localization method in computational cost and the superiority of the BCWLS method in localization accuracy. [ABSTRACT FROM AUTHOR]

Network security technology is capable of mitigating attack signals launched by malicious attackers, thereby safeguarding and bolstering system security. Secure state estimation is a type of network defense technology that involves reconstructing the system state by measuring potential attacks. The relevant research has also been expanded to distributed systems to enable collaborative secure state estimation among different agents facing homogeneous attacks; however, such research significantly enhance the communication load of the system. On the other hand, if the homogeneous attack is non-existent or consistent, excessive network communication is definitely inefficient. An event-triggered approach is a potent technique that can alleviate communication overhead while having minimal impact on system performance. This paper proposes a mechanism for event-triggered transmission in the context of distributed secure state estimation. While communication latency and data transmission disorder may be present within the communication network, the estimation error of the proposed observer is constrained and bounded. The simulation results indicate that for stable malicious attack signals, system communication can be divided into high-frequency and low-frequency communication periods. The simulation results also shows that the maximum estimation error is proportional to the trigger threshold, allowing the observer's performance to be finely tuned to the required precision. • In this paper, the observer presented implements an event-triggered communication strategy, which effectively decreases the frequency of data transmission and reduces the communication load on the network. • Network latency and data disorder are also taken into consideration. • The maximum estimation error is proportional to the trigger threshold, allowing the observer's performance to be finely tuned to the required precision. [ABSTRACT FROM AUTHOR]

Connected and automated vehicles (CAVs), integrated with sensors, cameras, and communication networks, are transforming the transportation industry and providing new opportunities for consumers to enjoy personalized and seamless experiences. The fast proliferation of connected vehicles on the road and the growing trend of autonomous driving create vast amounts of data that need to be analyzed in real time. Anomaly detection in CAVs refers to identifying any unusual or unforeseen behavior in the data generated by vehicles' various sensors and components. Anomaly detection aims to identify any unusual behavior that might indicate a problem or a malfunction in the vehicle. To identify and detect anomalies efficiently, a method must deal with noisy data, missing data, dynamic frequency data, and low- and high-magnitude data, and it must be accurate enough to detect anomalies in a dynamic sensor streaming environment. Therefore, this paper proposes a fast and efficient hard-voting-based technique named FT-HV, comprising three fine-tuned machine learning algorithms to detect and classify anomaly behavior in CAVs for single and mixed sensory datasets. In experiments, we evaluate our approach on the benchmark Sensor Anomaly dataset that contains data from various vehicle sensors at low and high magnitudes. Further, it contains single and mixed anomaly types that are challenging to detect and identify. The results reveal that the proposed approach outperforms existing solutions for detecting single anomaly types at low magnitudes and detecting mixed anomaly types in all settings. Furthermore, this research is envisioned to help detect and identify anomalies early and efficiently promote safer and more resilient CAVs. [ABSTRACT FROM AUTHOR]

This paper considers model-based fault detection of large-scale (possibly rank-deficient) dynamic systems. Assuming only global (and not local) observability over a sensor network, we introduce a single time-scale networked estimator/observer. Sensors take local outputs/measurements of system states with partial observability and share their information (including estimation and/or output) over a communication network, and gain distributed observability. We define the conditions on the network structure ensuring distributed observability and stabilising the error dynamics. However, system outputs are prone to faults and uncertainties, which affect the state estimation of all sensors as a consequence of communicating (possibly) faulty data. From the cyber-physical-systems (CPS) perspective, such faults add bias to the data transferred from the physical layer (dynamic system) to the cyber layer (sensor network). In this work, we propose a localised fault detection and isolation (FDI) mechanism at sensors to secure distributed estimation. This protocol enables every sensor to locally identify the possible fault at the sensor measurement, and, via local detection and isolation, to prevent the spread of biased/faulty information over the network. This distributed isolation and localisation of fault follows from our partial observability assumption instead of full observability at every sensor. Then, other sensors can estimate/track the system by using observationally-equivalent output information to recover for possible loss of observability. In particular, we study rank-deficient systems as they are known to demand more information-sharing, and thus, are more vulnerable to the spread of possible faults over the network. One challenge is the detection of faults in the presence of system/output noise without making (simplifying and unrealistic) upper-bound assumptions on the noise support. We resolve this by adopting probabilistic threshold designs on the residuals. Further, we show that additive faults at rank-deficiency-related outputs affect the residuals at all sensors, a consequence that mandates more constraints on the (distributed) FDI strategy. We address this problem by constrained LMI design of the feedback gain matrix. Finally, we design q-redundant distributed estimators, resilient to isolation/removal of up to q number of faulty sensors, and further, we consider thresholding residual history over a sliding time-window, known as the stateful FDI. [ABSTRACT FROM AUTHOR]

In this paper, the set-membership filtering problem is investigated for a class of polytopic uncertain two-dimensional shift-varying systems with delays and sensor saturation. The measurement information is transmitted between the sensors and the filter through a shared communication network. To avoid data congestions, the Round-Robin (R-R) protocol is employed to regulate the data transmission order. This paper aims to design a robust set-membership filter such that the real system states are always contained in the state estimate ellipsoid in the presence of the state delays, the sensor saturation, the parameter uncertainties, the R-R protocol and the unknown-but-bounded external perturbations. By using the mathematical induction, sufficient condition for the existence of the desired robust set-membership filter is given in the form of recursive linear matrix inequalities, and a convex optimisation method is also proposed to determine the optimal state estimation ellipsoid in the trace sense. One numerical example is also given to illustrate effectiveness of the proposed filtering strategy. [ABSTRACT FROM AUTHOR]

In this paper, passive wireless sensor network technology is used to conduct in-depth research and analysis on the monitoring of the in-transit health status of railway transportation. Safety detection sensors, train communication networks, and other onboard devices organically constitute a train sensor network with comprehensive state sensing, information aggregation, and business collaboration. First, this paper analyzes the three-layer architecture of the sensing layer, network layer, and application layer of the train operation status safety detection sensor network. Based on analyzing the feasibility of Ethernet application in an onboard communication network, ring, multiring, and ladder-type sensor network structure schemes are designed. Next, the real-time performance and reliability of various sensor network structures are analyzed. First, the characteristics of bandwidth demand, priority, and importance of information transmission of each monitoring object are analyzed; then, the system utility function is established according to the bandwidth usage efficiency and communication demand of information transmission of each monitoring object; finally, the bandwidth allocation optimization model is solved by using a particle swarm optimization algorithm, and the remaining bandwidth resources are dynamically rationed on demand while ensuring the complete transmission of basic information of each monitoring object. Rail transit technology has profoundly affected and changed the travel and lifestyle of residents in the new era and will provide strong infrastructure support for the smooth advancement of new urbanization construction and development strategies. The remaining bandwidth resources are dynamically allocated on the premise of ensuring the complete transmission of basic information of each monitoring object. In summary, this paper presents a complete study on the optimal allocation of resources for wireless sensor networks dedicated to rail transit condition monitoring, starting from the perspectives of routing protocol optimization, data fusion rate optimization, and bandwidth dynamic allocation optimization to achieve the efficient use of limited resources. The achieved research results enrich the research content in the field of wireless monitoring of rail transit system conditions at home and abroad in a certain sense and will also provide theoretical and empirical support for practical practitioners, managers, and scholars of service condition monitoring of rail transit systems. [ABSTRACT FROM AUTHOR]

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• Two-channel stochastic network attacks for discrete-time nonlinear switched systems on sensor networks are introduced. These attacks are detected in both the communication channel between the model and the sensor and among the sensors themselves. The attacks are modeled using an independent Bernoulli process with uncertain probabilities. • To address the distributed filter design problem for switched systems on sensor networks, the paper proposes a novel event-triggered communication mechanism. This mechanism involves a combination of switching signals and sensor nodes, enabling efficient communication and filtering. • The various asynchronous modes that can arise between the target switched systems and the switched distributed filter on each sensor node, considering the impact of different event-triggered communication mechanism, are taken into account. To capture these asynchronous modes, a compressed filtering error system is constructed, incorporating all switching signals on the sensor networks. A piecewise vector modal function is developed to represent the synchronous and asynchronous modes between the distributed filter and switched systems on all sensor nodes. • Some novel sufficient conditions in the presence of asynchronous modes, twochannel network attacks, and the event-triggered communication mechanism are established. These conditions ensure that the filtering error system is finite-time bounded and satisfies the H ∞ performance index. This paper addresses the problem of distributed event-triggered finite-time H ∞ filtering for switched systems on sensor networks, subject to two-channel network attacks and asynchronous modes. To tackle the issue posed by the switched event-triggered communication mechanism and network attacks, a distributed filter with switching signal is introduced. Additionally, considering the mismatched behavior between switched systems and distributed filters caused by the event-triggered communication mechanism and network attacks, a piecewise vector modal function which considers all switching conditions is proposed for handling the problem of the sensor network's filtering error system containing multiple switching signals. By utilizing the multiple Lyapunov functional method and the average dwell time switching mechanism, sufficient conditions are derived to guarantee that the filtering error system with synchronous and asynchronous modes is both finite-time bounded and satisfies the H ∞ performance index. Finally, an example is presented to demonstrate the validity of the results. [ABSTRACT FROM AUTHOR]

This paper deals with the practical aspects of development of multisatellite communication system. Specifically, the problem of data detection in multisatellite communication system is discussed in this paper. All satellites want to communicate to a particular earth station (ES). A novel interference cancellation method is used to obtain the data of different satellites at the ES. Based on the standard moment generating function approach, the proposed system is evaluated by analyzing the symbol error rate, diversity order, and average capacity. It is shown through simulation and analysis that the number of antennas at the ES should be sufficiently large as compared to the number of satellites in order to achieve good performance and improved diversity gain and average capacity. It is also shown that the diversity order of the considered system does not depend upon the shadowing environment. By placing more antennas at the ES, the effect of channel (shadowing) can be compensated. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) is a promising technology for communication systems. This paper investigates the impacts of unknown noise variance on the popular spectrum sensing scheme, i.e., energy detection, for OFDM cognitive radios over multipath fading channels. To study the effects of unknown parameters on the energy detector, a new maximum-likelihood estimation of noise and signal powers employing the cyclic prefix of OFDM is presented in this paper. The mean values and Cram $\acute{\text{e}}$ r–Rao lower bounds of the estimation are obtained. Furthermore, the performances of the energy detector for both hypotheses, i.e., false-alarm rate and detection probability, under the influence of unknown noise variance are validated by both simulation and analytical results. The assessment on the required number of samples for the proposed energy detector is conducted, which indicates that an amount of 40–50% samples can be saved compared to the conventional energy detector. [ABSTRACT FROM AUTHOR]

The internet of vehicles needs mobile communication systems for efficient communications. On the physical downlink control channel (PDCCH) of 5G, blind detection is performed to identify the downlink control information (DCI). Due to the uncertainty of DCI formats and PDCCH formats, the existing two-stage blind detection schemes separately decode every PDCCH code block under different DCI formats, leading to a high decoding complexity in the first stage. To reduce the detection complexity, this paper proposes an efficient DCI detection method, where a significance-test strategy is designed to detect the DCI formats. The significance-test strategy can forecast the DCI lengths without separately decoding the whole codeword, thus reducing the decoding complexity by several times. Moreover, the accuracy of the DCI detection is analyzed, with which the test scope of the test statistic is optimized for minimizing the decoding complexity on condition of meeting the detection accuracy requirements. Simulation results show that the proposed method significantly reduces the decoding complexity relatively to the existing two-stage detection schemes. [ABSTRACT FROM AUTHOR]

There has been a recent surge in interest for optical satellite communication (SatCom) utilizing lasers. It is clear to see why, as optical SatCom is capable of higher speed, lighter weight, higher directionality, and higher efficiency versus their radio-based counterparts. Research into optical SatCom has focused on devices operating in the short-wave infrared (SWIR), which is due to the maturity and commercial availability of such component’s thanks to significant development in terrestrial telecommunications networks. However, SWIR performs poorly in fog and heavy weather, prompting investigations into longer mid-wave and long-wave infrared bands for optical communication instead due to reduced atmospheric losses. This paper provides a comprehensive review of laser transmitters, detectors, and the science behind selecting longer wavelengths for optical SatCom to boost optical SatCom between ground stations and low earth orbit satellite constellations being deployed. [ABSTRACT FROM AUTHOR]

This paper studies the temporal characteristics of the intelligent reflecting surface (IRS)-based visible light communication (VLC) channel using radiometric concepts. Throughout this study, we account for the delays experienced by the transmitted power along the continuum of paths originating at the source, passing through the IRS, reaching the detector. Then, we derive the impulse response of multi-element phase-tunable metasurface and orientation-tunable mirror array-based reflector setups for a general setting of source, reflector, and detector dimensions and relative positions. In addition, we derive simpler expressions for the two special cases, namely, the point source and the large-source small-reflector. Moreover, we present the exact expression for the delay spread and derive lower, upper bounds and asymptotic expressions when the number of reflecting elements increases for both reflector types. Finally, we study the impact of several system parameters on the temporal characterization of the two IRS-based VLC systems. [ABSTRACT FROM AUTHOR]

Many applications of wireless sensor networks (WSNs) require deploying sensors in hostile environments, where an adversary may eavesdrop communications. To secure communications in WSNs, the $q$ -composite key predistribution scheme has been proposed in the literature. In this paper, we investigate secure $k$ -connectivity in WSNs operating under the $q$ -composite scheme, in consideration of the unreliability of wireless links. Secure $k$ -connectivity ensures that any two sensors can find a path in between for secure communication, even when $k-1$ sensors fail. We present conditions on how to set the network parameters such that the network has secure $k$ -connectivity asymptotically almost surely. The result is given in the form of a sharp zero–one law. [ABSTRACT FROM AUTHOR]

This paper is concerned with the protocol-based fault detection (FD) issue for state-saturated delayed nonlinear systems with both redundant channels and sensor nonlinearities. Specifically, in pursuit of relieving the communication pressure, the stochastic communication protocol is adopted, which can regulate the transmission of output signal during the communication process. Moreover, for the purpose of decreasing the negative impact of one channel failure on network communication and enhancing data reliability, the redundant channels transmission is introduced. Then, the protocol-based FD filter is constructed such that the resultant FD dynamics system attains the global asymptotic stability in mean-square sense and satisfies the H ∞ performance index. Moreover, an implement-to-easy algorithm is developed to facilitate the solvability of the desirable FD filtering method. In the end, two illustrative examples are utilized to demonstrate the validity of the developed FD filtering algorithm. • The stochastic communication protocol is adopted to regulate the network communication. • The redundant channels transmission mechanism is introduced into the signal communication process. • New sufficient criteria are derived to assure the existence of desirable FD filtering scheme for state-saturated systems. [ABSTRACT FROM AUTHOR]

This paper presents a cooperative, combinatorial search model for a multi-mobile sensor, multi-mobile target scenario in a two dimensional grid space. In the proposed model, sensors and targets act as searchers and hiders of a search game. A search game is a game between searcher and hider, modeled on a graph. In this paper, the identified problem states that multiple targets enter into a grid from the same or different sides and try to exit on the opposite directions of their respective entry sides. Alternatively, multiple mobile sensors are randomly deployed in the grid and try to maximize the number of target searched and to minimize search time before the targets leave the grid. This problem fits into several real life scenarios such as international border security, terrorist searching in a specified area, finding spies etc. The novelty of the proposed model is interpreting the problem as a search game and formulating strategies for the mobile sensors to optimize their moves to maximize the number of target searched and minimize search time. In this paper, shortest path and random walk strategies for the targets are analyzed by applying suitable mathematical models and on the other hand, advantages of cooperative over non-cooperative strategies for the mobile sensors are also shown with the help of analytical methods and simulation results. The significant mathematical concepts applied in the proposed model are as follows-computing shortest path, random walk, Markov chain, probability graph, overlapping of multiple probability graphs, cooperative and non-cooperative strategies etc. [ABSTRACT FROM AUTHOR]

In this paper, we extend the bilinear generalized approximate message passing (BiG-AMP) approach, originally proposed for high-dimensional generalized bilinear regression, to the multi-layer case for the handling of cascaded problem such as matrix-factorization problem arising in relay communication among others. Assuming statistically independent matrix entries with known priors, the new algorithm called ML-BiGAMP could approximate the general sum-product loopy belief propagation (LBP) in the high-dimensional limit enjoying a substantial reduction in computational complexity. We demonstrate that, in large system limit, the asymptotic MSE performance of ML-BiGAMP could be fully characterized via a set of simple one-dimensional equations termed state evolution (SE). We establish that the asymptotic MSE predicted by ML-BiGAMP’ SE matches perfectly the exact MMSE predicted by the replica method, which is well-known to be Bayes-optimal but infeasible in practice. This consistency indicates that the ML-BiGAMP may still retain the same Bayes-optimal performance as the MMSE estimator in high-dimensional applications, although ML-BiGAMP's computational burden is far lower. As an illustrative example of the general ML-BiGAMP, we provide a detector design that could estimate the channel fading and the data symbols jointly with high precision for the two-hop amplify-and-forward relay communication systems. [ABSTRACT FROM AUTHOR]

Industry 4.0 focuses on continuous interconnection services, allowing for the continuous and uninterrupted exchange of signals or information between related parties. The application of messaging protocols for transferring data to remote locations must meet specific specifications such as asynchronous communication, compact messaging, operating in conditions of unstable connection of the transmission line of data, limited network bandwidth operation, support multilevel Quality of Service (QoS), and easy integration of new devices. The Message Queue Telemetry Transport (MQTT) protocol is used in software applications that require asynchronous communication. It is a light and simplified protocol based on publish-subscribe messaging and is placed functionally over the TCP/IP protocol. It is designed to minimize the required communication bandwidth and system requirements increasing reliability and probability of successful message transmission, making it ideal for use in Machine-to-Machine (M2M) communication or networks where bandwidth is limited, delays are long, coverage is not reliable, and energy consumption should be as low as possible. Despite the fact that the advantage that MQTT offers its way of operating does not provide a serious level of security in how to achieve its interconnection, as it does not require protocol dependence on one intermediate third entity, the interface is dependent on each application. This paper presents an innovative real-time anomaly detection system to detect MQTT-based attacks in cyber-physical systems. This is an online-semisupervised learning neural system based on a small number of sampled patterns that identify crowd anomalies in the MQTT protocol related to specialized attacks to undermine cyber-physical systems. [ABSTRACT FROM AUTHOR]

In this paper, we consider non-coherent detection schemes for molecular communication systems in the presence of inter-symbol-interference. In particular, we study non-coherent detectors based on memory-bits-based thresholds in order to achieve low bit-error-ratio (BER) transmission. The main challenge of realizing detectors based on memory-bits-based thresholds is to obtain the channel state information based only on the received signals. We tackle this issue by reformulating the thresholds through intermediate variables, which can be obtained by clustering multi-dimensional data from the received signals, and by using the K-means clustering algorithm. In addition to estimating the thresholds, we show that the transmitted bits can be retrieved from the clustered data. To reduce clustering errors, we propose iterative clustering methods from one-dimensional to multi-dimensional data, which are shown to reduce the BER. Simulation results are presented to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Ambient backscatter communication (AmBC), a promising solution to future Internet of Things (IoT), has attracted increasing attention from both academia and industry in recent years. AmBC systems enable communications between RF-powered devices (e.g., tags and sensors) and AmBC receivers by utilizing ambient RF source signals from existing communication systems. Thus it offers a low-cost and energy-efficient means of communications for future IoT applications. In the current AmBC research, the impact of using channel coding on existing primary networks in terms of the bit-error-rate (BER) performance of the AmBC systems are mostly ignored. Low-density parity-check (LDPC) codes that offer fast encoding and decoding process have been proposed as promising channel codes in the fifth-generation (5 G) networks. In this paper, we investigate the BER performance of an AmBC system that uses LDPC-coded RF source signals. We have analytically derived the BER upper and lower bounds of both the RF source and tag signals for our proposed AmBC system. Simulation results show that the BERs of both signals decrease significantly, compared to conventional AmBC systems with uncoded RF source signals. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) has become an addition of humans. IoT assists in the security work to increase the quality of people life. This paper presents an intruder alert system using IoT-sensing through cloud service network. The proposed intruder alert system is divided into 4 sections, which are (1) intruder monitoring section, (2) communication network, (3) data processing unit and (4) user interface. Each composition works according to its function effectively. The intruder monitoring device was contained Ultrasonic and Passive Infrared (PIR) Sensors to analyze its performance. NETPIE work as graphic user interface (GUI) on cloud server was serviced to act as an intermediary to distribute information to other devices through internet network. Both sensors were evaluated the detection sensing test according to various distances. The obtained results based on individual test were analyzed in terms of percentage form, which showed that the Ultrasonic and PIR sensors show its different responses. The Ultrasonic stables in the distance test of 5–55 cm and after 55 cm distance it reacts unstable for detection. While, the PIR sensor swings in the distance of 5–30 cm and more stable after distance of 35 to 100 cm. Accordance the graph visually, it was found that the both sensors work in the opposite way. Therefore, the results of the experiment were again analyzed by statistical program. The finding presented that the Ultrasonic and PIR sensors accurately detected intruder at 99.94% and 99.56% respectively, with at statistically significant level of 95%. [ABSTRACT FROM AUTHOR]

In this paper, we address a multiple-input multiple-output (MIMO) communication system based on generalized spatial modulation (GSM) and dual-polarized (DP) antennas in sub-TeraHertz (sub-THz) bands to improve the Spectral Efficiency (SE) while reducing the spatial correlation effect and the space occupancy. Moreover, the joint Maximum Likelihood (ML) detector and a Modified Ordered Block Minimum Mean-Squared Error (MOB-MMSE) detector algorithm are proposed to detect jointly the complex symbols and the virtual bits conveyed by the activated polarization and the transmit antenna combination index. MOB-MMSE can achieve near-ML performance with low complexity. The performance of DP-GSM system over correlated Rayleigh/Rician fading and indoor sub-THz channels is studied. Provided results show that DP-GSM system is robust to the spatial correlation effects under Rician fading channel. In addition, an average bit-error probability (ABEP) upper bounding is derived and analyzed for the DP-GSM system over correlated Rayleigh/Rician fading channels. Since the sub-THz band suffers from many technological limitations and severe RF-impairments such as low transmit output power and important phase noise (PN), the DP-GSM system is studied by considering the sub-THz impairments. Moreover, the Dual Polarized Spatial Multiplexing (DP-SMX) and the Uni-Polarized GSM (UP-GSM) are compared with the DP-GSM system. The results reveal that DP-GSM with low order modulation schemes as QPSK outperforms the UP-GSM. Besides, DP-GSM and DP-SMX provide a good performance up to medium PN, which is interesting for sub-THz bands, but DP-GSM can reduce the transceiver cost by using a lower number of RF chains when the used transmitter architecture is based on RF-switching. [ABSTRACT FROM AUTHOR]

In modern distributed cyber-physical systems (CPS), information fusion often plays a key role in automate and self-adaptive decision making process. However, given the heterogeneous and distributed nature of modern CPSs, it is a great challenge to operate CPSs with the compromised data integrity and unreliable communication links. In this paper, we study the distributed state estimation problem under the false data injection attack (FDIA) with probabilistic communication networks. We propose an integrated ”detection + fusion” solution, which is based on the Kullback-Leibler divergences (KLD) between local posteriors and therefore does not require the exchange of raw sensor data. For the FDIA detection step, the KLDs are used to cluster nodes in the probability space and to partition the space into secure and insecure subspaces. By approximating the distribution of the KLDs with a general χ2 distribution and calculating its tail probability, we provide an analysis of the detection error rate. For the information fusion step, we discuss the potential risk of double counting the shared prior information in the KLD-based consensus formulation method. We show that if the local posteriors are updated from the shared prior, the increased number of neighbouring nodes will lead to the diminished information gain. To overcome this problem, we propose a near-optimal distributed information fusion solution with properly weighted prior and data likelihood. Finally, we present simulation results for the integrated solution. We discuss the impact of network connectivity on the empirical detection error rate and the accuracy of state estimation. [ABSTRACT FROM AUTHOR]

Viterbi detectors are widely used in all communication systems dealing with transmission and storage. In this paper, we develop the theory and design architecture for a 2-D separable iterative soft-output Viterbi detector (SISOVD) for applications in 2-D storage channels extending the original work from Wu et al. (IEEE Trans. Magn., vol. 39, no. 4, pp. 2115–2120, Jul. 2003). The contribution of this paper is twofold. First, we design a non-binary soft Viterbi detector that will be used as the core engine for the SISOVD and show its equivalence to the max-log-MAP algorithm implementation. We also study the performance of the algorithm through simulations under various design parameter constraints toward a systems architecture. Second, we propose a novel digital circuit that incorporates non-uniform quantization within a sliding block design framework. The proposed detector system architecture is tested within an field programmable gate array platform and proved to be efficient in terms of resource utilization, timing, and power compared with a conventional uniform quantizer with no signal-to-noise ratio performance degradation. It shows a 13.28% reduction in the total number of slice registers, 30.26% reduction in the slice lookup tables, 21.23% reduction in the critical path delay, and 14.84% reduction in the power consumption compared with the uniform quantizer. [ABSTRACT FROM AUTHOR]

In this paper, we propose a generalized space-time block coded spatial modulation (GSTBC-SM) scheme for open-loop massive multiple-input and multiple-output (MIMO) downlink communication systems. Specifically, we firstly partition the information bits into multiple groups with each group modulated by the spatial modulation (SM), where the SM symbols are invoked for orthogonal STBC (OSTBC) and quasi-orthogonal STBC (Q-OSTBC) structures. Then, message passing (MP) and block minimum mean square equalization (B-MMSE) detectors are designed for our GSTBC-SM systems, to achieve near-optimal performance with significantly reduced complexity in massive MIMO configurations. Finally, we derive the theoretical average bit error probability (ABEP) of the proposed scheme. The main contribution is that the propose scheme achieves high transmission rate and diversity gain even with small number of radio frequency (RF) chains at the transmitter. Simulation results verify the theoretical derivations and show that the proposed GSTBC-SM scheme provides near 20 dB gain over the conventional GSTBC scheme under massive MIMO configurations. [ABSTRACT FROM AUTHOR]

In the era of the fifth generation (5G) communication networks, massive multiple-input multiple-output (MIMO) systems demand even lower computation complexity and power consumption while catching up with good detection performance. In this paper, a low-complexity nonlinear detection algorithm is proposed for massive MIMO systems, which is based on partial tree search and successive interference cancellation (SIC). The proposed scheme allows us to expedite the detection process by coping with the transmit symbols group by group. As compared to vertical-Bell laboratories layered space time (V-BLAST), the major breakthrough of computation reduction lies in the fact that the partial tree search can assist the detection process to avoid the inversion of the detection matrix required in each recursion of the SIC process. Both computational complexity analysis and simulation results show that our proposed algorithm not only significantly reduces computational complexity, but also has better bit error rate (BER) performance. [ABSTRACT FROM AUTHOR]

In this paper, a fault diagnosis (FD) and fault tolerant control (FTC) scheme is proposed for the leader–follower based multiple manipulator system with sensor fault under network communication topology. The learning observer is designed to obtain the fault information when the time-varying sensor fault occurs in follower manipulators. The synchronization error between the leader manipulator and the follower manipulator is defined based on the graph theory. The distributed multiple manipulator synchronization controller is designed for each follower manipulator which contains the value of fault estimation and RBF neural network based approximator. Correspondingly, the stability analysis of the error system is analyzed by the Lyapunov stability theorem. Finally, a simulation example is given to prove the effectiveness of the algorithm. • The learning observer is designed to obtain the sensor fault information. • The manipulator synchronization FTC scheme is designed for the follower manipulator. • The FTC controller can reduce the impact of the sensor fault. [ABSTRACT FROM AUTHOR]

Vehicular networks are vulnerable to various attacks such as Sybil, denial-of-service (DoS) and false alert generation attacks. Cryptographic methods can provide some protection to vehicular networks from external attacks but are found to be vulnerable to internal attacks. A misbehavior detection system (MDS) can be deployed to detect and prevent internal attacks. In this paper, we propose a machine learning and reputation based MDS to enhance the detection accuracy as well as to ensure the reliability of both vehicles and messages. Proposed MDS is trained using datasets generated through extensive simulation based on the realistic vehicular network environment. To improve the accuracy of the detection, we have employed the Dempster-Shafer (DS) theory-based collaborative misbehavior detection system. In the proposed scheme, the reputation score of each vehicle is used as a belief value for Dempster-Shafer based feedback combination. In addition, we propose a beta distribution based reputation update and revocation scheme. Moreover, we show that our proposed scheme is better compared to previous methods in terms of accurately identifying various misbehaviors. [ABSTRACT FROM AUTHOR]

In this paper, we propose a detector, based on the compressive sensing (CS) principles, for multiple-access spatial modulation (SM) channels with a large-scale antenna base station (BS). Particularly, we exploit the use of a large number of antennas at the BSs and the structure and sparsity of the SM transmitted signals to improve the performance of conventional detection algorithms. Based on the above, we design a CS-based detector that allows the reduction of the signal processing load at the BSs particularly pronounced for SM in large-scale multiple-input–multiple-output (MIMO) systems. We further carry out analytical performance and complexity studies of the proposed scheme to evaluate its usefulness. The theoretical and simulation results presented in this paper show that the proposed strategy constitutes a low-complexity alternative to significantly improve the system's energy efficiency against conventional MIMO detection in the multiple-access channel. [ABSTRACT FROM AUTHOR]

Today, due to the impossibility of further reducing the dimensions, electronic devices are faced with fundamental challenges in parameters such as speed, frequency, and power consumption for CMOS technology circuit. One solution is to replace CMOS technology with other technologies such as Quantum-dot Cellular Automata (QCA) technology. Extensive researches have been done for design digital circuits in QCA technology. Phase-frequency detector (PFD) is one of the main blocks in electrical and communication systems. In this paper, a structure is presented for a PFD in QCA technology for the first time. In the proposed structure, a D flip-flop (D-FF) with reset ability based on a new inverter gate is used. The new inverter gate of this D-FF compared to previous inverters, has output signal with high polarization level. Also, the proposed PFD has 199 cells, 0.22 μm2 occupied area and two clock cycles latency that is smaller compared with PFD which is designed with the conventional inverter. [ABSTRACT FROM AUTHOR]

Faster-than-Nyquist signaling (FTNS) is capable of improving the spectral efficiency (SE) of communication systems. However, for conventional single-carrier FTNS (SC-FTNS) in which only symbol interval is reduced, the increase of SE is very limited due to the presence of inter-symbol interference (ISI) introduced by the FTNS. To deal with this problem, this paper proposes a new time-frequency compressed SC-FTNS (TFC-SC-FTNS) scheme that includes the conventional FTNS as a special case, to improve the SE via two dimensions simultaneously: time dimension by stacking symbols closer; frequency dimension by precoding to make the FTN signal spectrum more compact. Further, an optimization subject to a spectral mask constraint is performed on the precoder to suppress the ISI, according to a mean-square-error criterion, but the optimization problem is non-convex. A nontrivial contribution in the new scheme is that the non-convex problem is transformed into a convex one by a change of variable and an addition of admissibility constraint. Simulation results demonstrate that the proposed scheme significantly outperforms the conventional FTNS in terms of achievable SE or, equivalently, reception performance at a given SE. Further, with larger constellations applied, the gains of the TFC-FTNS increase. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the design, testing, and validation of a ultra‐wideband (UWB) wireless solution to replace wired intra‐spacecraft communications with wireless communications. The system requirements are provided in the framework of the Eu:CROPIS mission and the wired intra‐spacecraft communication system is replaced with a two‐segment wireless network. As such, distinct sets of UWB gateways and nodes are prototyped to interface with the on‐board entities and properly handle the data transmission in the resulting spacecraft and payload wireless networks. To accomplish these tasks, a custom radio module integrated into the prototypes was designed to provide the appropriate UWB RF front‐end and run a custom‐built communication stack. The viability of the solution was tested in laboratory conditions. For the test scenarios, sensor data are acquired in the payload network and forwarded as SpaceWire packets over the spacecraft network. Experimental test results indicate the suitability of the proposed solution in terms of delay and data integrity for implementing intra‐spacecraft wireless communications. [ABSTRACT FROM AUTHOR]

This paper investigates the symbol detection of the multiple antenna ambient backscatter communication systems. In particular, to overcome the problem of the noise uncertainty, the maximum-eigenvalue detector is derived from the general likelihood ratio test, and the approximate bit error rate (BER) performance is characterized. The analytical results show that the BER of the maximum-eigenvalue detector converges to a fixed number in large signal-to-noise ratio or number of receiving antennas $M$ regime. Finally, numerical results are presented to confirm the correctness of theoretical analysis, and reveal that the maximum-eigenvalue detector outperforms the energy detector regarding the BER performance. [ABSTRACT FROM AUTHOR]

Direct conversion radios are widely recognized as the most appealing approach for reducing the hardware cost as well as power consumption in upcoming communication systems. However, such radios are known to entail gain and phase uncertainties along the analog inphase/quadrature (I/Q) paths. In this paper, we address the effects of the transmitter (TX) and receiver (RX) I/Q errors or mismatches on the improperness of the transmitted and received signals, respectively. We analytically show how the properness of a transmitted signal and the receiver thermal noise can be destroyed, respectively, under the transmitter and receiver I/Q errors, given that the corresponding ideal signals are proper under perfect I/Q balance. Then, we address the spectrum sensing problem in cognitive radio systems through modeling it as a composite binary hypothesis testing task, and apply the likelihood ratio test approach to solve it. To this end, we propose three impropriety-based multiantenna spectrum sensing algorithms under the transmitter and receiver I/Q uncertainties. The principle of invariance is exploited to examine the potential constant false alarm rate (CFAR) behavior of the proposed detectors. We analytically prove that all the proposed sensing methods possess CFAR behavior against the noise variance uncertainty, while only two of them have CFAR property against the receiver I/Q mismatch values. The achievable sensing performance of the proposed methods is then analyzed through extensive numerical experiments, and the devised alternative detectors are mutually compared. Finally, analytical solutions are derived to quantify the improvement/degradation in the effective received signal SNR under I/Q imbalanced radios. [ABSTRACT FROM AUTHOR]

Quadrature spatial modulation (QSM) using frequency modulated diverse retrospective array (FMD-RDA) is put forward to achieve green transmission paradigm shift from phased-array-based arrangement. Up to date, the QSM techniques have employed phased-array, but only angular focusing direction is possible without range focusing direction. On the other hand, millimeter-wave (mmWave) scheme is suggested as an alternative approach for fifth-generation because of large bandwidth spectrum. Therefore, this paper studies green secure communication range-angle focusing QSM FMD-RDA in mmWave wireless communication. In FMD-RDA, a small frequency increment is included across the RDA elements to decouple range-angle focusing. More importantly, an attractive advantage of using FMD-RDA is the automatic self tracking feature which alleviate transmitter/receiver's channel state information (CSI) requirement. To ensure secure transmission, we exploit physical layer security to degrade the channel quality of the eavesdropper. Furthermore, low complexity greedy detector is devised to retrieved the information bits at the receiver. We also derived pair-wise error probability, and analyze secrecy sum rate and energy transfer capability. The reported simulation results demonstrate that the proposed scheme is effective in improving the spectral efficiency with low complexity and no CSI requirement. [ABSTRACT FROM AUTHOR]

Abstract Molecular Communication via Diffusion (MCvD) is a promising paradigm which enables nano-machines to communicate with each other. However, the reliability of existing communication systems degrades rapidly as the distance between the transmitters and the receivers grows. To solve this issue, relaying schemes must be implemented in practice. In this paper, we study two relaying schemes: In the first case, the relay node decodes the incoming signal symbol and forwards it to the receiver using a different types of molecules. Then, the receiver detects the information bits by only considering the molecules from the relay node. In the second case, the receiver considers both types of molecules sent from the transmitter and the relay node. Closed-form expression for the end-to-end bit error probability of the these two schemes are derived. Also, we obtain optimal relay location for both schemes. Moreover, we study the optimal threshold, concentration, baud-rate and timing offset to mitigate the overall Inter-Symbol Interference(ISI) and obtain maximum throughput in the relay network. [ABSTRACT FROM AUTHOR]

Index modulation (IM) is an attractive concept for next generation communication systems. However, as an emerging technique, there are still some challenges need to be tackled in this frontier. In this paper, we consider two aspects of IM, which are diversity and detection complexity. Specifically, we propose a linear precoding assisted index modulation (LPIM) scheme for orthogonal frequency division multiplexing (OFDM) systems. We commence by analyzing the diversity and coding gains of the proposed scheme. Moreover, a detailed codebook design criterion is proposed. Then, our LPIM codebook is designed based on the maximum diversity and coding gain criteria. In contrast to the signaling model of the existing full diversity precoder designed for OFDM, we introduce a modeling method to link the zero-valued IM symbols to the origin of a Lattice for implementing our full diversity precoder designed for OFDM-IM. Both analytical and computer simulation results are provided for characterizing the attainable performance of OFDM-LPIM, demonstrating that it is capable of achieving full diversity as well as an attractive coding gain. However, the maximum-likelihood (ML) detection complexity of OFDM-LPIM is excessive, hence a low-complexity generalized iterative residual check detector (GIRCD) is proposed, which is inspired by the existing sparse recovery algorithms. Finally, computer simulation results are provided for demonstrating that GIRCD can provide a beneficial trade-off between bit error ratio performance and complexity. [ABSTRACT FROM AUTHOR]

This paper addresses the issues on spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Each cognitive user may occupy a non-overlapped sub-band of the primary spectrum, but it needs to perform spectrum sensing independently before accessing the sub-band. To reduce the complexity of spectrum sensing and thus energy consumption, this paper proposes a scheduled spectrum sensing scheme. First, we consider a single spectrum sensing scenario where only one cognitive user is elected to perform spectrum sensing, and then it broadcasts its sensing results to the other cognitive users. The scheduled spectrum sensing scheme works in both network-centric and user-centric ways. Next, the scheduled spectrum sensing scheme is further generalized to work in a multiple spectrum sensing scenario. The results show the effectiveness of the proposed schemes compared with the traditional schemes where all cognitive users may perform spectrum sensing at the same time. Copyright © 2010 John Wiley & Sons, Ltd. This paper proposes a scheduled spectrum sensing scheme for spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Both single and multiple scheduled spectrum sensing schemes are considered. The results show that in general the proposed scheduling schemes are more efficient than the extreme case in terms of the number of sensing operations required with a given sum false alarm probability and the sum-missed detection probability. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

With the advent of the Internet of things, massive machine-type communications (mMTC) have become one of the most important requirements for next generation communication systems. In the mMTC scenarios, grant-free nonorthogonal multiple access on the transmission side and compressive sensing-based multi-user detection (CS-MUD) on the reception side are a promising solution because many users sporadically transmit small data packets at low rates. In this paper, we propose a novel CS-MUD algorithm for the active user and data detection in the mMTC systems. The proposed scheme consists of the maximum a posteriori probability (MAP) based active user detector (MAP-AUD) and the MAP-based data detector (MAP-DD). By exchanging the extrinsic information between MAP-AUD and MAP-DD, the proposed algorithm improves the active user detection performance and the reliability of the data detection. In addition, we extend the proposed algorithm to exploit group sparsity. By jointly processing the multiple received data with common activity, the proposed algorithm dramatically enhances the active user detection performance. We show by numerical experiments that the proposed algorithm achieves a substantial performance gain over existing algorithms. [ABSTRACT FROM AUTHOR]

A next-generation network (NGN) is an advanced network that exploits multiple broadband and QoS-enabled transport technologies to provide telecommunication services. The principles and requirements of convergence of wireless sensor networks are likely to deliver all the desired benefits of NGN and should be carefully studied. In this paper, we focus on the power consumption topic, which is a fundamental concern in wireless multimedia sensor networks (WMSNs). Node placement in WMSNs has considerable impact on network lifetime. In this paper, we have investigated and developed a power-efficient node placement scheme (PENPS) in linear WMSNs, which can minimize the average energy consumption per node and maximize the network lifetime. The analysis of PENPS and the comparison of performance with the equal-spaced placement scheme (EPS) show that PENPS scheme can significantly decrease the average energy consumption per node, which can prolong the lifetime of sensor nodes and sensor networks effectively. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) consist of networked sensor nodes, deployed to sense a phenomenon and report it to a base station. Sensor nodes are small and usually equipped with small batteries with limited capacity, and therefore, one of the most important design considerations for WSNs is power consumption. WSNs expend energy for communications, data processing and sensing; for commonly used RF communications this task accounts for the largest portion of power expended. Hybrid radio frequency/free space optical (RF/FSO) communications has been proposed to reduce power consumption by the sensor node, and in this paper, the performance of the RF/FSO WSN is compared against an RF-only WSN in terms of network lifetime and coverage. Results show that for the wide range of scenarios considered, the RF/FSO WSN lasts at least twice as long as its RF-only counterpart, despite providing the same level of network coverage. This paper also investigates network parameter selection for optimum RF/FSO network coverage. [ABSTRACT FROM AUTHOR]

A precise localization is required in order to maximize the usage of Mobile Sensor Network. As well, mobile robots also need a precise localization mechanism for the same reason. In this paper, we showed a combination of various localization mechanisms for precise localization in three different levels. Localization can be classified in three big categories: wide area and long distance localization with low accuracy, medium area and distance localization with medium accuracy, and small area short distance localization with high accuracy. In order to present localization methods, traditional map building technologies such as grid maps or topological maps can be used. We implemented mobile sensor vehicles and composed mobile sensor network with three levels of localization techniques. Each mobile sensor vehicles act as a mobile sensor node with the facilities such as autonomous driving, obstacle detection and avoidance, map building, communication via wireless network, image processing, extensibility of multiple heterogeneous sensors, and so on. For localization, each mobile sensor vehicle has abilities of the location awareness by mobility trajectory based localization, RSSI based localization and computer vision based localization. With this set of mobile sensor network, we have the possibility to demonstrate various localization mechanisms and their effectiveness. In this paper, the result of computer vision based localization, sensor mobility trail based localization and RSSI based localization will be presented. [ABSTRACT FROM AUTHOR]

The paper considers the connected target coverage (CTC) problem in wireless heterogeneous sensor networks (WHSNs) with multiple sensing units, termed MU-CTC problem. MU-CTC problem can be reduced to a connected set cover problem and further formulated as an integer linear programming (ILP) problem. However, the ILP problem is an NP-complete problem. Therefore, two distributed heuristic schemes, REFS (remaining energy first scheme) and EEFS (energy efficiency first scheme), are proposed. In REFS, each sensor considers its remaining energy and its neighbors' decisions to enable its sensing units and communication unit such that all targets can be covered for the required attributes and the sensed data can be delivered to the sink. The advantages of REFS are its simplicity and reduced communication overhead. However, to utilize sensors' energy efficiently, EEFS is proposed. A sensor in EEFS considers its contribution to the coverage and the connectivity to make a better decision. To our best knowledge, this paper is the first to consider target coverage and connectivity jointly for WHSNs with multiple sensing units. Simulation results show that REFS and EEFS can both prolong the network lifetime effectively. EEFS outperforms REFS in network lifetime, but REFS is simpler. [ABSTRACT FROM AUTHOR]

In wireless sensor networks (WSN), it is very important for sensor nodes to locate with low energy consumption and high accuracy, especially in a dangerous environment. This paper describes a range-free layered localization scheme using one mobile anchor node which can transmit gradient signals, and whose moving track is a straight-line along the x-axis. And this paper proposes a sleep/wake mechanism called sensor sleep-time forecasting to save energy consumption during localization. The relationship, between the key factors in localization algorithm and the average location error, is analyzed in detail. Simulation results show that the scheme performs better than other range-free mechanisms—the average location error is less than 0.7 m, and it is independent on sensor nodes density or sensor nodes radio range, the accuracy of the algorithm can be adjusted in different occasions, and the algorithm beacon overhand is small and average localization time is short. [ABSTRACT FROM AUTHOR]

Rainfall rate is the main cause of fades in the frequency bands above 10 GHz. To optimize the planning of satellite and terrestrial radio communication systems operating on these frequency bands, it is essential to have a detailed knowledge of the temporal and spatial distributions of the rainfall rate. For this reason, it is necessary to develop experimental networks, which provide adequate data to study, prevent, and compensate the rain fade. In this paper, an experimental instrumentation network is presented. This network comprises weather stations that are capable of measuring rainfall rate; temperature, and humidity; a weather radar; and three radio links. This paper first introduces the rationale and the state of the art in meteorological sensors and describes the experimental network for automatic data acquisition as a distributed process system. The design of the experimental network is explained in detail. Finally, the interest in millimeter wavelength for broadband applications is outlined, and some research lines from the collected data are presented. [ABSTRACT FROM AUTHOR]

This paper proposes a cross-layer optimization framework for the wireless sensor networks. In a wireless sensor network, each sensor makes a local observation of the underlying physical phenomenon and sends a quantized version of the observation to a central location via wireless links. As the sensor observations are often partial and correlated, the network performance is a complicated and nonseparable function of individual data rates at each sensor. In addition, due to the shared nature of wireless medium, nearby transmissions often interfere with each other. Thus, the traditional "bit-pipe" model for network link capacity no longer holds. This paper deals with the joint optimization of source quantization, routing, and power control in a wireless sensor network. We follow a separate source and channel coding approach and show that the overall network optimization problem can be naturally decomposed into a source coding subproblem at the application layer and a wireless power control subproblem at the physical layer. The interfaces between the layers are precisely the dual optimization variables. In addition, we introduce a novel source coding model at the application layer, which allows the efficient design of practical source quantization schemes at each sensor. Finally, we propose a dual algorithm for the overall network optimization problem. The dual algorithm, when combined with a column-generation method, allows an efficient solution for the overall network optimization problem. [ABSTRACT FROM AUTHOR]

In semiautonomous mobile sensor networks (MSNs), since human operators may be involved in the control loop, particular improper actions may cause accidents and result in catastrophes. For such systems, this paper proposes a command filtering framework to accept or reject the human-issued commands so that undesirable executions are never performed. In the present approach, Petri nets are used to model the operated behaviors and to synthesize the command filters for supervision. An application to a mobile wireless surveillance system is provided to show the feasibility of the developed approach. It is believed that the technique presented in this paper could be further applied to large-scale wireless MSNs. [ABSTRACT FROM AUTHOR]

Protecting implemented security mechanisms and trusting their output (e.g. log files) when the host, under which they are deployed, is compromised, is among the major challenges that have to be faced. To fulfil this need, recent advances in security have considered the design of storage-based intrusion detection system, which detect intrusions by looking at the low-level disk requests patterns. However, these systems neither tolerate intrusions, nor do they distinguish whether the disk requests are generated by legitimate or malicious processes; and consequently, they generate a lot of false negative and positive alerts. In this paper, we present a Cooperative Intrusion Detection and Tolerance System, called CIDTS, which takes advantage of the information that are available at the network, host operating system, and storage level to better detect intrusion attempts in their early stages, even when the host is compromised. To allow cooperation, the disk communication interface that transports requests between the storage level and the host level is extended to forward information about the processes that generate the request. The paper also provides intrusion tolerance capabilities and provides techniques to support investigation activities. Copyright © 2007 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In random-access communication systems, the number of active users varies with time, and has considerable bearing on receiver's performance. Thus, techniques aimed at identifying not only the information transmitted, but also that number, play a central role in those systems. An example of application of these techniques can be found in multiuser detection (MUD). In typical MUD analyses, receivers are based on the assumption that the number of active users is constant and known at the receiver, and coincides with the maximum number of users entitled to access the system. This assumption is often overly pessimistic, since many users might be inactive at any given time, and detection under the assumption of a number of users larger than the real one may impair performance. The main goal of this paper is to introduce a general approach to the problem of identifying active users and estimating their parameters and data in a random-access system where users are continuously entering and leaving the system. The tool whose use we advocate is Random-Set Theory (RST): applying this, we derive optimum receivers in an environment where the set of transmitters comprises an unknown number of elements. In addition, we can derive Bayesian-filter equations which describe the evolution with ti me of the a posteriori probability (APP) density of the unknown user parameters, and use this density to derive optimum detectors. In this paper, we restrict ourselves to interferer identification and data detection, while in a companion paper we shall examine the more complex problem of estimating users' parameters. [ABSTRACT FROM AUTHOR]

This paper presents a 3-dimensional algorithm for determining the node locations in ad-hoc wireless local area sensor networks capable of internodal distance measurement (ranging). In accordance with common classification of localisation strategies, the paper proposes a geometric centralised optionally anchor free algorithm that is based on clusterisation, multilateration and geodetic network adjustment. The method avoids fold- ambiguities by statistical tests on the robustness of the minimally stable structure in 3D. Such a rigid cluster is expanded by a novel robust approach for multilateration. The algorithm developed is capable of obtaining the least-squares solution reliably even in the presence of measurement noise levels of up to 7% of the ranges. Simulations with randomly deployed networks show that it is possible to reach the best achievable mean position deviation (i.e. the Cramer Rao bound). [ABSTRACT FROM AUTHOR]