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The digital trunking system has the characteristics that the calling mode is mainly group calling and the communication mode is mostly half duplex. For the problem that the traditional user classification method couldn't meet the classification requirements of digital cluster users, this paper proposed a digital cluster user classification method based on improved RFM model. Firstly, it introduced the average speech duration attribute to establish the recency vitality speak (RVS) model. Then, it used the analytic hierarchy process to determine the weight of each parameter in the model. Finally, it used the K-means + + clustering algorithm to classify digital cluster users. The simulation result shows that, by using the user classification method proposed in this paper, the accuracy of digital cluster user classification can reach more than 87. 9% . [ABSTRACT FROM AUTHOR]

For the security problem of the spread of digital image and the digital image encryption from plaintext and too depend on the chaotic systems, this paper proposed a digital image encryption and monitoring algorithm combined with plaintext-related chaotic mapping and SHA-256. The algorithm used the SHA-256 algorithm to calculate the hash value as record to monitor the spread of digital image. Lorenz chaotic mapping generated the corresponding cryptogram by using forward diffusion, associated plaintext scrambling and backward diffusion to encrypt the digital image. The results show that the algorithm can resist many attacks and achieve the security and concealment of image propagation. [ABSTRACT FROM AUTHOR]

The diverse application vertices of internet-of-things (IoT) including internet of vehicles (IoV), industrial IoT (IIoT) and internet of drones things (IoDT) involve intelligent communication between the massive number of objects around us. This digital transformation strives for seamless data flow, uninterrupted communication capabilities, low latency and ultra-high reliability. The limited capabilities of fifth generation (5G) technology have given way to sixth generation (6G) wireless technology. This paper presents a dynamic cell-free framework for a 6G-enabled IoT network. A number of access points (APs) are distributed over a given geographical area to serve a large number of user nodes. A pilot-based AP selection (PBAS) algorithm is proposed, which offers robust resource control through AP selection based on pilots. Selecting a subset of APs against all APs for each user node results in improved performance. In this paper, the performance of the proposed transmission model is evaluated for the achieved data rate and spectral efficiency using the proposed algorithm. It is shown that the proposed PBAS algorithm improves the spectral efficiency by 22 % at the cell-edge and 1.5 % at the cell-center. A comparison of the different combining techniques used at different user locations is also provided, along with the mathematical formulations. Finally, the proposed model is compared with two other transmission models for performance evaluation. It is observed that the spectral efficiency achieved by an edge node with the proposed scheme is 5.3676 bits/s/Hz, compared to 0.756 bits/s/Hz and 1.0501 bits/s/Hz, attained with transmission schemes 1 and 2, respectively. [ABSTRACT FROM AUTHOR]

With the advancement of information technology, the security of digital images has become increasingly important. To ensure the integrity of images, a novel color image-encryption algorithm based on extended DNA coding, Zig-Zag transform, and a fractional-order laser system is proposed in this paper. First, the dynamic characteristics of the fractional-order laser chaotic system (FLCS) were analyzed using a phase diagram and Lyapunov exponent spectra. The chaotic sequences generated by the system were used to design image-encryption algorithms. Second, a modified Zig-Zag confusing method was adopted to confuse the image. Finally, in the diffusion link, the DNA encoding scheme was extended to allow for a greater number of DNA encoding rules, increasing the randomness of the matrix and improving the security of the encryption scheme. The performance of the designed encryption algorithm is analyzed using key space, a histogram, information entropy, correlation coefficients, differential attack, and robustness analysis. The experimental results demonstrate that the algorithm can withstand multiple decryption methods and has strong encryption capability. The proposed novel color image-encryption scheme enables secure communication of digital images. [ABSTRACT FROM AUTHOR]

Steganography methods are considered to be one of the most common technologies for the protection of any digital data when transmitted over open communication channels at a given time. The solution of the problem of digital data protection using steganography methods is used not only by government services, but also by terrorist organizations. Therefore, the need for research, development and continuous improvement of steganoanalytical methods is becoming extremely important. The steganoanalytical algorithm based on the study of the singular decomposition of digital image matrix blocks is proposed in the paper. The main purpose of this paper is to increase the efficiency of digital image steganoanalysis, in the absence of a container, by developing a new steganoanalytical algorithm based on the study of the singular decomposition of digital image matrix blocks. As a result of a detailed study of the steganography algorithm using the singular decomposition of digital image matrix blocks, the statistical characteristics of the singular values of image matrix blocks are established. Based on the defined characteristics, the paper presents the main steps of the stegananoanalytical algorithm. As a criterion for assessing the effectiveness of the developed steganoanalytical algorithm, the probability of detecting additional information was used. Errors of the first and second type are considered. To compare the results of the developed steganoanalytical algorithm with existing algorithms in open access, the following applications are selected: XSteg; StegSpy. The software product "StegoAnalysis" has been implemented for the automated solution of the stegananalytical problem for digital image. [ABSTRACT FROM AUTHOR]

The transmission of high-speed data over communication channels is the function of digital communication systems. Due to linear and nonlinear distortions, data transmitted through this process is distorted. In a communication system, the channel is the medium through which signals are transmitted. The useful signal received at the receiver becomes corrupted because it is associated with noise, ISI, CCI, etc. The equalizers function at the front end of the receiver to eliminate these factors, and they are designed to make them work efficiently with proper network topology and parameters. In the case of highly dispersive and nonlinear channels, it is well known that neural network-based equalizers are more effective than linear equalizers, which use finite impulse response filters. An alternative approach to training neural network-based equalizers is to use metaheuristic algorithms. Here, in this work, to develop the symmetry-based efficient channel equalization in wireless communication, this paper proposes a modified form of bat algorithm trained with ANN for channel equalization. It adopts a population-based and local search algorithm to exploit the advantages of bats' echolocation. The foremost initiative is to boost the flexibility of both the variants of the proposed algorithm and the utilization of proper weight, topology, and the transfer function of ANN in channel equalization. To evaluate the equalizer's performance, MSE and BER can be calculated by considering popular nonlinear channels and adding nonlinearities. Experimental and statistical analyses show that, in comparison with the bat as well as variants of the bat and state-of-the-art algorithms, the proposed algorithm substantially outperforms them significantly, based on MSE and BER. [ABSTRACT FROM AUTHOR]

Theoretically, the spectral efficiency of in-band full-duplex underwater acoustic communications (IBFD-UWAC) is twice that of a half-duplex one. However, the actual achievable spectral efficiency of IBFD-UWAC is determined by the performance of the self-interference cancellation (SIC). In addition, the hostile underwater environment poses a challenge to the tracking performance of the SIC due to its complexity and variability. In this paper, we propose a digital SIC method based on the improved variable step-size least mean square (IVSS-LMS) algorithm where we modify the step-size adjustment criterion in the classical LMS filter and establishes a nonlinear relationship with the Sigmoid function to control the step-size using the instantaneous state error, thus improving the robustness and tracking performance of IVSS-LMS. Hardware-in-loop simulation (HLS) based on Simulink ® platform verifies the real-time implementability and effectiveness of the proposed IVSS-LMS algorithm. Furthermore, the sea trial results show that the digital SIC method based on the proposed algorithm can be implemented in real-time and the convergence speed, and steady-state performance are significantly improved. [ABSTRACT FROM AUTHOR]

With the rapid development and maturity of unconnected communication technology, effector technology, embedded computing technology, and distributed information processing technology, as well as the rapid advancement of digital processing and computing capabilities, unconnected effector Internet has received more and more attention. It is a new type of self-organizing unconnected multihop Internet. With the development and progress of technology and society, the development of unconnected effector Internet is also advancing by leaps and bounds, and it has a wide range of applications in many fields such as military, civil, environmental, medical, and industrial. At present, the research on unconnected effector Internet mainly focuses on the communication protocol, but there is almost no research on input review of unconnected effector Internet. Due to the limited energy of the effector and the limitation of the transmission signal bandwidth, the use of limited resources for input review research in effector Internet is of great significance to the development of unconnected effector Internet. Therefore, this paper studies the input review of unconnected effector Internet based on the L-A model on the on-chip embedded tune system. Because the classic low-power adaptive cluster layering protocol (LEACH) has the problems of unbalanced energy consumption and short node life cycle, this paper uses the embedded tune technology based on the L-A model and analyzes the remaining energy and location of the unconnected effector Internet node. Parameters are tested and studied. Through the research on the input review of unconnected effector Internet, the simulation results obtained show that the research in this paper is feasible and reasonable. [ABSTRACT FROM AUTHOR]

As an emerging technology, the hybrid analog-digital structure has been considered for use in future millimeter-wave communications. Although this structure can reduce the hardware cost and power consumption considerably, the spatial covariance matrix (SCM), as the core of subspace-based direction of arrival (DOA) estimation, cannot be obtained directly. Previously, the beam sweeping algorithm (BSA) has been found effective for reconstructing the spatial covariance matrix and realizing DOA estimation by forming the beams to difference directions. However, it is computationally intractable owing to the high-dimensional matrix operation. To address this problem and improve the DOA estimation performance, this paper applies the nested array to the hybrid analog-digital structure and proposes the enhanced BSA (EBSA) for DOA estimation. By deleting a large number of redundant elements exist in the SCM to be reconstructed, the computational cost can be considerably reduced. Also, the nested array can offer high degrees of freedom. Finally, simulation experiments are conducted to verify the performance of EBSA. The results indicate that the proposed EBSA is better than the state-of-the-art method in terms of estimation accuracy and computational cost. [ABSTRACT FROM AUTHOR]

Monte Carlo computation has been widely applied in the field of dynamic systems. This paper focuses on the general framework in the implementation of sequential importance sampling by combining redrawing, resampling and rejection control simultaneously. The proposed algorithm is named as Redrawing Resampling Rejection Controlled Sequential Importance Sampling (RR-RC-SIS). It can reduce sampling computation and meanwhile maintain the diversity of random samples. Theoretical basis is given to prove that RR-RC-SIS has advantages in comparison with Rejection Controlled Sequential Importance Sampling. It also has practical value as illustrated in numerical simulation on blind deconvolution problem in digital communications. [ABSTRACT FROM AUTHOR]

Today, digital multimedia (audio, video, images) is a common evidential source in litigation and criminal justice proceedings, and, not surprisingly, multimedia forensics is an active research area. One particular challenge faced by multimedia forensic researchers is the lack of a comprehensive and publicly available data-set for evaluating existing and new algorithms. This paper presents a digital audio forensic data-set, designed to facilitate evaluation of audio forensic algorithms (e.g. microphone identification, acoustic environment identification and splice detection). This paper also briefly describes the data-collection settings, microphones, speakers, languages and notations used. Existing tamper-detection techniques rely on artefacts due to recording devices, codec and/or the acoustic environment in the audio in question. Experimental results show that the selected approaches achieved promising results. [ABSTRACT FROM AUTHOR]

In a wireless sensor network, the sensor nodes transmit the acquired information to the server through the data transmission link. On the serverside, the data are processed, fused, and expressed to serve the user. Sensor deployment is a key factor related to the stability and security of wireless networks. This article uses environmental changes to drive related technologies to deploy wireless sensors. In this article, environmental change-driven means that through certain deployment cost model assumptions and problem descriptions, network deployment is artificially divided into two stages: initial deployment and redeployment. In the deployment phase, by referring to the idea of virtual force, a new sensor deployment algorithm is proposed in the redeployment phase, which can well solve the stability- and security-related issues encountered in agricultural wireless sensor networks. In this algorithm, the moving distance of the mobile receiver and the average coverage of the network are calculated based on the virtual force, the direction, and the number of adjacent clusters. Finally, the algorithm model was simulated in MATLAB, and the feasibility of the algorithm was verified by analyzing the event coverage and the moving distance of nodes. The final simulation results show that the algorithm proposed in this paper can achieve better performance than existing algorithms in terms of average coverage and moving distance. [ABSTRACT FROM AUTHOR]

In order to solve the issue of malicious phonily occupying seats for some ticket agents or passengers in the process of air ticket sales, this paper proposed a blockchain system scheme based on the improved PoA consensus mechanism. The scheme used the alliance blockchain as a communication platform among airlines, adopted credit points and dynamic grading to build a new PoA consensus mechanism, protected passengers ' private information with hash algorithm, and achieved digital storage of ID information, registration of passengers, storage and sharing of passenger booking information for airline corporations relying on smart contracts. The prototype system trial operation shows that the system can timely detect and effectively stop the phonily occupying seats behavior. After analysis and evaluation, the program has the characteristics of privacy protection, decentralization and high security, and provides a new reference to solve the long-standing problem of phonily occupying seats in the civil aviation field. [ABSTRACT FROM AUTHOR]

This paper models the downlink Fifth Generation (5G) network that supports a flexible frame structure and a shorter Round-Trip Time (RTT) for Hybrid Automatic Repeat Request (HARQ). Moreover, the design of the renowned Time Division Multiple Access (TDMA) packet scheduling algorithms is revised to allow these algorithms to support packet scheduling in the downlink 5G. Simulation results demonstrate that the Proportional Fair provides a comparable performance to the delay-aware Maximum-Largest Weighted Delay First for simultaneously providing the desired transmission reliability of the Guaranteed Bit Rate (GBR) and Non-Guaranteed Bit Rate (Non-GBR) healthcare contents whilst maximizing the downlink 5G performance. [ABSTRACT FROM AUTHOR]

This paper is concerned with the state estimation problem for a class of discrete-time singularly perturbed systems with distributed time-delays. During the data transmission through a network channel of limited bandwidth, for the sake of collision avoidance and energy saving, a dynamic event-triggered scheme is employed to schedule the data communication from the sensors to the designed estimator. First, for a given singular perturbation parameter (SPP), by constructing a novel Lyapunov–Krasovskii SPP-dependent functional, sufficient conditions are obtained to guarantee the exponentially mean-square ultimate boundedness of the error dynamics of the state estimation. Furthermore, in the case that the SPP does not exceed a predefined upper bound, a design algorithm is developed for the desired state estimator ensuring that the error dynamics is exponentially mean-square ultimately bounded. In this case, by solving certain matrix inequalities, the estimator gain is characterized without needing to know the exact SPP (as long as it stays below the given upper bound). Moreover, the ultimate bound of the error dynamics is estimated. Finally, simulation results are given to confirm the validity and advantages of the proposed design scheme of the state estimator. [ABSTRACT FROM AUTHOR]

This paper studies how a group of delivery workers in Barcelona were able to organize a successful traditional and a social media strategy in order to claim for their rights as waged workers. They created a union, RidersxDerechos, and they also decided to create a worker's cooperative, Mensakas, with their own application and algorithm. We will study how they were able to re-appropriate technology and to use digital communities to spread alternative discourses. We have used different methodologies: traditional content analysis in Media, debate analysis in Social Media, qualitative ethnography. We noticed that RidersxDerechos access to media was very successful (300 piece of news analyzed) thanks to strikes and court trials, facilitating a change of perspective in the treatment of platform economy in Media. Media were following up the digital entrepreneurship rhetoric until then. Along with the traditional media strategy they developed a diversified communicative pathway in social media (Twitter, Instagram, Facebook, and Goteo) that helped them to establish alliances with riders from other cities and countries. We focused on more than 25.000 tweets. Finally, they proposed a new way to use technology by creating their own app and algorithms for their working cooperative, Mensakas. Crowdfunding was also used to fund it and to spread an alternative working storytelling from Silicon Valley's. [ABSTRACT FROM AUTHOR]

This paper proposed a twice channel estimation algorithm, in which used weighted coefficient to cancel ICI caused by Doppler frequency shift in high speed mobile environment. The algorithm achieved twice channel estimation. The first estimation provided channel state information to cancel the ICI under the premise of ensuring the symbol rate. In the case of ICI cancellation, the second estimation enhanced the channel estimation accuracy. Then the algorithm improved the simplified PIC algorithm, and introduced the weighting coefficient to make the residual error smallest after ICI cancellation based on the minimum mean square error criterion. The simulation results are in good agreement with the theoretical analysis. The proposed algorithm improves the estimation accuracy of rapidly time-varying channels. The maximum value of NMSE performance gain is0. 071 4, when the SNR is 0 dB. [ABSTRACT FROM AUTHOR]

Orthogonal frequency-division multiplexing (OFDM) is one of the most successful digital communication techniques. Nevertheless, the decrease in inter-symbol interference in quadrature amplitude modulation (QAM) over dispersive channels is still challenging. Different researches recently proposed the idea of using unsupervised learning as an alternative to the classic approaches to equalization of OFDM channels. In those purposes, the identification of a received QAM symbol is possible by the comparison of its position on the in-phase/quadrature (IQ) plane relative to the positions of previously arrived symbols, generally processed by the Kohonen’s Self-Organizing Map (SOM) algorithm. This work presents the SOM unsupervised learning method executed on an embedded system applied to QAM symbols identification. The system is implemented on an FPGA, a configurable digital circuit able to meet the low power and parallel process requirements of mobile applications. Also, in order to extend the classical set of experiments to evaluate our system, this paper proposes a theoretical model of the time-varying scheme representing the transition between different channel characteristics, obtained from real measurements available on a public repository. The model is employed to verify our purpose under dynamically both changing and realistic conditions. On the assumption that it is provided enough IQ symbols for the initial training process, the hardware implementation of SOM is able to track and identify the time-varying distorted QAM constellation. No knowledge of channel characteristics is necessary. The system spends only some microseconds at start-up to reach about 100% performance, and no dedicated training phase is needed afterward. [ABSTRACT FROM AUTHOR]

Phase noise poses a serious challenge for high-speed digital communications systems mainly when going to higher and higher carrier frequencies, such as in satellite communications. Traditionally, phase noise estimation was performed separately from the decoding task and it was shown, recently, that there is much to be gained from joint estimation and decoding, particularly when using LDPC (low-density parity check)/turbo codes. However, jointly estimating phase noise and decoding is a very complex and computationally demanding task. In this paper, we propose several algorithms based on the sum and product algorithm (SPA) for low complexity joint decoding and estimation of coded information in strong phase noise channels. These algorithms are based on a novel approximation of SPA messages as Tikhonov mixtures of a given order. Since mixture-based Bayesian inference such as SPA, creates an exponential increase in mixture order for consecutive messages, a mixture reduction scheme is a must. Therefore, in this paper, we propose a low complexity mixture reduction algorithm, which provably satisfies an upper bound on the Kullback Leibler (KL) divergence between the mixture and the reduced mixture. We then reduce the complexity even further, including limiting the model order and reducing the clustering effort to simple component selection. As an extreme case, it is even possible to reduce the number of modes to one. We show the relation between the simplified algorithm to the phase locked loop (PLL). Finally, we show simulation results and complexity analysis for the proposed algorithms, which show superior performance over other state of the art low complexity algorithms. [ABSTRACT FROM AUTHOR]

The new High Efficiency Video Coding (HEVC) standard is targeted for high-resolution video contents that are suitable for many high-delay video communications applications, such as video streaming. A few-rate control algorithms (RCAs) have been proposed for the HEVC in the literature. Almost all state-of-the-art RCAs proposed for the HEVC are optimized for constant bit rate low-delay applications. In order to reach a higher visual quality in high-delay applications, such as video streaming, a proportional integral derivative (PID)-fuzzy RCA with the buffering constraint is proposed for the HEVC in this paper. The proposed RCA is designed to minimize fluctuations of quantization parameter (QP) while the buffering constraints are fully obeyed. Unlike conventional fuzzy-PID algorithms that use a PID controller for control and a fuzzy system for tuning the PID parameters, the proposed algorithm uses a fuzzy controller with proportional, integral, and derivative inputs. A base QP is calculated for each group of picture (GOP) by the PID-fuzzy controller and determined QP offsets are added to the base QP to obtain the QP of frames at different temporal layers in the GOP. Experimental results indicate that high rate-distortion performance, fulfilled buffering constraint, and the high visual quality of compressed video are gained simultaneously by the proposed algorithm with low computational complexity. [ABSTRACT FROM AUTHOR]

In this paper, we propose an energy efficient approximate multiplier design obtained by truncating the input operands. In the structure, the n-bit multiplication operation is transformed to a smaller bit length multiplication plus some add and shift operations. The simple calculation core makes the multiplier a scalable yet low power structure. Also, we suggest an output quality-tunable multiplier providing ability to change the output quality during the multiplication operation. The characteristics of the proposed multiplier are compared with those of the exact and some other approximate multipliers in a 45 nm technology. The comparison reveals an average improvement of 89.2% (74.9%) in terms of the energy (area) compared to that of the exact multiplier. The utility of the proposed multiplier in a JPEG encoder application is also investigated. The results reveal that the Peak Signal to Noise Ratio (PSNR) reduction is at most 0.15 dB compared to that of the exact one. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the energy efficiency of downlink transmissions in heterogeneous networks. Our objective is to satisfy the rate requirement of users while maximizing the energy efficiency of the network. We employ the fractional frequency reuse (FFR) scheme to increase the energy efficiency of downlink transmissions and to eliminate outages for the cell-edge users. We formulate the joint cell-center boundary selection for FFR, scheduling, and power allocation problems. This formulation gives us a mixed discrete (selection of the cell-center boundary selection for FFR and scheduling) and continuous (power allocation) optimization problem which is hard to solve jointly. In order to solve this problem, we propose a three-stage resource allocation algorithm. In the first stage, we propose a dynamic method to determine the cell-center region boundaries. In the second stage, we employ the Lagrangian-directed scheduler algorithm to incorporate the rate requirements of users. The third stage solves the power allocation subproblem using the Levenberg–Marquardt method combined with dual decomposition. In order to make the base stations further reduce intercell interference, interference pricing mechanism is applied. This scheme penalizes the utility of a base station with the interference it creates. The performance of the proposed algorithm is simulated in a long-term evolution (LTE) network simulation tool. Our numerical results reveal that significant gains in terms of energy efficiency can be achieved with the proposed algorithm. The outage probability is also significantly reduced. [ABSTRACT FROM AUTHOR]

SUMMARY Computational capability of wireless sensor network (WSN) significantly facilitates application of dense sensory arrays, which is increasingly important in health monitoring of large-scale structural systems. As the wireless sensor technology improves, more complicated tasks can be assigned to sensing units, and the communication between sensing nodes and their base station can be minimized, utilizing in-network processing. This strategy should be used to address WSN challenges, such as limited communication bandwidth and prohibitive power consumption, associated with wireless communication and battery power. An iterative modal identification algorithm is proposed in this paper, which uses the on-board processors for estimation of system parameters through iteration cycles. The iterative algorithm was originally developed such that each individual sensor, having an initial estimate of the system parameters, its local measurement, and the excitation signal, updates the estimated model and passes it through the network until convergence. This study further improves the algorithm to eliminate its limitations in need for availability of excitation load and initial estimate of the system parameters. As a result, the algorithm is applicable for modal identification of structural systems under ambient loading without need for prior information about the system parameters. The development of the algorithm is presented in this paper and validated through implementation on a numerically simulated example and a laboratory experiment. Furthermore, its performance is evaluated using data from an ambient vibration test of the Golden Gate Bridge using a WSN. Results of these implementations verify the functionality of the algorithm in monitoring of real-life structural systems. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The problem of two node-disjoint paths is to identify two paths and from source to target without any common intermediate node in a communication network , where each node (vertex) in denotes a process and each edge denotes a communication channel between nodes and . In this paper, we present the first adaptive stabilizing algorithm for finding a pair of node-disjoint paths in a semi-anonymous arbitrary network in rounds and the state-space complexity is bits per process, where is the diameter of the communication network. The algorithm assumes weakly fair distributed daemon and the knowledge of an upper bound on the number of processes by each process. If two disjoint paths exist between and , two disjoint paths are guaranteed to be constructed. In addition, the algorithm detects if two node-disjoint paths exist or not. Since the proposed algorithm is stabilizing, it does not require initialization and is capable of withstanding transient faults. We view a fault that perturbs the state of the system but not its program as a transient fault. The proposed algorithm has a wide range of applications in ensuring reliability and security of sensor, mobile and fixed communication networks. [ABSTRACT FROM AUTHOR]

Comprehension of the statistical and structural mechanisms governing human dynamics in online interaction plays a pivotal role in online user identification, online profile development, and recommender systems. However, building a characteristic model of human dynamics on the Internet involves a complete analysis of the variations in human activity patterns, which is a complex process. This complexity is inherent in human dynamics and has not been extensively studied to reveal the structural composition of human behavior. A typical method of anatomizing such a complex system is viewing all independent interconnectivity that constitutes the complexity. An examination of the various dimensions of human communication pattern in online interactions is presented in this paper. The study employed reliable server-side web data from 31 known users to explore characteristics of human-driven communications. Various machine-learning techniques were explored. The results revealed that each individual exhibited a relatively consistent, unique behavioral signature and that the logistic regression model and model tree can be used to accurately distinguish online users. These results are applicable to one-to-one online user identification processes, insider misuse investigation processes, and online profiling in various areas. [ABSTRACT FROM AUTHOR]

In conventional digital communication systems, the quality of the received signal does not improve beyond a certain level as the channel quality increases. Such kind of quality saturation effect is caused by the unrecoverable quantization errors produced by source coding. The Hybrid Digital-Analog (HDA) transmission, where the quantization errors are transmitted in an analog mode along with the quantized data in a digital mode, has been recognized as an effective technique to combat the quality saturation effect. In this paper, we introduce HDA transmission in Wireless Relay Networks (WRNs) over Rayleigh slow-fading channels to eliminate the quality saturation effect and achieve graceful improvement for the better channel quality. Our goal is to minimize the end-to-end distortion by optimal power allocation. We note that digital-analog power allocation involved in HDA transmission is coupled with source-relay power allocation in WRNs. Therefore, the joint power allocation problem should be considered. We investigate this problem for two kinds of relays in WRNs, i.e., Amplify-and-Forward (AF) relays and Decode-and-Forward (DF) relays. In the case of AF relays, we find that the joint power problem is concave and thus derive the explicit expressions of the optimal solution. In the case of DF relays, we formulate the joint power allocation problem as a nonlinear fractional programming problem and then propose an efficient algorithm to search the optimal solution. Simulation results show that the proposed joint power allocation schemes outperform existing schemes in terms of end-to-end distortion in both WRNs with AF relays and that with DF relays under various channel conditions. [ABSTRACT FROM AUTHOR]

This paper introduces a novel analytical model for analyzing the performance of handoff algorithms based on absolute and relative signal strength measurements. The performance is analyzed in multicell and multisector environments where cochannel interference (CCI) is present. The model presented in this paper accounts for the distinct features of intersector handoff compared with intercell handoff. Numerical results show that the performance metrics are affected by the CCI level. The occurrence condition of unnecessary handoffs in multisector systems is also presented. [ABSTRACT FROM AUTHOR]

This paper considers a scheduling problem for multi-user transmissions over the downlink of a time-slotted cellular data network. For such a network, opportunistic scheduling exploits the time-varying radio channel and improves network performance. This paper presents a new scheduling solution that maximizes the aggregate user performance subject to certain minimum and maximum performance constraints. By constraining the performance experienced by individual users, who share a common radio downlink, to some upper bounds, it is possible to provide the system operator with a better control of radio resource allocations and service differentiation among different classes of users. The proposed solution, which is referred to as Throughput Constrained Opportunistic Scheduling (TCOS), offers better service differentiation among different classes of users than the existing opportunistic scheduling algorithms with only minimum performance constraints. For ideal memoryless fading channels, TCOS provides performance comparable with an existing scheme with minimum and maximum performance constraints. For realistic fading channels with memory, TCOS significantly improves system performance due to its ability to trade off feasibility with throughput. Extensive simulation results demonstrate the improved system performance and effective service differentiation of the proposed solution under realistic channel conditions. [ABSTRACT FROM AUTHOR]

This paper presents an analysis framework for estimating spatio-temporal distortion associated with data-gathering algorithms in sensor networks. We assume that the underlying data field being sensed is spatially and temporally correlated and that the sink node performs real-time reconstruction of the field. Unlike existing work, the proposed analysis framework assumes realistic transmission schemes and network/routing parameters, such as congestion and limited transmission range. Our simulations show that, even for a simple collision-free transmission scheme and regular deployment patterns, the distortion analyses yield starkly different results, compared with the analyses performed in the absence of these assumptions. The analytical method presented in this paper could easily be extended to consider the real-time data-reconstruction problem under different transmission schemes, node distributions, and reconstruction methods. [ABSTRACT FROM AUTHOR]

Performance assessment and large-scale monitoring of terrestrial digital video broadcasting (DVB-T) transmission apparatuses are currently a pressing need due to the rapid growth of related broadcasting networks in many countries. Power measurements, in particular, play a very important role since RF and IF signal power, RF channel power, RF and IF power spectrum, noise (or unwanted) power, and power efficiency are relevant parameters to be measured as accurately as possible. Although modern spectrum analyzers and high-performance vector signal analyzers exhibit satisfying accuracy and repeatability, their cost, weight, and size make them unsuitable for the purpose. This paper is focused on the design and realization of a digital signal processing-based meter for power measurement in DVB-T systems that is capable of granting good accuracy, satisfying repeatability, reduced measurement time, and cost effectiveness. This paper deals with the digital signal processing algorithm to be implemented in the meter, paying attention to parametric power spectral density (PSD) estimators for their reduced memory requirement and potentially limited computational burden. In particular, a parametric estimation algorithm that is capable of assuring a fast measurement rate is implemented and made operative. The simulation and emulation stages are properly designed to regulate the most relevant parameters of the adopted PSD estimators according to the specific features of the signals involved; a number of experiments on actual DVB-T signals are conducted, the results of which are compared to those provided by competitive measurement solutions. [ABSTRACT FROM AUTHOR]

Recently there has been an increasing interest in active fault detection when traditional approaches are not effective or cannot be used. Previous papers have shown how to construct continuously varying test (auxiliary) signals for use in fault detection and identification. Such signals may not always be easy to implement. In this paper a new algorithm is presented to compute optimal piecewise constant test signals. In the important case where the test signal changes values a small number of times, the new test signals can be both smaller and more effective than test signals computed by other means. Two computational examples are given to illustrate both computational issues and differences between different types of piecewise constant signals. [ABSTRACT FROM AUTHOR]

The paper presents an admission approach for IPTV service providers that is designed to minimize QoS violations whilst effectively utilizing available bandwidth. Central to the approach is an empirical method of estimating the effective bandwidth required to satisfy QoS targets for admitted traffic flows. The paper describes this method and specifies two admission control algorithms based on the use of effective bandwidth estimates. The first algorithm employs a simple evaluation of whether there is sufficient bandwidth available to ensure, with an appropriate degree of confidence, that QoS targets will not be violated if a requested flow is admitted. The second algorithm utilizes information relating to the cost, duration and request frequency of specific IPTV content to prioritize higher revenue flows within the admission control process. Results of a simulation study (employing real traffic traces of long-lived flows) indicate that the proposed algorithms ensure that an adequate, but not overly generous, amount of bandwidth is allocated to ensure that QoS targets for accepted flows are met. Furthermore, they demonstrate the potential advantage of using content specific information in the admission control process to maximize generated revenue. [ABSTRACT FROM AUTHOR]

With increasing richness in features such as personalization of content, Web applications are becoming more complex and, hence, computationally intensive. Traditional approaches toward the design of Web cluster architectures have targeted static content such as images that are usually network intensive. However, these methods are not applicable to dynamic-content applications, which are more computationally intensive than static content. This paper proposes a suite of algorithms that optimize the performance of dynamic- content applications by considering both server CPU loads and network latencies. The goal of the algorithms is to reduce client access times while also minimizing the resource utilization. The algorithms are designed for a hosting architecture comprising a grid of clusters interconnected via high-bandwidth links, with each cluster hosting a complete application replica. A server migration algorithm allocates servers on-demand within a cluster, while a server selection mechanism enables statistical multiplexing of resources across clusters by redirecting requests away from overloaded clusters. The paper also proposes a cluster decision algorithm that decides between serving a request locally after migrating in additional servers at the local cluster or serving it remotely by redirecting the request to a remote server that can serve the request earliest. Through a combination of analytical modeling, simulation over traces from large e-commerce sites, and testbed implementation, we explore the performance savings achieved by the proposed algorithms. [ABSTRACT FROM AUTHOR]

In the current network and big data environment, the secure transmission of digital images is facing huge challenges. The use of some methodologies in artificial intelligence to enhance its security is extremely cutting-edge and also a development trend. To this end, this paper proposes a security-enhanced image communication scheme based on cellular neural network (CNN) under cryptanalysis. First, the complex characteristics of CNN are used to create pseudorandom sequences for image encryption. Then, a plain image is sequentially confused, permuted and diffused to get the cipher image by these CNN-based sequences. Based on cryptanalysis theory, a security-enhanced algorithm structure and relevant steps are detailed. Theoretical analysis and experimental results both demonstrate its safety performance. Moreover, the structure of image cipher can effectively resist various common attacks in cryptography. Therefore, the image communication scheme based on CNN proposed in this paper is a competitive security technology method. [ABSTRACT FROM AUTHOR]

A novel robust adaptive beamformer, formulated as a semidefinite programming (SDP) problem, is proposed in this paper. With new constraints on the magnitude response, the beamwidth and response ripple of the robust response region can be well controlled. Moreover, only a small part of these inequality constraints on the magnitude response are active during optimization so that few degrees of freedom (DOF5) of the adaptive beamformer are consumed. Consequently, the resultant beamformer has significant improvement on signal-to-interference-plus-noise ratio (SINR). An important problem in the proposed beamformer is how to generate the array weight vector from the optimal semidefinite matrix. In this paper, a method utilizing the extended spectral factorization method is proposed to solve this problem. Simple implementation, flexible performance control as well as significant SINR enhancement support the practicability of the proposed method. [ABSTRACT FROM AUTHOR]

The combination of the famed kernel trick and the least-mean-square (LMS) algorithm provides an interesting sample-by-sample update for an adaptive filter in reproducing kernel Hubert spaces (RKHS), which is named in this paper the KLMS. Unlike the accepted view in kernel methods, this paper shows that in the finite training data case, the KLMS algorithm is well posed in RKHS without the addition of an extra regularization term to penalize solution norms as was suggested by Kivinen [Kivinen, Smola and Williamson, "Online Learning With Kernels," IEEE Transactions on Signal Processing, vol. 52, no. 8, pp. 2165-2176, Aug. 2004] and Smale [Smale and Yao, "Online Learning Algorithms," Foundations in computational Mathematics, vol. 6, no. 2, pp. 145-176, 20061. This result is the main contribution of the paper and enhances the present understanding of the LMS algorithm with a machine learning perspective. The effect of the KLMS step size is also studied from the viewpoint of regularization. Two experiments are presented to support our conclusion that with finite data the KLMS algorithm can be readily used in high dimensional spaces and particularly in RKHS to derive nonlinear, stable algorithms with comparable performance to batch, regularized solutions. [ABSTRACT FROM AUTHOR]

This paper deals with a crucial aspect in the control of grid-connected power converters, i.e., the detection of the fundamental-frequency positive-sequence component of the utility voltage under unbalanced and distorted conditions. Specifically, it proposes a positive-sequence detector based on a new decoupled double synchronous reference frame phase-locked loop (DDSRF-PLL), which completely eliminates the detection errors of conventional synchronous reference frame PLL's (SRF-PLL). This is achieved by transforming both positive- and negative-sequence components of the utility voltage into the double SRF, from which a decoupling network is developed in order to cleanly extract and separate the positive- and negative-sequence components. The resultant DDSRF-PLL conducts then to a fast, precise, and robust positive-sequence voltage detection even under unbalanced and distorted grid conditions. The paper presents a detailed description and derivation of the proposed detection method, together with an extensive evaluation using simulation and experimental results from a digital signal processor-based laboratory prototype in order to verify and validate the excellent performance achieved by the DDSRF-PLL. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the synthesis of signals which have a power spectral density (PSD) equal to . It is well known that a linear infinite line of RC cells can generate such signals. For a finite number of cells, the spectrum is not perfect. Here, we propose a novel method which enables the control of the precision within a frequency bandwidth. The algorithm proposed in the paper is based on a geometric approach. A cluster of elementary cells is designed. Each cell is defined by two parameters (the two cut off frequencies) which are easily computed through recursive formulae. The digital conversion requires the analog to digital open loop design method. Finally, sample paths are generated and their PSD compared to . [Copyright &y& Elsevier]

In this paper, a method is proposed to construct spectrally efficient unitary space-time codes for high-rate differential communications over multiple-antenna channels. Unlike most of the known methods which are designed to maximize the diversity product (the minimum determinant distance), our objective is to increase the spectral efficiency. The simulation results indicate that for high spectral efficiency and for more than one receive antenna, the new method significantly outperforms the existing alternatives. In the special case of two transmit antennas, which is the main focus of this paper, the relation between the proposed code and the Alamouti scheme helps us to provide an efficient maximum-likelihood (ML) decoding algorithm. Also, we demonstrate that similar ideas can be applied to designing codes for more than two transmit antennas. As an example, we present a construction for 4-by-4 unitary constellations which has a good performance, compared with the other known codes. [ABSTRACT FROM AUTHOR]

This paper describes the design and implementation of simple fuzzy logic controller (SFLC) for a nonlinear quasi-resonant converter (QRC). It is shown that the two-dimensional rule table of conventional FLCs (CFLCs) used in power converters can be reduced to one-dimensional rule table using SFLC. The proposed SFLC reduces the memory space and computing time of the fuzzy algorithm. The tuning of scaling factors and the generation of fuzzy rules are also easier when compared with CFLC. As a result, realizing SFLC in a Microcontroller or Digital Signal Processor (DSP) is made simple. The proposed controller structure is universal and it can be directly applied to any of the dc–dc converter topologies. In this paper, the application of SFLC is successfully verified for the voltage control of Extended Period (EP)-ZCS/ZVS-QRC through simulation and experimental studies using TMS320F2407A Processor. The ability of SFLC, compared to CFLC, to achieve good transient response for load variations and supply disturbances is demonstrated. [ABSTRACT FROM AUTHOR]

Bluetooth networks can be constructed as piconets or scatternets depending on the number of nodes in the network. Although piconet construction is a well-defined process specified in Bluetooth standards, scatternet formation policies and algorithms are not well specified. Among many solution proposals for this problem, only a few of them focus on efficient usage of bandwidth in the resulting scatternets. In this paper, we propose a distributed algorithm for the scatternet formation problem that dynamically constructs and maintains a scatternet based on estimated traffic flow rates between nodes. The algorithm is adaptive to changes and maintains a constructed scatternet for bandwidth-efficiency when nodes come and go or when traffic flow rates change. Based on simulations, the paper also presents the improvements in bandwidth-efficiency and reduction in energy consumption provided by the proposed algorithm. [ABSTRACT FROM AUTHOR]

Abstract: Dynamic channel resource allocation (DCA) exploiting wideband multiuser diversity can provide data transmission with very high spectral efficiency by scheduling at each dimension (time, frequency, space) the user with the best channel conditions. The main issue arising from this allocation is fairness. Base station or users have to wait until their channel is most favorable to transmit. It is commonly considered that fairness comes at the cost of a significant system capacity penalty. In this paper we show that multiuser diversity, and thus an increase of aggregate data rates with the size of the user population, can still be successfully achieved even with deterministic channel use and that even under a hard fairness constraint we can achieve performance which comes close to those of the optimal unfair policy for K-user systems with K parallel sub-channels. We propose and compare different algorithms which perform channel allocation yielding variable-rate/constant-power (Max–Min allocation and maximum total rate allocation) and fixed-rate/variable-power (fixed rate allocation). We show the effect of system bandwidth (and thus sub-channel correlation) on wideband multiuser diversity. This paper also investigates the performance of combined orthogonal channel and antenna allocation algorithms in multiple-antenna multi-channel systems. We extend the proposed Max-Min allocation algorithm to the multiple-antenna systems and compare its performance in two different transmission scenarios (spatial multiplexing and space time coding). An extension of the Max–Min allocation algorithm to the general case of an arbitrary number of users is also given. The proposed techniques are applicable, for instance, in orthogonal frequency division multiple-access (OFDMA) systems with dynamic sub-carrier allocation. [Copyright &y& Elsevier]

The demand for video service in mobile communications systems is increasing. In response to this demand, wireless P-MP (Point-to-MultiPoint) video transmission, in which a given video is transmitted to several moving terminals via a single channel, has been studied. This scheme can make effective use of bandwidth, power, and spreading codes. In this paper, as wireless P-MP video transmission schemes effective in the CDMA system, we propose MCAP (MultiCode Assignment algorithm for P-MP transmission) and the P-MP video transmission system. In MCAP, the mobile terminals receiving the identical video are divided into two groups, high quality and low quality, based on the channel quality. By performing transmission power and transmission rate control for each group, the transmission rate can be improved. Also, by using multicode transmission, transmission rate control and the channel allocation are carried out in a unified fashion. In this paper, by means of simulations, it is demonstrated that the proposed scheme can substantially improve the transmission rate without increasing the number of spreading codes and the power. Several schemes are compared as power control base selection schemes needed for MCAP. An optimum scheme is determined from the comparative evaluation results. © 2006 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 89(8): 14–25, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.20280 [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an investigation of a novel model for parallel evolutionary algorithms (EAs) based on the biological concept of species. In EA population search, new species represent solutions that could lead to good solutions but are disadvantaged due to their dissimilarity from the rest of the population. The Speciating Island Model (SIM) attempts to exploit new species when they arise by allocating them to new search processes executing on other islands (other processors). The long term goal of the SIM is to allow new species to diffuse throughout a large (conceptual) parallel computer network, where idle and unimproving processors initiate a new search process with them. In this paper, we focus on the successful identification and exploitation of new species and show that the SIM can achieve improved solution quality as compared to a canonical parallel EA. [Copyright &y& Elsevier]

In this paper, the authors study the performance of scheduling algorithms exploiting the multiuser selection diversity. Schedulers with affordable-rate transmission and adaptive transmission based on the absolute signal-to-noise ratio (SNR) and the normalized SNR are considered. In contrast to previous studies on the multiuser-diversity systems, the channel dynamics is taken into consideration in this paper by a novel formulation based on the level crossing analysis of stochastic processes. Then, the authors make the connection between the Doppler frequency shift, which indicates the channel temporal correlation, and the average (channel) access time, the average waiting time (AWT) between accesses, and the average access rate (AAR) of active users. These properties are important for the scheduler design, especially for applications where delay is a concern. In addition, analytical expressions for the system throughput and the degree of fairness (DOF) when users have nonidentical average channel conditions are presented. These expressions quantify the effect of disparateness in users' average channel conditions on the system performance. [ABSTRACT FROM AUTHOR]

Reverse link capacity of a direct-sequence code-division multiple-access (DS-CDMA) system in a multicell environment has been studied recently, and significant capacity improvements due to the use of beamforming have been observed. However, system performance with beamforming will be affected by several impairments, such as direction of arrival estimation errors, array perturbations, mutual coupling, and signal spatial spreads. In this paper, reverse link performance of CDMA systems with beamforming under these impairments (imperfect beamforming) is investigated. A simplified beamforming model is developed to evaluate the system performance in terms of user capacity, bit-error rates (BER), and outage probabilities. Both signal-to-interference-ratio-based power control and strength-based power control are considered in this paper. The capacity and BER degradations due to different impairments are shown, and outage probabilities under different power control schemes are examined. [ABSTRACT FROM AUTHOR]

Most embedded systems have limited amount of memory. In contrast, the memory requirements of the digital signal processing (DSP) and video processing codes (in nested loops, in particular) running on embedded systems is significant. This paper addresses the problem of estimating and reducing the amount of memory needed for transfers of data in embedded systems. First, the problem of estimating the region associated with a statement or the set of elements referenced by a statement during the execution of nested loops is analyzed. For a fixed execution ordering, a quantitative analysis of the number of elements referenced is presented; exact expressions for uniformly generated references and a close upper and lower bound for nonuniformly generated references are derived. Second, in addition to presenting an algorithm that computes the total memory required, this paper also discusses the effect of transformations (that change the execution ordering) on the lifetimes of array variables, i.e., the time between the first and last accesses to a given array location. The term maximum window size is introduced, and quantitative expressions are derived to compute the maximum window size. A detailed analysis of the effect of unimodular transformations on data locality, including the calculation of the maximum window size, is presented. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of a content distribution network designed to provide bounded content access latency. Content can be divided into multiple classes with different configurable per-class delay bounds. The network uses a simple distributed algorithm to dynamically select subsets of its proxy servers for different classes such that a global per-class delay bound is achieved on content access. The content distribution algorithm is implemented and tested on PlanetLab [25], a world-wide distributed Internet testbed. Evaluation results demonstrate that, despite Internet delay variability, subsecond delay bounds (of 200-500ms) can be guaranteed with a very high probability at only a moderate content replication cost. The distribution algorithm achieves a four to five-fold reduction in the number of response-time violations compared to prior content distribution approaches that attempt to minimize average latency. To the authors' knowledge, this paper presents the first wide-area performance evaluation of an algorithm designed to bound maximum content access latency, as opposed to optimizing an average performance metric. [ABSTRACT FROM AUTHOR]

This paper presents the systolic array implementation of a real-time symbol-optimum multiuser detection (MUD) algorithm for a direct-sequence code-division multiple-access system by truncating the backward recursions in the generalized forward/backward schedule. Simulation results show that the real-time algorithm provides negligible performance loss compared to the original symbol-optimum detection algorithm. The systolic array implementation is derived in this paper through the factor graph language of the real-time algorithm in order to exploit the suitability of the algorithm for parallel signal processing. [ABSTRACT FROM AUTHOR]

Abstract: A real time monitoring and diagnosis system to measure spindle center displacement (roundness error) during turning operation is introduced in this paper. The system was developed based on the three-point method. The error generated during cutting process was monitored and diagnosed by using a system equipped with a designed DSP (Digital Signal Processor) board and FFT (Fast Fourier Transform) algorithm. The system could estimate cutting force and predict other cutting characteristics such as chattering and tool wear. Using the spindle center fluctuation, i.e. a roundness error movement from the center, the relationship between the cutting force and the roundness error could also be investigated. The roundness error that eliminated geometric shape error and eccentric error from the measured signals in the frequency domain proved to be a dominating factor in determining cutting characteristics. [Copyright &y& Elsevier]