This document presents a comparative study of high-resolution direction of arrival (DOA) estimation algorithms, specifically MUSIC, ESPRIT, and Q-MUSIC. It provides background on array signal processing and direction of arrival estimation. The key high-resolution DOA estimation algorithms - MUSIC, ESPRIT, and Q-MUSIC - are explored in detail. Through simulation, Q-MUSIC is shown to be highly accurate, stable, and provide high angular resolution for multidimensional complex data signals compared to MUSIC and ESPRIT.
PERFORMANCE ANALYSIS OF BARKER CODE BASED ON THEIR CORRELATION PROPERTY IN MU...ijistjournal
Spread-spectrum communication, with its inherent interference attenuation capability, has over the years become an increasingly popular technique for use in many different systems. They have very beneficial and tempting features, like Antijam, Security, and Multiple accesses. This thesis basically deals with the pseudo codes used in spread spectrum communication system. The cross-correlation and auto-correlation properties of the long Barker Code are analyzed. It has been seen that the length of the code, autocorrelation and cross-correlation properties can help us to determine the best suitable code for any particular communication environment. We have tried to find out the code with suitable auto-correlation properties along with low cross-correlation values. Barker code has good auto-correlation properties and we have found the pairs with the low cross- correlation so that they can be used in multi-user environment.
Enhanced signal detection slgorithm using trained neural network for cognitiv...IJECEIAES
Over the past few years, Cognitive Radio has become an important research area in the field of wireless communications. It can play an important role in dynamic spectrum management and interference identification. There are many spectrum sensing techniques proposed in literature for cognitive radio, but all those techniques detect only presence or absence of the primary user in the designated band and do not give any information about the used modulation scheme. In certain applications, in cognitive radio receiver, it is necessary to identify the modulation type of the signal so that the receiver parameters can be adjusted accordingly. Most of the modulated signals exhibit the property of Cyclostationarity that can be used for the purpose of correct detection of primary user and the modulation type. In this paper, we have proposed an enhanced signal detection algorithm for cognitive radio receiver which makes use of cyclostationarity property of the modulated signal to exactly detect, the modulation type of the received signal using a trained neural network. The algorithm gives better accuracy of signal detection even in low SNR conditions. The use of a trained neural network makes it more flexible and extendible for future applications
PERFORMANCE ANALYSIS OF BARKER CODE BASED ON THEIR CORRELATION PROPERTY IN MU...ijistjournal
Spread-spectrum communication, with its inherent interference attenuation capability, has over the years become an increasingly popular technique for use in many different systems. They have very beneficial and tempting features, like Antijam, Security, and Multiple accesses. This thesis basically deals with the pseudo codes used in spread spectrum communication system. The cross-correlation and auto-correlation properties of the long Barker Code are analyzed. It has been seen that the length of the code, autocorrelation and cross-correlation properties can help us to determine the best suitable code for any particular communication environment. We have tried to find out the code with suitable auto-correlation properties along with low cross-correlation values. Barker code has good auto-correlation properties and we have found the pairs with the low cross- correlation so that they can be used in multi-user environment.
Enhanced signal detection slgorithm using trained neural network for cognitiv...IJECEIAES
Over the past few years, Cognitive Radio has become an important research area in the field of wireless communications. It can play an important role in dynamic spectrum management and interference identification. There are many spectrum sensing techniques proposed in literature for cognitive radio, but all those techniques detect only presence or absence of the primary user in the designated band and do not give any information about the used modulation scheme. In certain applications, in cognitive radio receiver, it is necessary to identify the modulation type of the signal so that the receiver parameters can be adjusted accordingly. Most of the modulated signals exhibit the property of Cyclostationarity that can be used for the purpose of correct detection of primary user and the modulation type. In this paper, we have proposed an enhanced signal detection algorithm for cognitive radio receiver which makes use of cyclostationarity property of the modulated signal to exactly detect, the modulation type of the received signal using a trained neural network. The algorithm gives better accuracy of signal detection even in low SNR conditions. The use of a trained neural network makes it more flexible and extendible for future applications
Bayesian distance metric learning and its application in automatic speaker re...IJECEIAES
This paper proposes state-of the-art Automatic Speaker Recognition System (ASR) based on Bayesian Distance Learning Metric as a feature extractor. In this modeling, I explored the constraints of the distance between modified and simplified i-vector pairs by the same speaker and different speakers. An approximation of the distance metric is used as a weighted covariance matrix from the higher eigenvectors of the covariance matrix, which is used to estimate the posterior distribution of the metric distance. Given a speaker tag, I select the data pair of the different speakers with the highest cosine score to form a set of speaker constraints. This collection captures the most discriminating variability between the speakers in the training data. This Bayesian distance learning approach achieves better performance than the most advanced methods. Furthermore, this method is insensitive to normalization compared to cosine scores. This method is very effective in the case of limited training data. The modified supervised i-vector based ASR system is evaluated on the NIST SRE 2008 database. The best performance of the combined cosine score EER 1.767% obtained using LDA200 + NCA200 + LDA200, and the best performance of Bayes_dml EER 1.775% obtained using LDA200 + NCA200 + LDA100. Bayesian_dml overcomes the combined norm of cosine scores and is the best result of the short2-short3 condition report for NIST SRE 2008 data.
Simulation Analysis of Prototype Filter Bank Multicarrier Cognitive Radio Und...ijeei-iaes
Cognitive Radio has proven as a optimum technique for getting improved spectrum utilization by sharing the radio spectrum with licensed primary users opportunistically. The cognitive radio is a new paradigm to overcome the persisting problem of spectrum underutilization.Seeing the everincreasing demand of wireless applications,the radio sp ectrum is a valuable resource and in cognitive radio systems,trustworthy spectrum sensing techniques are required to avoid any harmful interference to the primary users.As cognitive radio possess the capability to utilise the unused spectrum holes or white spaces so,there is a tremendous need to scan the large range of spectrum either for interference management or for primary receiver detection.Dynamic Spectrum Access techniques need to be implemented for the sake of better radio resource management and computational complexity analysis of multirate filter bank cognitive radio,where BER and Eb/No are the performance metrics or governing parameters to affect the system performance using polyphase filter bank.The present paper deals with the study of effect of variation of number of subchannels M at fix overlapping factor K of polyphase component of Filter Bank Multicarrier cognitive radio in terms of prototype filter length at Lp=K*M .
Collaborative spectrum sensing (CSS) was visualize to improve the reliability of spectrum sensing in centralized cognitive radio networks (CRNs). A popular attack in Collaborative Spectrum Sensing is the called spectrum sensing data falsification (SSDF) attack. There will be a punishment strategy which is present to see the reputation method, in which the honour factor and the retribution factor are introduced to give SUs to given in positive and honest sensing activities. There will be a punishment strategy which is present to see the reputation method, in which the honour factor and the retribution factor are introduced to give SUs to given in positive and honest sensing activities. Harvesting energy from ubiquitous radio frequency (RF) signals in urban area is environmentally friendly and self-sustaining. Here Proposed a threshold-based framework for optimal spectral access strategy and show that the threshold is optimal and traffic-dependent. The proposed threshold-based strategy takes into account both the spectral access and energy harvesting opportunities provided by a particular traffic application. Also an iterative algorithm is used that selects a threshold which maximizes the SU transmission opportunity subject to the overall harvested energy budget. Further, we illustrate the effects of different Harvesting energy for the Primary users and the illerate algorithm is used here.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Classification of vehicles based on audio signalsijsc
The focusof this paper is on classification of different vehicles using sound emanated from the vehicles. In
this paper,quadratic discriminant analysis classifies audio signals of passing vehicles to bus, car, motor, and
truck categories based on features such as short time energy, average zero cross rate, and pitch frequency of
periodic segments of signals. Simulation results show that just by considering high energy feature vectors,
better classification accuracy can be achieved due to the correspondence of low energy regions with noises
of the background. To separate these elements, short time energy and average zero cross rate are used
simultaneously.In our method,we have used a few features which are easy to be calculated in time domain
and enable practical implementation of efficient classifier. Although, the computation complexity is low,
the classification accuracy is comparable with other classification methodsbased on long feature vectors
reported in literature for this problem.
A Mathematical Approach for Hidden Node Problem in Cognitive Radio NetworksTELKOMNIKA JOURNAL
Cognitive radio (CR) technology has emerged as a realistic solution to the spectrum scarcity
problem in present day wireless networks. A major challenge in CR radio networks is the hidden node
problem, which is the inability of the CR nodes to detect the primary user. This paper proposes energy
detector-based distributed sequential cooperative spectrum sensing over Nakagami-m fading, as a tool to
solve the hidden node problem. The derivation of energy detection performance over Nakagami-m fading
channel is presented. Since the observation represents a random variable, likelihood ratio test (LRT) is
known to be optimal in this type of detection problem. The LRT is implemented using the Neyman-Pearson
Criterion (maximizing the probability of detection but at a constraint of false alarm probability). The
performance of the proposed method has been evaluated both by numerical analysis and simulations. The
effect of cooperation among a group of CR nodes and system parameters such as SNR, detection
threshold and number of samples per CR nodes is investigated. Results show improved detection
performance by implementing the proposed model.
Improved performance of scs based spectrum sensing in cognitive radio using d...eSAT Journals
Abstract
Tremendous growth in current wireless networks raises the demand of more frequency spectrum, over the finite availability of spectrum resource. Although, the research has specifies that the available primary users (i.e. licensed user) has not occupying the channel all the time. The most effective technology known as Cognitive radio giving promises for a solution of under utilization of available frequency spectrum in wireless communication. In cognitive radio network two types of wireless user can be define as primary user and secondary user. Primary users have highest priority to utilize the available band of frequency and secondary user can utilize these services only when the channel is vacant by primary user and there will be no any interference. The optimization of this may be implemented by a smart technique such as cognitive radio, which is fully automated intelligent wireless sensor tool having capability to sense, learn & adjust relevant operating parameters dynamically in radio atmosphere. This can be happen if we prefer the appropriate window technique to evaluate system parameter for sensing the availability of vacant band. We show that by comparing the different windows techniques, cognitive radios not only provide better spectrum opportunity but also provide the chance to huge number of wireless users.
Keywords: Primary user, Secondary user, Spectrum Sensing and Window technique etc.
Adaptive quantization for spectrum exchange information in mobile cognitive r...IJECEIAES
To reduce the detection failure of the exchanging signal power onto the OFDM subcarrier signal at uniform quantization, dynamic subcarrier mapping is applied. Moreover, to addressing low SNR’s wall less than predetermine threshold, non-uniform quantization or adaptive quantization for the signal quantization size parameter is proposed. μ-law is adopted for adaptive quantization subcarrier mapping which is deployed in mobility environment, such as Doppler Effect and Rayleigh Fading propagation. In this works, sensing node received signal power then sampled into a different polarity positive and negative in μ-law quantization and divided into several segmentation levels. Each segmentation levels are divided into several sub-segment has representing one tone signal subcarrier number OFDM which has the number of quantization level and the width power. The results show that by using both methods, a significant difference is obtained around 8 dB compared to those not using the adaptive method.
We propose a model for carrying out deep learning based multimodal sentiment analysis. The MOUD dataset is taken for experimentation purposes. We developed two parallel text based and audio basedmodels and further, fused these heterogeneous feature maps taken from intermediate layers to complete thearchitecture. Performance measures–Accuracy, precision, recall and F1-score–are observed to outperformthe existing models.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Bayesian distance metric learning and its application in automatic speaker re...IJECEIAES
This paper proposes state-of the-art Automatic Speaker Recognition System (ASR) based on Bayesian Distance Learning Metric as a feature extractor. In this modeling, I explored the constraints of the distance between modified and simplified i-vector pairs by the same speaker and different speakers. An approximation of the distance metric is used as a weighted covariance matrix from the higher eigenvectors of the covariance matrix, which is used to estimate the posterior distribution of the metric distance. Given a speaker tag, I select the data pair of the different speakers with the highest cosine score to form a set of speaker constraints. This collection captures the most discriminating variability between the speakers in the training data. This Bayesian distance learning approach achieves better performance than the most advanced methods. Furthermore, this method is insensitive to normalization compared to cosine scores. This method is very effective in the case of limited training data. The modified supervised i-vector based ASR system is evaluated on the NIST SRE 2008 database. The best performance of the combined cosine score EER 1.767% obtained using LDA200 + NCA200 + LDA200, and the best performance of Bayes_dml EER 1.775% obtained using LDA200 + NCA200 + LDA100. Bayesian_dml overcomes the combined norm of cosine scores and is the best result of the short2-short3 condition report for NIST SRE 2008 data.
Simulation Analysis of Prototype Filter Bank Multicarrier Cognitive Radio Und...ijeei-iaes
Cognitive Radio has proven as a optimum technique for getting improved spectrum utilization by sharing the radio spectrum with licensed primary users opportunistically. The cognitive radio is a new paradigm to overcome the persisting problem of spectrum underutilization.Seeing the everincreasing demand of wireless applications,the radio sp ectrum is a valuable resource and in cognitive radio systems,trustworthy spectrum sensing techniques are required to avoid any harmful interference to the primary users.As cognitive radio possess the capability to utilise the unused spectrum holes or white spaces so,there is a tremendous need to scan the large range of spectrum either for interference management or for primary receiver detection.Dynamic Spectrum Access techniques need to be implemented for the sake of better radio resource management and computational complexity analysis of multirate filter bank cognitive radio,where BER and Eb/No are the performance metrics or governing parameters to affect the system performance using polyphase filter bank.The present paper deals with the study of effect of variation of number of subchannels M at fix overlapping factor K of polyphase component of Filter Bank Multicarrier cognitive radio in terms of prototype filter length at Lp=K*M .
Collaborative spectrum sensing (CSS) was visualize to improve the reliability of spectrum sensing in centralized cognitive radio networks (CRNs). A popular attack in Collaborative Spectrum Sensing is the called spectrum sensing data falsification (SSDF) attack. There will be a punishment strategy which is present to see the reputation method, in which the honour factor and the retribution factor are introduced to give SUs to given in positive and honest sensing activities. There will be a punishment strategy which is present to see the reputation method, in which the honour factor and the retribution factor are introduced to give SUs to given in positive and honest sensing activities. Harvesting energy from ubiquitous radio frequency (RF) signals in urban area is environmentally friendly and self-sustaining. Here Proposed a threshold-based framework for optimal spectral access strategy and show that the threshold is optimal and traffic-dependent. The proposed threshold-based strategy takes into account both the spectral access and energy harvesting opportunities provided by a particular traffic application. Also an iterative algorithm is used that selects a threshold which maximizes the SU transmission opportunity subject to the overall harvested energy budget. Further, we illustrate the effects of different Harvesting energy for the Primary users and the illerate algorithm is used here.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Classification of vehicles based on audio signalsijsc
The focusof this paper is on classification of different vehicles using sound emanated from the vehicles. In
this paper,quadratic discriminant analysis classifies audio signals of passing vehicles to bus, car, motor, and
truck categories based on features such as short time energy, average zero cross rate, and pitch frequency of
periodic segments of signals. Simulation results show that just by considering high energy feature vectors,
better classification accuracy can be achieved due to the correspondence of low energy regions with noises
of the background. To separate these elements, short time energy and average zero cross rate are used
simultaneously.In our method,we have used a few features which are easy to be calculated in time domain
and enable practical implementation of efficient classifier. Although, the computation complexity is low,
the classification accuracy is comparable with other classification methodsbased on long feature vectors
reported in literature for this problem.
A Mathematical Approach for Hidden Node Problem in Cognitive Radio NetworksTELKOMNIKA JOURNAL
Cognitive radio (CR) technology has emerged as a realistic solution to the spectrum scarcity
problem in present day wireless networks. A major challenge in CR radio networks is the hidden node
problem, which is the inability of the CR nodes to detect the primary user. This paper proposes energy
detector-based distributed sequential cooperative spectrum sensing over Nakagami-m fading, as a tool to
solve the hidden node problem. The derivation of energy detection performance over Nakagami-m fading
channel is presented. Since the observation represents a random variable, likelihood ratio test (LRT) is
known to be optimal in this type of detection problem. The LRT is implemented using the Neyman-Pearson
Criterion (maximizing the probability of detection but at a constraint of false alarm probability). The
performance of the proposed method has been evaluated both by numerical analysis and simulations. The
effect of cooperation among a group of CR nodes and system parameters such as SNR, detection
threshold and number of samples per CR nodes is investigated. Results show improved detection
performance by implementing the proposed model.
Improved performance of scs based spectrum sensing in cognitive radio using d...eSAT Journals
Abstract
Tremendous growth in current wireless networks raises the demand of more frequency spectrum, over the finite availability of spectrum resource. Although, the research has specifies that the available primary users (i.e. licensed user) has not occupying the channel all the time. The most effective technology known as Cognitive radio giving promises for a solution of under utilization of available frequency spectrum in wireless communication. In cognitive radio network two types of wireless user can be define as primary user and secondary user. Primary users have highest priority to utilize the available band of frequency and secondary user can utilize these services only when the channel is vacant by primary user and there will be no any interference. The optimization of this may be implemented by a smart technique such as cognitive radio, which is fully automated intelligent wireless sensor tool having capability to sense, learn & adjust relevant operating parameters dynamically in radio atmosphere. This can be happen if we prefer the appropriate window technique to evaluate system parameter for sensing the availability of vacant band. We show that by comparing the different windows techniques, cognitive radios not only provide better spectrum opportunity but also provide the chance to huge number of wireless users.
Keywords: Primary user, Secondary user, Spectrum Sensing and Window technique etc.
Adaptive quantization for spectrum exchange information in mobile cognitive r...IJECEIAES
To reduce the detection failure of the exchanging signal power onto the OFDM subcarrier signal at uniform quantization, dynamic subcarrier mapping is applied. Moreover, to addressing low SNR’s wall less than predetermine threshold, non-uniform quantization or adaptive quantization for the signal quantization size parameter is proposed. μ-law is adopted for adaptive quantization subcarrier mapping which is deployed in mobility environment, such as Doppler Effect and Rayleigh Fading propagation. In this works, sensing node received signal power then sampled into a different polarity positive and negative in μ-law quantization and divided into several segmentation levels. Each segmentation levels are divided into several sub-segment has representing one tone signal subcarrier number OFDM which has the number of quantization level and the width power. The results show that by using both methods, a significant difference is obtained around 8 dB compared to those not using the adaptive method.
We propose a model for carrying out deep learning based multimodal sentiment analysis. The MOUD dataset is taken for experimentation purposes. We developed two parallel text based and audio basedmodels and further, fused these heterogeneous feature maps taken from intermediate layers to complete thearchitecture. Performance measures–Accuracy, precision, recall and F1-score–are observed to outperformthe existing models.
Performance Analysis of Bfsk Multi-Hop Communication Systems Over K-μ Fading ...ijwmn
Multi-hop communication systems gained popularity in wireless communications; they can be used to
extend the coverage of the network and reduce the transmitted power. The transmission of data from the
source node to the destination node in multi-hop communications undergoes through intermediate relay
nodes. In this paper, we study the performance of multi-hop communication systems, in terms of average bit
error rate (BER) with Binary frequency shift keying assuming the κ-µ fading channel model. Due to the
difficulty in finding the probability density function (PDF) of the end-to-end signal to noise ratio (SNR) and
hence for the performance metrics, we use Gaussian Mixture (GM) approximation technique to
approximate the PDF of the end to end SNR assuming the κ-µ fading models as weighted sums of Gaussian
distributions. Numerical results are provided for the BER of binary frequency shift keying (BFSK) of
amplify and forward (AF) multi-hop communication systems assuming different values for the fading
parameters (, ) and for different number of hops. Numerical results are validated by comparing them
with simulation results.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Smart Antenna is a device with signal processing
capability combining multiple antenna elements to optimize its
radiation and reception patterns as per designed specifications.
Smart antennas basically comprise of two functionalities, i.e.,
Direction of Arrival and Beamforming. This paper explains the
estimation of Direction of Arrival using MLM method and a
novel approach called MUltiple Signal Classification which takes
advantage of orthogonal property and performs subspace
computation. With a comparative study of both the algorithms,
we shall prove the advantages of MUltiple Signal Classification
over the MLM method with the aid of MATLAB
A novel high resolution doa estimation design algorithm of close sources sign...eSAT Journals
Abstract Underwater target finding in ocean environment has gain considerable interest in both military and civilian applications. In this paper the performance of directions finding techniques, subspace and the non-subspace methods are presented. In this paper, the Eigen analysis of high resolution and supreme resolution algorithms, comparisons and the performance, resolution analysis are done. The analysis is based on linear array elements and the calculation of the pseudo spectra function of the valuation algorithms. Traditional MUSIC algorithm decomposes the signal covariance matrix and then make the signals subspace obtained is orthogonal to the noise subspace, which decreases the effect of the noise. But when the signals intervals are very small, traditional improved MUSIC algorithm has been unable to distinguish the signals as the SNR decreases. A new improved algorithm is introduced using Singular value decomposition of the covariance matrix. An antenna of ULA configuration is taken for both the algorithms. Simulation results show that projected method gives better performance than MUSIC algorithm. In this newly Modified MUSIC algorithm, conditions required for under water environment are taken into account such as water density, permittivity of water, pressure, Signal to Noise Ratio, speed of sound wave in water. Keywords: Underwater Communication, Number of Snapshots, Antenna Noise, Uniform Linear Array (ULA) and Distance Between Array Elements.
IFKSA-ESPRIT - Estimating the Direction of Arrival under the Element Failures...IDES Editor
This paper presents the use of Inverse Free Krylov
Subspace Algorithm (IFKSA) with Estimation of Signal
Parameters via Rotational Invariance Technique (ESPRIT)
for the Direction-of-Arrival (DOA) estimation under element
failure in a Uniform Linear Antenna Array (ULA). Failure of
a few elements results in sparse signal space. IFKSA algorithm
is an iterative algorithm to find the dominant eigenvalues
and is applied for decomposition of sparse signal space, into
signal subspace and the noise subspace. The ESPRIT is later
used to estimate the DOAs. The performance of the algorithm
is evaluated for various elements failure scenarios and noise
levels, and the results are compared with ESPRIT and Cramer
Rao Lower bound (CRLB). The results indicate a better
performance of the IFKSA-ESPRIT based DOA estimation
scheme under different antenna failure scenarios, and noise
levels.
Optimum Sensor Node Localization in Wireless Sensor Networkspaperpublications3
Abstract: Scientists, engineers, and researchers use wireless sensor networks (WSN) for a wide array of applications. Many of these applications rely on knowledge of the precise position of each node. An optimum localization algorithm can be used for determining the position of nodes in a wireless sensor network. This paper provides an overview of different approach of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Experiments were performed in a testbed area containing anchor and blind nodes deployed in it to characterize the pathloss exponent and to determine the localization error of the algorithm. Details regarding the implementation of new algorithm are also discussed in this paper.
Direction of Arrival Estimation Based on MUSIC Algorithm Using Uniform and No...IJERA Editor
In signal processing, the direction of arrival (DOA) estimation denotes the direction from which a propagating wave arrives at a point, where a set of antennas is located. Using the array antenna has an advantage over the single antenna in achieving an improved performance by applying Multiple Signal Classification (MUSIC) algorithm. This paper focuses on estimating the DOA using uniform linear array (ULA) and non-uniform linear array (NLA)of antennas to analyze the performance factors that affect the accuracy and resolution of the system based on MUSIC algorithm. The direction of arrival estimation is simulated on a MATLAB platform with a set of input parameters such as array elements, signal to noise ratio, number of snapshots and number of signal sources. An extensive simulation has been conducted and the results show that the NLA with DOA estimation for co-prime array can achieve an accurate and efficient DOA estimation
performance analysis of MUSIC and ESPRIT DOA estimation used in adaptive arra...CSCJournals
MUSIC and ESPRIT DOA Estimaion algorithms are widely used in adaptive array to locate the desired desired signal.MUSIC is found to be more stable and accurate and widely used inthe design of adaptive array.
Fast and accurate primary user detection with machine learning techniques for...nooriasukmaningtyas
Spectrum decision is an important and crucial task for the secondary user to avail the unlicensed spectrum for transmission. Managing the spectrum is an efficient one for spectrum sensing. Determining the primary user presence in the spectrum is an essential work for using the licensed spectrum of primary user. The information which lacks in managing the spectrum are the information about the primary user presence, accuracy in determining the existence of user in the spectrum, the cost for computation and difficult in finding the user in low signal-to noise ratio (SNR) values. The proposed system overcomes the above limitations. In the proposed system, the various techniques of machine learning like decision tree, support vector machines, naive bayes, ensemble based trees, nearest neighbour’s and logistic regression are used for testing the algorithm. As a first step, the spectrum sensing is done in two stages with orthogonal frequency division multiplexing and energy detection algorithm at the various values of SNR. The results generated from the above algorithm is used for database generation. Next, the different machine learning techniques are trained and compared for the results produced by different algorithms with the characteristics like speed, time taken for training and accuracy in prediction. The accuracy and finding the presence of the user in the spectrum at low SNR values are achieved by all the algorithms. The computation cost of the algorithm differs from each other. Among the tested techniques, k-nearest neighbour (KNN) algorithm produces the better performance in a minimized time.
PERFORMANCE ANALYSIS OF BARKER CODE BASED ON THEIR CORRELATION PROPERTY IN MU...ijistjournal
Spread-spectrum communication, with its inherent interference attenuation capability, has over the years become an increasingly popular technique for use in many different systems. They have very beneficial and tempting features, like Antijam, Security, and Multiple accesses. This thesis basically deals with the pseudo codes used in spread spectrum communication system. The cross-correlation and auto-correlation properties of the long Barker Code are analyzed. It has been seen that the length of the code, autocorrelation and cross-correlation properties can help us to determine the best suitable code for any particular communication environment. We have tried to find out the code with suitable auto-correlation properties along with low cross-correlation values. Barker code has good auto-correlation properties and we have found the pairs with the low cross- correlation so that they can be used in multi-user environment.
Investigation of the performance of multi-input multi-output detectors based...IJECEIAES
The next generation of wireless cellular communication networks must be energy efficient, extremely reliable, and have low latency, leading to the necessity of using algorithms based on deep neural networks (DNN) which have better bit error rate (BER) or symbol error rate (SER) performance than traditional complex multi-antenna or multi-input multi-output (MIMO) detectors. This paper examines deep neural networks and deep iterative detectors such as OAMP-Net based on information theory criteria such as maximum correntropy criterion (MCC) for the implementation of MIMO detectors in non-Gaussian environments, and the results illustrate that the proposed method has better BER or SER performance.
Electrically small antennas: The art of miniaturizationEditor IJARCET
We are living in the technological era, were we preferred to have the portable devices rather than unmovable devices. We are isolating our self rom the wires and we are becoming the habitual of wireless world what makes the device portable? I guess physical dimensions (mechanical) of that particular device, but along with this the electrical dimension is of the device is also of great importance. Reducing the physical dimension of the antenna would result in the small antenna but not electrically small antenna. We have different definition for the electrically small antenna but the one which is most appropriate is, where k is the wave number and is equal to and a is the radius of the imaginary sphere circumscribing the maximum dimension of the antenna. As the present day electronic devices progress to diminish in size, technocrats have become increasingly concentrated on electrically small antenna (ESA) designs to reduce the size of the antenna in the overall electronics system. Researchers in many fields, including RF and Microwave, biomedical technology and national intelligence, can benefit from electrically small antennas as long as the performance of the designed ESA meets the system requirement.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.