To deal with the multimodality, nonlinearity, and nonconvexity of the maximum likelihood (ML) cost function when solving the localization problem with received signal strength (RSS) in wireless sensor networks, we propose a localization approach based on the differential evolution algorithm, opposition-based learning, and adaptive redirection in a unified way. In the proposed approach, we need neither to approximate the ML cost function nor to provide a good initial point while most conventional approaches, including those based on the semidefinite programming, second-order cone programming, and unscented transformation. The performance and computational complexity of the proposed approach are analyzed and compared with those of other approaches for three practical scenarios. Simulation results confirm that the proposed approach performs better than other approaches with relatively low computational complexity. Note to Practitioners-This article was motivated by the problem of localization in wireless sensor networks that can be found in different areas, such as intelligent farming, health care monitoring, and environmental monitoring. In this article, a technique is proposed, which exploits the RSS measurements to estimate the position of a target node. This technique is quite popular due to its simplicity and low cost. Most of the techniques based on the ML formulation approximate the ML cost function due to its high nonlinearity and nonconvexity. This article suggests a new approach using differential evolution and opposition-based learning a redirection, which does not require approximating the ML cost function to find the location of a target. In addition, in this article, we analyze the sensor nodes' placement and its effect on localization accuracy. Numerical results in three practical scenarios are provided to demonstrate the effectiveness of the proposed approach and its superiority compared with state-of-the-art algorithms. In future research, we will address a more realistic scenario with multiple targets.

We propose a novel TH-NRDCSK system to enjoy the advantages of both TH and chaotic systems for AJ communication purpose and alleviate the strict synchronization issue of TH systems. We then simulate the performance of the proposed system to reveal the effects of the system parameters on AJ performance. In addition, the performance of the proposed system is compared to that of the TH-BPSK system to look at the advantages of non-coherent system. The simulation results show that the proposed system significantly outperforms conventional counterparts in a practical environment.

Common fall occurrences in the elderly population pose dramatic challenges in public healthcare domain. Adoption of an efficient and yet highly reliable automatic fall detection system may not only mitigate the adverse effects of falls through immediate medical assistance, but also profoundly improve the functional ability and confidence level of elder people. This paper presents a pervasive fall detection system developed on smart phones, namely, FallDroid that exploits a two-step algorithm proposed to monitor and detect fall events using the embedded accelerometer signals. Comprising of the threshold-based method and multiple kernel learning support vector machine, the proposed algorithm uses novel techniques to effectively identify fall-like events (such as lying on a bed or sudden stop after running) and reduce false alarms. In addition to user convenience and low power consumption, experimental results reveal that the system detects falls with high accuracy (97.8% and 91.7%), sensitivity (99.5% and 95.8%), and specificity (95.2% and 88.0%) when placed around the waist and thigh, respectively. The system also achieves the lowest false alarm rate of 1 alarm per 59 h of usage, which is best till date.

Distribution of limited smart grid resources among electric vehicles (EVs) with diverse service demands in an unfavorable manner can potentially degrade the overall profit achievable by the operating charging station (CS). In fact, inefficient resource management can lead to customer dissatisfaction arising due to prolonged queueing and blockage of EVs arriving at the CS for service. In this paper, a dynamic electric power allocation scheme for a charging facility is proposed and modeled as a bi-variate continuous-time Markovian process, with exclusive charging outlets being allotted to EVs of different classes in real-time. The presented mechanism enables the CS to guarantee the quality-of-service expected by customers in terms of blocking probability, while also maximizing its own overall revenue. By adopting a practical congestion pricing model within the defined profit function, the revenue optimization framework for a single CS is further extended to a load-balanced network of CSs. Simulation results for the single CS and networked models reveal considerably higher satisfaction levels for congested fast charging EV customers and improved attainable system revenue as compared to a baseline scenario which assumes no classification based on EV service preferences.

Wireless sensors and multimedia communications are increasingly becoming a part of our everyday lives and societies.Subsequently, issues surrounding their safety and security are becoming ever more important.The situation is true, not only for overtly hostile environments such as for defense and public security, but also for covert commercial platforms handling private and sensitive information.Also, with the advent of new devices and circuits from the development of military systems, a host of new technologies have come to the fore, including sophisticated RF sensing, activating, signal processing, and communications.The prompt ability to protect against hostile actions to sense, access, process, command, and control covert information is of utmost importance and is vital for the success of this next generation of communication systems and networks.This special issue presents several research results in covert communication networks in hostile environments, including the identification of current challenges for each domain, the development of novel technologies and strategies, and discussion and exploration of future solutions.The first challenge of the cover communications and networks is how to confront the hostile noises or environments.Historically, for communication engineers, the white Gaussian is the least favorable noise [1], and conventional system designer considers the best design under the least favorable Gaussian or combination of the multiple or variational Gaussian, such as Rician, Nakagami, or others in [2].However, the hostile noises are far from the natural Gaussian shape and are rather close to typical signals such as single tone and sweep sinusoidal jamming.Further, the hostile noise is very intentional, having less information in theory in other words.Subsequently, we may fully utilize the known and

This paper investigates the antijamming performance of the NR-DCSK system. We consider practical jamming environments including broadband jamming (BBJ), partial-time jamming (PTJ), tone jamming (TJ), and sweep jamming (SWJ). We first analytically derived the bit error rates of the system under the BBJ and the PTJ. Our results show that the system performances under these two jamming environments are enhanced as P increases, where P is the parameter of the NR-DCSK modulation scheme denoting the number of times a chaotic sample is repeated. In addition, our results demonstrate that, for the PTJ, the optimal value of the jamming factor is close to zero when the jamming power is small; however, it increases and approaches one as the jamming power enlarges. We then investigate the performance of the system under the TJ and the SWJ via Monte-Carlo simulations. Our simulations show that single-tone jamming causes a more significant performance degradation than multitone jamming. Moreover, we point out that the system performance is significantly degraded when the starting frequency of the sweep jammer is close to the carrier frequency of the transmitted signals, the sweep bandwidth is small, and the sweep time is half of the transmitted bit duration.

In vehicle-to-vehicle (V2V) channels, roadside scatterers (RSSs), such as houses, buildings, trees, and many more, play a crucial role in the determination of the Doppler power spectral density (DPSD) characteristics. However, the relevant research results are scarce due to the lack of computationally tractable analytic DPSD solutions. To fill this gap, we investigate an indirect method for the DPSD analysis of a generic 2-D RSS model for V2V channels. The indirect method, based on Hoeher's theorem, employs successive transformations of random variables to obtain the DPSD. Compared with the conventional methods, leading to impractical multiple integral solutions, our method yields a single integral form, more useful for analytic studies, model validation/parameter estimation, and fading simulator design. Using the new DPSD solution, the impact of different RSS layouts on the DPSD characteristics is further investigated, and several new insights are provided. The joint probability density function (PDF) of the angle-of-departure and the angle-of-arrival (AoA) and the joint Doppler-AoA PDF are newly presented in closed forms and analyzed with respect to the DPSD shape. Comparisons with the DPSDs measured in highway and urban canyon environments demonstrate not only the validity of the generic 2-D RSS model but also the significant contribution of RSSs to V2V channels.

Industrial wireless sensor networks are getting popular for indoor monitoring of heavy machinery and large factories to make a reliable decision on the state of machines in a certain area of interest. However, the indoor wireless communication channel is not always reliable, and observations of some sensors cannot be reported successfully to the base station. In order to deal with this problem, we propose a cooperative WSN scheme by introducing a novel cooperation mechanism and a medium access control protocol. The proposed scheme effectively increases the probability of correct decision about the state of the machine, reduces the probability of false alarms at a given signal level, and reduces the overall energy consumption as compared to noncooperative schemes. We also present a closed-form expression for the symbol-error rate analysis of the proposed scheme, which shows that our proposed scheme achieves full diversity order offered by the cooperation scheme.

Sudden cardiac arrests are mainly caused by ventricular fibrillation and ventricular tachycardia, which are known as shockable (SH) rhythms and properly curable by electronic defibrillators. In this paper, we propose a novel algorithm to decide whether an electrocardiogram (ECG) signal is SH or nonshockable (NSH). The algorithm selects 20 features from both the preprocessed ECG and its NSH signal using a modified variational mode decomposition technique, and uses the support vector machine for the binary SH/NSH classification. The 20 features are identified as an efficient set of the most informative, among 54 candidate features, by comparing the balanced error rate of each combination, based on two layers of feature selection. This feature set is validated with the evaluation data in the public database using a fivefolds cross validation procedure. The proposed algorithm results in accuracy of 99.00%, sensitivity of 97.36%, and specificity of 99.16%.

Due to the advancement in energy harvesting wireless sensor networks (EH-WSNs), the data collection from one-hop stationary sensor nodes using a path-constrained mobile sink has become one of the challenging issues. Toward the throughput improvement, we propose a general framework for network throughput maximization (NTM) problem by optimizing practically feasible parameters. For each proposed scenario, a mixed integer linear programming (MILP) optimization model is introduced for the problem formulation. Due to the NP-Hardness of the MILP models, we design two efficient algorithms namely as ODSAA and ODAA for two practically implementable scenarios. Having a preknowledge about the deployed location of nodes, the proposed algorithms run centrally by sink and find the sub-optimal solutions within a reasonable computation time. Furthermore, under the uniform distribution of energy harvesting, we find out two threshold points on, respectively, energy harvesting mean and battery capacity of nodes after which the network throughput reaches a stable point. Finally, simulations are conducted on a different set of node deployments, which the results confirm that the proposed algorithms significantly improve the data throughput collected by sink and also the theoretical thresholds provide a confidence interval of 90 percent.

In this paper, we focus on the issue of maximizing the data collected by a mobile sink with unlimited energy which traverses a given straight path in an energy harvesting wireless sensor network (EH-WSN). Sensors are assumed to harvest energy periodically from the solar resources in their surrounding. Due to limitations on energy replenished within different time intervals, the sensors can reduce their transmission period in time slots with lesser available data in order to conserve energy for the possibility of higher data transmission in consecutive slots. Aiming at improving the overall network throughput, we formulate the problem of finding the effective data transmission period as a mixed integer linear programming (MILP) optimization model. With prior knowledge of the maximum transmission range, we design an online centralized algorithm for the problem which is run by the sink and easily scalable to large network sizes. Corroborated by extensive simulation results, we demonstrate that the proposed algorithm outperforms the existing work with the mean of throughput improvement being inversely proportional to that of the energy harvested while exhibiting the same order of computational complexity.

Fairness is an important property of computer networks and systems. In a wide range of these systems such as distributed multi-hop wireless networks, multihomed networks, and cloud computing, each user may be allocated a number of system resources; this resembles a many-to-many relationship between the sets of users and resources, which raises the problem of system-wide fair resource allocation. In this paper, we assume that each user/node can be allocated a number of resources, which could be either in its neighborhood or far from it. As a key difference with previous works and through incorporating the concept of “flow”, we model near/far resources allocated to nodes. To attain fair flow control in such systems, first we model this situation by introducing a new multi-server system called multi-ring, in which a server that represents a resource, can serve only a subset of either neighboring or far nodes in the system. Then, we define a centralized optimization problem to attain weighted proportional fairness among all nodes meaning that the sum of allocated capacities from all servers to each node (while considering its flow) is fair. We evaluate fairness properties of multi-ring networks and provide conditions on system parameters under which a system can have a fair resource allocation. Moreover, we present a distributed method to attain fairness in distributed environments, and its stability/convergence is evaluated by non-linear discrete dynamical systems. We present conditions under which the system is stable, and through numerical analysis, we show how to obtain stable system parameters for large systems. The effectiveness of the presented method is studied through extensive numerical evaluation. Results show the success of our method in attaining fairness for various topologies and system parameters, and confirm our stability analysis. A number of systems with fairness issues are also studied as potential applications of our model.

In energy harvesting wireless sensor networks (EH-WSNs), maximizing the data collection throughput is one of the most challenging issues. In this paper, we consider the problem of data collection on a pre-specified path using a mobile sink which has a fixed-mobility pattern. As a generalization of the previous works, we propose an optimization model for the problem which incorporates the effective and heterogeneous duration of sensors' transmission in each time slot. To improve the network throughput, a simple condition is proposed which determines the maximum number of available time slots to each sensor node. Accordingly, the proposed condition specifies the constant velocity of the mobile sink. The NP-Hardness of the problem under the proposed condition is proved and an online centralized algorithm with less complexity is designed to handle the problem. Its complexity is in polynomial order and is easily scalable to the networks with large number of sensor nodes. Furthermore, we address the effect of increase in time slot period on the total amount of collected data which has not been yet exploited well. Finally, through extensive simulations on different set of deployed nodes, we observe that the proposed algorithm significantly increases the network throughput when the travelled distance by sink per time slot is reduced down to the adjusted point.

Maintaining efficiency and fairness is a challenging problem in distributed systems and networks. In this paper, we focus on distributed multi-server systems and networks in which each user may be allocated resources by different servers. Reemphasizing polling systems as abstractions of resource sharing systems, in this paper, first we introduce a multi-server polling system in which each server (resource) can poll (be allocated to) only a subset of queues (users) in the system to model a wide range of multi-server systems such as multihomed networks and cloud computing. Then, to obtain a fair resource allocation vector to queues, a network utility maximization problem with a general utility function is defined. Depending on the type of the utility function, the presented scheme can attain different kinds of fairness such as weighted proportional and max-min fairness. Although maintaining fairness is important in many applications, providing efficiency is also crucial. Hence, we present an efficient algorithm to convert the obtained fair resource allocation vector into a Markovian routing matrix to determine the polling order of queues. This algorithm is capable of improving performance measures such as delay variance and mitigating short-term unfairness by minimizing the probability of consecutive polling of the same queue. Two distributed schemes are presented to obtain fairness and efficiency in even highly dynamic and distributed environments. The effectiveness of the presented schemes is also studied through simulation and numerical evaluation. Our results show their success in attaining fairness and efficiency in dynamic multi-server distributed systems and networks.

In this paper, we question the accuracies and validity ranges of conventional geometry-based one-ring models (GBORMs) and their variants whose correlation functions (CFs) are based on approximate total propagation distances (TPDs) under a small beamwidth (or small angular spread) assumption. To answer this, we use a reference GBORM for space-time-frequency (STF) correlated channels and analyze the accuracies and validity ranges of the conventional models. Our analysis shows that the conventional models become inaccurate for urban pico/micro/macrocells, vehicular-to-vehicular, and wideband channels, where large beamwidths and relative propagation delays are typical. In order to remedy these issues, we propose new TPDs and closed-form STF-CF using novel approximation methods with Jacobi-Anger expansion and show their superior accuracies and validity range. The new closed-form STF-CF represents or includes conventional closed-form CFs as special cases for small beamwidth. Also, it has favorable properties facilitating its use in a wide range of propagation channels. The applicability of the new solutions to conventional wideband models are tested and verified based on measured data.

In this paper, we introduce the problem of road condition surveillance using a mobile vehicle as a concrete practical application of data collection paradigm on a direct path in energy harvesting wireless sensor networks (EH-WSNs). The application components together with its associated challenges are discussed throughout the paper. An optimization model is introduced for the network throughput maximization problem. In contrast to the previous models, the proposed optimization model considers the effective and heterogeneous duration of sensor's transmission together with the dynamic aspect of energy harvesting over different time intervals. Towards the improvement of the network throughput under a proposed condition, an online centralized algorithm with less complexity is designed. Finally, simulations on both Random and Equal-Distance deployment of sensor nodes are conducted to compare the performance of the proposed algorithm with the previous approaches and to observe the effect of different energy harvesting distributions on the throughput achieved by the algorithm.

Approximate message-passing (AMP) method is a simple and efficient framework for the linear inverse problems. In this letter, we propose a faster AMP to solve the L1-Split-Analysis for the 2-D sparsity separation, which is referred to as MixAMP. We develop the MixAMP based on the factor graphical modeling and the min-sum message-passing. Then, we examine MixAMP for two types of the sparsity separation: separation of the direct-and-group sparsity, and that of the direct-and-finite-difference sparsity. This case study shows that the MixAMP method offers computational advantages over the conventional first-order method, TFOCS.

In this study, the authors investigate the expected complexity of increasing radii algorithm (IRA) in an independent and identified distributed Rayleigh fading multiple‐input–multiple‐output channel with additive Gaussian noise and then present its upper bound result. IRA employs several radii to yield significant complexity reduction over sphere decoding, whereas performing a near‐maximum‐likelihood detection. In contrast to the previous expected complexity presented by Gowaikar and Hassibi (2007), where the radius schedule was hypothetically fixed for analytic convenience, a new analytical result is obtained by considering the usage of multiple radius schedules. The authors analysis reflects the effect of the random variation in the radius schedule and thus provides a more reliable complexity estimation. The numerical results support their arguments, and the analytical results show good agreement with the simulation results.

In this letter, we aim to present a near-maximum-likelihood (ML) decoding algorithm with low-complexity for wider ranges of SNR and system dimension in multiple-input-multiple-output (MIMO) systems. Based on the proposed radius design criterion, we introduce the effective radius (ER) which is determined using the statistics of path metric under correct and incorrect decoding cases. Since the constraint established by the ER maintains tightness during most search procedure, the proposed scheme further improves the complexity, and its performance loss is still negligible by properly selecting design probabilities.

Location information is fundamental and essential for UWSNs monitoring underwater environment. Underwater environment requires three dimensional localization algorithm. Several localization protocols and system architectures have been proposed for underwater sensor networks. In this paper, 3D underwater localization algorithm is proposed for near-sea marine monitoring system, using a small number of beacons. Underwater sensors are found through a hierarchical approach. We also propose a distributed self-organized ordering scheme and a hybrid ranging method selecting one of TOA and RSS measurement in order to improve localization accuracy. The proposed 3D underwater localization algorithm increases the coverage of underwater sensor network and makes it possible to achieve accurate location.

In underwater sensor networks, localization is one of the most important issues because sensor nodes are considerably difficult to be deployed at determined locations. Localization schemes using a mobile beacon have fine-grained localization accuracy because one mobile beacon can replace a lot of static beacons. In localization with a mobile beacon, the movement of a mobile beacon determines the deployment of the beacons used for localization and the deployment influences the localization accuracy. To improve the localization accuracy for localization with a mobile beacon, the study on the path of a mobile beacon is necessary. In this paper, we propose a static path to improve the localization accuracy by considering the path of a mobile beacon and the deployment of the beacons. Simulation results show that the determined static path provides higher localization accuracy than a random path and other static paths.

Range-free localization schemes are much promising in wireless sensor networks because they can estimate the location of a sensor node without power-consuming and expensive devices for measuring distance or angle information. Among range-free schemes, multi-hop schemes can localize sensor nodes with a few beacon nodes through the multi-hop connection between nodes. Since the localization accuracy depends largely on the communication range in multi-hop schemes, the communication range should be determined considering the relationship between the communication range and the localization accuracy. In this paper, we propose the selection method of the communication range for the DV-Hop scheme, a typical multi-hop scheme. The DV-Hop scheme utilizing the selection method of the communication range leads to better position determination than some existent range-free multi-hop schemes.

The distributed detection problem in wireless sensor networks is studied under the impulsive α-stable noise assumption. Since symmetric α-stable density does not have a closed form, its approximation, the bi-parameter Cauchy Gaussian mixture model, is used to describe the impulsive behavior of α-stable noises. With this model, we propose a low-complexity robust fusion rule by taking the maximin setting with respect to the detection probability. An explicit formula for the detection probability is derived. Robustness of the proposed maximin fusion rule is justified by numerical and simulation results for α-stable noises.

In practical problems of signal detection, it is quite common that the underlying noise distribution is not Gaussian and may vary in a wide range from light- to heavy-tailed forms. To design a robust fusion rule for distributed detection in wireless sensor networks, an asymptotic maximin approach is used by introducing weak signals in the canonical parallel fusion model. Explicit formulas for the detection and false alarm probabilities are derived. The analytic results are written out for the classes of nondegenerate, with a bounded variance and contaminated Gaussian noise distributions. Numerical and simulation results are obtained to justify robustness and asymptotic characteristics of the proposed fusion rule.

This paper presents a bearings-only tracking (BOT) scheme based on distributed floating beacons in underwater sensor networks (UWSNs). Conventional BOT systems extract target-originated bearings in noisy measurements, locate and track targets based on the bearings in real time. We propose a tracking scheme by modifying BOT systems for UWSNs where a multidimensional assignment (MDA) method is used to extract target-originated bearings and to associate them with corresponding targets. In addition, a threshold-based decision in extracting bearings in MDA and a local Kalman filter is proposed to keep tracking information at a floating beacon even if a target is undetected. Simulation results show that the proposed scheme has advantage of tracking accuracy over recently known work under low detection probability.

In underwater sensor networks, localization is one of the most important issues because sensor nodes are considerably difficult to be deployed at determined locations. Since range-based schemes require additional device and precise time synchronization for measuring distances in underwater environments, range-free schemes are promising in the view point of energy consumption and implementation. Coarseness of range-free schemes in the localization accuracy can be compensated utilizing a mobile beacon. In this paper, we propose a new range-free localization scheme with a mobile beacon which estimates two candidates for the location of a sensor node utilizing geometry and then determines the final location out of the two candidates. During simulations, the proposed scheme was indeed shown to provide higher localization accuracy with respect to irregularities in acoustic range.

Classical network fluid model and RED algorithm are based on TCP flows in internet network, and they have not considered the UDP flows' effects in network. However, in real work of the network, the network link capacity is shared by the hybrid traffics: TCP flows and UDP flows, and UDP flows can occupy the original link capacity of TCP flow. Since there is no feedback control for UDP flows, the classical network fluid model and RED algorithm can not reflect and control the congestion of TCP/UDP networks. To solve the problem, we modify the classical AQM router into multiple queues AQM router with classifier. We express the proposed TCP/UDP AQM router by a linear time-delay system model. Then, by utilizing the 2-D Laplace-Z transform technique, we derive some explicit conditions that establish the relationship between the control parameter pmaxand the network stability. This paper first proposes parameter pmax's stability bounds for TCP/UDP routers for congestion control based on 2-D Hurwitz-Schur stability conditions. The simulation results verify that the proposed stability condition can gain the effective congestion control.

In this paper, we present a new scheme combining mode switching (SM/STBC), and transmit antenna subset selection (Tx-AnSS), i.e.,joint selection for a multiuser-MIMO (MU-MIMO) system with block diagonalization (BD) for error probability enhancement. Further, the proposed scheme also adaptively selects the number of streams by a simple selection criterion which is a square minimum Euclidean distance of the user with worst performance. Then, the proposed joint selection with multi-streams can take the advantages of spatial diversity improvement and array gain. Simulation results show that bit error rate (BER) of the proposed scheme outperforms the conventional schemes, which follows the SM-based scheme at low-SNR region and the STBC-based scheme at high-SNR region.

In large-scale sensor networks, localization with mobile beacons is one of the most efficient ways to deploy sensor nodes as well as locate them. Direct communication with mobile beacons has an advantage of improvement in location accuracy by enabling sensor nodes to measure distances to the mobile beacons. Thus, it is important to improve the accuracy in the distance for high accurate positioning. In this letter, we propose a distance estimation scheme with weighted least squares in mobile beacon-based localization. First, we model distance measurements to a beacon node moving along the given linear tracks. Given our measurement model, the proposed scheme uses weighted least squares to minimize errors in distance measurements. Additionally we analyze the lower bound of errors in our distance estimation based on the Cramer-Rao bound. Simulation results show that our scheme can provide improved accuracy in both distance estimation and position estimation.

This paper presents reliability comparison of opportunistic scheduling and block diagonalization (BD)-precoding in downlink MIMO systems, employing orthogonal space-time block coding (OSTBC) with multiple users. The opportunistic scheduling scheme transmits data of a user to provide the maximum effective signal-to-noise ratio (SNR), while the BDprecoding scheme transmits data for all users in a precoded form to remove co-channel interference. At first, we derive the exact analytical expressions of the average effective SNR for the opportunistic scheduling and BD-precoding schemes, respectively. Next, we derive the exact analytical expressions of the outage probability for both schemes. The diversity gain of outage probability is also quantified through asymptotic analysis. From the analytical results, the opportunistic scheduling scheme is shown to provide the effective SNR gain as well as the diversity gain, compared with the BD-precoding scheme, in proportion to the number of users. Finally, we illustrate the analytical results with corresponding simulation results.

Distributed detection has newly received research interest due to the success of the emerging wireless sensor network (WSN) technology. To deal with the problem of distributed detection for the WSN having the energy constraint, the fusion of decisions modeled as weak signals is studied. By using the weak signal model and additive non-Gaussian noise channels in the canonical parallel fusion scheme, we propose an asymptotic fusion rule applicable for wide classes of noise probability density functions (pdfs). In the particular case of a known pdf, an optimal detection rule is given. Both asymptotic analysis and Monte Carlo simulation are used to examine the performance of the proposed detection fusion rule.

This paper provides parameter setting and 2-D local stability conditions for TCP/RED networks. In general, a network cannot avoid congestions due to the limit of network capacity. The RED scheme is one of the representative AQM that was proposed to avoid and alleviate network congestions. However, the issue of network stability with many TCP subscribers needs to be considered when setting the RED parameters, where the classical RED has not considered the problem. In this paper, we set up a linear time-delay system for the TCP dynamic behavior and derive some stability conditions with simple RED network parameters by utilizing the 2-D Laplace-Z transform technique. Simulation results show that the proposed stability conditions can gain the effective stability in regard to the router queue length.

As Cognitive Radio Network (CRN) emerges as an extremely promising next generation wireless technology that can ease the apparent spectrum scarcity and support novel wireless applications; they will become bigger targets for hackers. Moreover, they will also be exposed to diverse security threats especially at the physical layer (PHY) spectrum sensing module. Hence, security consideration is central in its development. Starting with overview of on-going research efforts in CR-based network security, this paper describes a PHY attacker model that exploits the adaptability and flexibility of CRN. In thwarting this attack, we propose a waveform pattern recognition scheme to identify emitters and detect camouflaging attackers by using the Electromagnetic Signature (EMS) of the transceiver. On the performance of the technique, our simulation results show that our approach is effective for spectrum monitoring, mitigating denial-of-service threats and facilitating spectral efficiency.

In underwater sensor networks (UWSNs), localization is an important issue and a challenging task due to harsh environments for people to access. In this paper, we propose a distributed algorithm to locate nodes deployed in 3-D space using long-range beacons floating on the sea surface. Long-range beacons allow underwater nodes directly to obtain reference positions of beacons and to measure distances to beacons. Because all beacons are placed on the same plane, i.e. the sea surface, the proposed algorithm estimates two candidates for a node position with multidimensional scaling and then determines the final position out of two candidates. Simulation results confirm that our proposed algorithm can achieve high location accuracy with respect to measurement errors.

In this paper, we investigate a joint diversity scheme combining space-time block coding (STBC) and opportunistic scheduling in a multiple-input multiple-output (MIMO) system. In this scheme, the user with the maximum effective signal-to-noise ratio (SNR) is adaptively selected, and the closed-form symbol error rate (SER) of the joint diversity scheme is presented. The exact SER of the joint diversity scheme can then be derived forM-ary QAM andM-ary PSK modulations in flat Rayleigh fading channels. Furthermore, using asymptotic analysis, we approximate the SER and clearly quantify both the diversity order and SNR gain for the joint diversity scheme. Based on this analysis, we show that the diversity order of the joint diversity scheme is improved in proportion to multiuser diversity (MUD) and spatial diversity, whereas the SNR gain worsens as spatial diversity increases. Finally, analytical results are verified through Monte-Carlo simulation results.

Localization schemes using a mobile beacon have similar effects as the use of many static beacons in terms of improving localization accuracy. Specifically, the localization scheme with mobile beacons proposed by Ssu et al. has finegrained accuracy, scalability, and power efficiency without requiring measured distance or angle information. However, this scheme often has large location errors in ill-conditioned cases. To improve the localization accuracy in Ssu's scheme, this letter proposes a localization scheme that estimates sensor location from possible areas by using geometric constraints. During simulations, the proposed scheme was shown to provide higher localization accuracy than Ssu's scheme and other schemes using a mobile beacon.

In wireless sensor networks, an energy-efficient routing protocol is a key design factor to prolong network lifetime. Recently, Optimal Coverage-Preserving Scheme (OCoPS) is proposed in [11] as an extension of the Low Energy Adaptive Clustering Hierarchy (LEACH) routing protocol with the coverage-preserving scheme which saves energy consumption through excluding redundant nodes of which sensing ranges are fully overlapped by their on-duty neighbors. In this paper, we propose a basestation-aided clustering-based routing protocol, namely, the Basestation-aided clustering routing protocol with the Coverage-Preserving Scheme (BCoPS). In BCoPS, the base station substitutes energy intensive tasks for deployed sensor nodes to prolong network lifetime. The performance of BCoPS is compared with the LEACH and OCoPS. The extensive simulation results show that BCoPS outperforms OCoPS by more than 20% on network lifetime and by more than 30% network lifetime until the coverage rate is higher than 80%.

In wireless sensor networks, energy efficiency is a key design factor to prolong the network lifetime. Recently, optimal coverage-preserving scheme (OCoPS) is proposed in the work of Boukerche et al., (2005) as an extension of the low energy adaptive clustering hierarchy (LEACH) protocol with the coverage-preserving scheme which saves energy consumption through excluding redundant nodes of which sensing ranges are fully overlapped by their on-duty neighbors. Nevertheless, in some stringent applications such as battlefield surveillance, fire detection, and toxic liquid leaking detection, the higher network coverage quality is also strictly required. In this paper, we propose the central angle decision algorithm (CADA) which guarantees no coverage-hole during the coverage-preserving scheme. To evaluate applicability of our proposed algorithm to routing protocols and its performance, we extend the OCoPS routing protocol with CADA, namely, the optimal coverage-preserving scheme with the central angel decision algorithm (OCoPS_CADA). Extensive simulations show that the OCoPS_CADA outperforms the OCoPS by initially guaranteeing 100% of the network coverage.

This paper presents work with regard to specification of requirement, design, and development of a hardware-in-the-loop simulation (HILS)-based advance tool for the configuration, validation, and management of a control network (CN). Embedding a simulation scenario within the design domain can improve optimality, validity, reusability, integrability, and productivity. This paper studies the basic infrastructure required to realize the HILS tool for distributed control systems (DCS). HILS for CN (HILS4CN) inherits most of the state-of-the-art attributes of control software including modularity, flexibility, GUI-conformant user-friendliness, and multiuser capability. Besides its virtual boundary, the operational range of HILS4CN has also been extended in terms of incorporating the online management functions such as winking, installation, ad monitoring, etc., in order to achieve online extendibility and scalability. The utility of the developed tool is tested through case studies with two exemplar platforms such as a printed circuit board drilling machine and semiautonomous mobile robotic systems.

In practical communication environments, it is frequently observed that the underlying noise distribution is not Gaussian and may vary in a wide range from short-tailed to heavy-tailed forms. To describe partially known noise distribution densities, a distribution class characterized by the upper-bounds upon a noise variance and a density dispersion in the central part is used. The results on the minimax variance estimation in the Huber sense are applied to the problem of asymptotically minimax detection of a weak signal. The least favorable density minimizing Fisher information over this class is called the Weber-Hermite density and it has the Gaussian and Laplace densities as limiting cases. The subsequent minimax detector has the following form: i) with relatively small variances, it is the minimum L2-norm distance rule; ii) with relatively large variances, it is the L1-norm distance rule; iii) it is a compromise between these extremes with relatively moderate variances. It is shown that the proposed minimax detector is robust and close to Huber's for heavy-tailed distributions and more efficient than Huber's for short-tailed ones both in asymptotics and on finite samples

In practical communication environments, it is frequently observed that the underlying noise PDF is not Gaussian and may vary in a wide range from short-tailed to heavy-tailed forms. To provide stable and high quality detection of a known signal, we design an asymptotically minimax (in the Huber sense) minimum distance detection rule under rather general conditions of regularity imposed upon noise PDFs and derive the closed expression for its probability of detection error. In several PDF classes, the least favorable PDFs and corresponding minimax detectors are written down. The minimax robust detectors exhibit robustness of detection in heavy-tailed noise and efficiency in short-tailed noise, both in asymptotics and on finite samples.

Ranging in wireless access is the process to acquire up-link synchronization, control the power between personal subscriber station and base station and perform the bandwidth request to BS. In this paper, we evaluate the capacity of a ranging subchannel in terms of the ranging code error probability versus the number of active users to attempt ranging, referring to specifications for the Korea's 2.3 GHz band wireless broadband portable Internet service based on the IEEE 802.16-2004 standard. We consider the additive white Gaussian noise and the two-ray Rayleigh fading channels. The result shows that the capacity in the case of two-ray Rayleigh fading channel decreases about one-third, comparing with that in the case of additive white Gaussian noise channel.

Ranging in wireless access is the process to acquire up-link synchronization, control the power between personal subscriber station and base station and perform the bandwidth request to BS. In this paper, we evaluate the capacity of a ranging subchannel in terms of the ranging code error probability versus the number of active users to attempt ranging, referring to specifications for the Korea's 2.3 GHz band wireless broadband portable Internet service based on the IEEE 802.16-2004 standard. We consider the additive white Gaussian noise and the two-ray Rayleigh fading channels. The result shows that the capacity in the case of two-ray Rayleigh fading channel decreases about one-third, comparing with that in the case of additive white Gaussian noise channel.

In this paper, we consider multiple quality of service (QoS) support by using modified largest weighted delay first (M-LWDF) discipline in the adaptive resource allocation of the orthogonal frequency division multiplexing (OFDM) multiple access (OFDMA) systems. We propose a M-LWDF (M Andrews et al., Feb. 2001) based on subchannel assignment, which can satisfy different QoS requirements of services including delay-sensitive and data rate-sensitive traffics in OFDMA systems. The simulation shows that the proposed M-LWDF based subchannel assignment provides controlled QoS provisions while maintaining both the stability of scheduling discipline and the flexibility of the multiple QoS support.

In order to investigate effects of fast frequency hopping multiple access (FHH-MA) systems due to the frequency and timing offset, we evaluate the bit error rate (BER) performance of the FFH-MA system using noncoherent M-ary frequency shift keying (FSK) modulation in the Rayleigh fading channel. While the frequency or timing offset increases at a given SNR, the BER is severely degraded. When the system is affected only by either of two offsets, and normalized offset is less than 0.3, the timing offset has a worse influence upon the FFH-MA system than the frequency offset. For the SNR of more than 20 dB, the threshold level of the receiver suffering from the frequency and timing offsets should be greater than that of the perfectly synchronized receivers.

In this paper, we propose a MAC architecture for IEEE 802.11-like WLANs supporting multimedia services. The main characteristics of the proposed MAC procedure are the period restriction and DCF/SC (distributed coordination function with shortened contention-windows) instead of the PCF (point coordination function) of the IEEE 802.11 standards. We investigate the performance of the proposed MAC mechanism in terms of utilization, throughput, latency and jitter under two multimedia network environments considered by the IEEE 802.11-task group E. These environments are home and enterprise. In the simulated performance, this novel approach, which preserves the traffic classification but increases the channel utilization, thus guarantees QoS (quality of service) of multimedia traffic.

In this paper, we investigate two packet scheduling schemes over the downlink of DS/CDMA systems to support packet data services. These schemes are the code division multiplexing (CDX)-based packet scheduling and the time division multiplexing (TDX)-based packet scheduling. To evaluate each scheme more effectively, we derive the throughput gain of the downlink as a performance measure based on the power constraint equation. As the downlink capacity is quite related to the orthogonality factor, our analysis shows from the results that the throughput gain is highly dependent on this factor. Furthermore, it is shown that the TDX scheduling scheme in CDMA downlink affords better performances than the CDX scheduling scheme, except when the orthogonality factor is around 1.

The multiple input-queued (MIQ) switch is the switch which manages multiple (m) queues in each input port, each of which is dedicated to a group of output ports. Since each input port can switch up to m cells in a time slot, one from each queue, it hardly suffers from the head-of-line (HOL) blocking which is known to be the decisive factor limiting the throughput of the single input-queued (SIQ) switch. As a result, the MIQ switch guarantees enhanced performance characteristics as the number of queues m in an input increases. However, the service of multiple cells from an input could cause internal speedup or expansion of the switch fabric, diluting the merit of high-speed operation in the conventional SIQ scheme. The restricted rule is contrived to circumvent this side effect by regulating the number of cells switched from an input port. We analyze the performance of the MIQ switch employing the restricted rule. For the switch using the restricted rule, the closed formulas for the throughput bound, the mean cell delay and average queue length, and the cell loss bound of the switch are derived as functions of m, by generalizing the analysis for the SIQ switch by J.Y. Hui and E. Arthurs (see IEEE J. Select. Areas Commun., vol.SAC-5, p.1262-73, 1987).

This paper proposes a delay and data rate decoupled fair queueing scheme for wireless multimedia, where two separate scheduling algorithms are applied respectively for real time and non-real time flows. For real time flows, we propose an explicit-delay-guarantee algorithm to guarantee the delay deadline, while a conventional fair queuing algorithm is adopted for non real time flows to guarantee fairness and throughput requirements. In erroneous wireless channel, resource swapping is further adopted to guarantee the required quality of service. In addition, a real time flow can easily react to varying channel error condition by controlling the transmission order without degrading the performance of other real time flows. Through simulations, it is shown that the proposed scheme provides not only improved performance in terms of delay but also simplified control operation in dynamic channel error condition.

In order to extend fair queueing algorithms to wireless networks, we propose a channel error and handoff compensation scheme based on a compensation session with a priority swapping mechanism. The proposed compensation scheme provides a short-term fairness guarantee for an error-free session, long-term fairness guarantee for an erroneous session, fast handoff and traffic-specific control.

The upper bound on the pairwise error probability of MTCM/CPFSK with coherent detection is derived using a linear transformation for orthogonalizing the autocorrelation matrix of Rayleigh fading process with perfect CSI in the presence of an additive white Gaussian noise and a correlated Rayleigh fading. The analyzed performance well estimates the simulated performance for Doppler frequencies when BER is lower than 10/sup -3/.

Since the interference is related to the capacity and performance of DS/CDMA systems, it is necessary to investigate other-cell-interference characteristics according to the location of a user. In this paper, we specifically analyze the ratio of the intercell interference to the total power received from the own cell in downlink, defined as the other-cell-interference factor, as a function of normalized distance. Additionally, the maximum transmission rate under uniform user distribution throughout the cell is simulated when TDX mode packet scheduling is applied. The results show that a maximum transmission rate up to 7.6 Mbit/s for the privileged user could be supported when the bandwidth is 1.2288 MHz, orthogonality factor is 0.9 and the normalized distance is 0.1.

The multiple input-queued (MIQ) switch is the switch which manages multiple (m) queues in each input port, each of which is dedicated to a group of output ports. Since each input port can attend m arbitration rounds, the switch suffers from a reduced HOL blocking which is known as the decisive factor limiting the throughput of the pure single input-queued (SIQ) packet switch. As a result, the MIQ switch guarantees satisfying performance characteristics as the number of queues m increases. However, the service of multiple cells from an input could cause the internal speedup or expansion of the switch fabric, diluting the merit of high-speed operation in the conventional SIQ scheme. The restricted rule is contrived to circumvent this side effect by regulating the number of cells switched from an input port to just one cell. In this paper we analyze the performance of the MIQ ATM switch employing the restricted rule. For the switch using the restricted rule, the closed formulae for the throughput bound of the switch are derived as the function of m, by generalizing the analysis for the SIQ switch by Hui et al. (1987).

In this paper, we propose a QoS-sensitive admission threshold method for the transmission of the non-real-time data packet in voice/data mixed CDMA systems while guaranteeing the QoS requirements of voice and data calls. The proposed admission scheme fully utilizes the remaining resources after serving the voice users for transmitting non-realtime data packet while meeting the QoS requirements for both services. The system performance of the proposed scheme is measured in terms of the average data throughput, the average delay and the average packet loss probability of data traffic while maintaining the outage probability of voice to be less than the predetermined value. In addition, we investigate the effect of the admission threshold level on the system performances.

We propose the OFDM system with a subchannel power control, which transmits data with a variable power for each subchannel based on the received SNR. The OFDM system, employing a subchannel power control with a grouping coefficient equal to 3, gives about 3 dB gain in E/sub b//N/sub 0/ compared with the OFDM system without the subchannel power control, for either coherent or noncoherent QPSK modulation under the two-ray multipath channel with the mean value of the second-ray's attenuation coefficient equal to 0.3, for the required BER equal to 10/sup -5/.

We propose a 2-stage GSIC scheme considering a strict delay constraint and analyze its BER performance in single and multi-cell DS/CDMA systems. Groupwise power disparity is applied in order to enhance the BER performance. We compare the BER performance, complexity and delay of the proposed 2-stage GSIC scheme with those of both conventional detection scheme and SIC scheme. Analysis results show that the capacity increase obtained by both 2-stage GSIC scheme and SIC scheme is smaller in a multicell model than in a single cell model. BER performance enhancement by the proposed 2-stage GSIC scheme is appropriate regarding the minimal increase in cancellation delay and computational complexity. For example, in a multicell DS/CDMA system, the proposed 2-stage GSIC scheme can enhance the user capacity about 21% at BER=10/sup -2/ with twice the cancellation delay and complexity compared with the conventional detection scheme, while the pure SIC scheme can enhance the user capacity 33% with K and K/sup 2/ times increase in delay and complexity, respectively, where K is the number of concurrent users.

In practice, the DS-CDMA system is equipped with a finite number of channel elements (CEs) that performs the baseband spread signal processing for a given channel in the base station. In this situation, the call blocking can be caused not only by the insufficient number of channel elements but also by the limit of available traffic channels. We focus on analyzing the effect of the limited number of CEs on the Erlang capacity of multimedia DS-CDMA systems in the reverse link when the CDMA cells are sectorized with 3 sectors. For the performance analysis, a multi-dimensional Markov chain model is developed. As a result, the more CE results in the larger Erlang capacity. However, the Erlang capacity is saturated after a certain value of CEs where the call blocking is mainly caused by the insufficient channels per sector.

The author presents an analysis of the cost-effectiveness of discrete Fourier transform processors, based on CORDIC modules such as the bit-serial, parallel with non-redundant and redundant arithmetic, and pipelined. The performance of each processor is analyzed with respect to the time to process one frequency output and the number of modules required. It is shown that the CORDIC-based DFT processor is a prospective solution in VLSI to be used for a wide range of input bit rate.>

A general approach is proposed to resolve the wideband detection problem, which utilizes data in the correlation domain via autoregressive modeling. The structures of Gaussian autoregressive processes are reviewed and applied to the modeling of a sinusoid in additive white Gaussian noise (AWGN). Based upon the output sequences of this adopted model, optimal hypothesis-testing tools are employed, leading to a novel scheme, namely the multiple-correlation-coefficient detector. For a properly selected model, this statistic is shown to be competitive to the spectral-maximum detector. This fact is established analytically as well as through extensive simulations. Connections to the other detectors in the correlation domain are also established by means of this model-based approach.>

Optimal and suboptimal decision rules for the detection of constant-envelope quadrature digital modulations in broadband noise are derived and analyzed. The effect of various stochastic models for the carrier phase is examined in detail, while no epoch or frequency uncertainty is assumed. The delay-and-multiply type of detector is considered. A new binary/quadrature phase shift keying (BPSK/QPSK) classifier is compared to the more traditional ad hoc techniques of a square-law classifier and a phase-based classifier (weighting on the phase histogram). The new classifier is derived by approximating the likelihood-ratio functionals of phase-modulated digital signals in white Gaussian noise, hence is named the quasi-log-likelihood ratio (qLLR) rule. It is shown analytically that its performance is significantly better than that of intuitively designed phase-based rules or the conventional square-law classifier.>