Adaptive Array Antennas (AAAs) are expected to play a key role in meeting the demands of the wireless communication systems of the future. AAAs in cognitive relay network is proposed to reduce the symbol error rate and improve the system performance. Many algorithms such as wiener solution and least mean square (LMS) will be explained to show how AAAs in cognitive relay network achieves this object. AAAs at different locations will be investigated under AWGN and Rayleigh fading channel. Moreover, enhancement the system performance by showing the effect of increasing the number of AAAs element at the relay node, increasing the source gain and decreasing the relay gain. In addition, increasing the rate adaptation and number of iterations in LMS algorithm has significant improvement in the system.
PERFORMANCE EVALUATION OF ADAPTIVE ARRAY ANTENNAS IN COGNITIVE RELAY NETWORKcsijjournal
1) Adaptive array antennas in cognitive relay networks are proposed to improve system performance by reducing symbol error rate. Wiener solution and least mean square algorithms are explored to calculate optimal antenna weights.
2) Simulations show that placing adaptive array antennas at the source node provides better performance than at the relay or destination nodes. Additional enhancements include increasing the source gain, decreasing the relay gain, and using more antenna elements.
3) Under different channel conditions, adaptive array antennas perform best under additive white Gaussian noise and improve under Rayleigh fading by increasing the step size or number of iterations in the least mean square algorithm.
This document summarizes a research paper that analyzes the performance of adaptive equalization algorithms RLS and CMA for noisy speech signals. It finds that the RLS algorithm has a faster convergence rate but requires more computing power, while the CMA algorithm has a slower convergence rate but requires less computing power and performs relatively better. The parameters of an adaptive equalizer combining these algorithms with a noisy audio source are optimized in simulations. The results show that CMA has a better frequency response and MSE convergence than RLS in the presence of noisy audio. Therefore, blind equalization using CMA is concluded to perform better than trained equalization with RLS for noisy speech signals.
Hybrid protocol for wireless EH network over weibull fading channel: performa...IJECEIAES
In this paper, the hybrid TSR-PSR protocol for wireless energy harvesting (EH) relaying network over the Weibull fading channel is investigated. The system network is working in half-duplex (HD) mode. For evaluating the system performance, the closed-form and integral-form expressions of the outage probability (OP) are investigated and derived. After that, numerical results convinced that our derived analytical results are the same with the simulation results by using Monte Carlo simulation. This paper provides a novel recommendation for the wireless EH relaying network.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
PERFORMANCE EVALUATION OF BER FOR AWGN, AWGN MULTIPATH AND RAYLEIGH FADING CH...IJEEE
This document evaluates the performance of bit error rate (BER) for different digital modulation techniques over additive white Gaussian noise (AWGN), AWGN multipath, and Rayleigh fading channels. It presents simulation results comparing the BER of binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulation under varying signal-to-noise ratio (SNR) levels for AWGN and AWGN multipath channels, and under varying Doppler shift levels for Rayleigh fading channels. The results show that BPSK has better BER performance than QPSK, and that BER is lowest for AWGN channels and highest for Rayleigh fading channels.
Heuristic based adaptive step size clms algorithms for smart antennascsandit
This document summarizes research on heuristic-based adaptive step size complex least mean square (CLMS) algorithms for smart antennas. It presents Benveniste and Mathews algorithms, which use heuristics with CLMS to speed up convergence. Simulations show these algorithms outperform CLMS and augmented CLMS in convergence rate while achieving similar performance in terms of half power beamwidth and side lobe level of the array factor. The key advantage of these algorithms is faster convergence for the output signal of smart antenna systems compared to baseline algorithms like CLMS.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
PERFORMANCE EVALUATION OF ADAPTIVE ARRAY ANTENNAS IN COGNITIVE RELAY NETWORKcsijjournal
1) Adaptive array antennas in cognitive relay networks are proposed to improve system performance by reducing symbol error rate. Wiener solution and least mean square algorithms are explored to calculate optimal antenna weights.
2) Simulations show that placing adaptive array antennas at the source node provides better performance than at the relay or destination nodes. Additional enhancements include increasing the source gain, decreasing the relay gain, and using more antenna elements.
3) Under different channel conditions, adaptive array antennas perform best under additive white Gaussian noise and improve under Rayleigh fading by increasing the step size or number of iterations in the least mean square algorithm.
This document summarizes a research paper that analyzes the performance of adaptive equalization algorithms RLS and CMA for noisy speech signals. It finds that the RLS algorithm has a faster convergence rate but requires more computing power, while the CMA algorithm has a slower convergence rate but requires less computing power and performs relatively better. The parameters of an adaptive equalizer combining these algorithms with a noisy audio source are optimized in simulations. The results show that CMA has a better frequency response and MSE convergence than RLS in the presence of noisy audio. Therefore, blind equalization using CMA is concluded to perform better than trained equalization with RLS for noisy speech signals.
Hybrid protocol for wireless EH network over weibull fading channel: performa...IJECEIAES
In this paper, the hybrid TSR-PSR protocol for wireless energy harvesting (EH) relaying network over the Weibull fading channel is investigated. The system network is working in half-duplex (HD) mode. For evaluating the system performance, the closed-form and integral-form expressions of the outage probability (OP) are investigated and derived. After that, numerical results convinced that our derived analytical results are the same with the simulation results by using Monte Carlo simulation. This paper provides a novel recommendation for the wireless EH relaying network.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
PERFORMANCE EVALUATION OF BER FOR AWGN, AWGN MULTIPATH AND RAYLEIGH FADING CH...IJEEE
This document evaluates the performance of bit error rate (BER) for different digital modulation techniques over additive white Gaussian noise (AWGN), AWGN multipath, and Rayleigh fading channels. It presents simulation results comparing the BER of binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulation under varying signal-to-noise ratio (SNR) levels for AWGN and AWGN multipath channels, and under varying Doppler shift levels for Rayleigh fading channels. The results show that BPSK has better BER performance than QPSK, and that BER is lowest for AWGN channels and highest for Rayleigh fading channels.
Heuristic based adaptive step size clms algorithms for smart antennascsandit
This document summarizes research on heuristic-based adaptive step size complex least mean square (CLMS) algorithms for smart antennas. It presents Benveniste and Mathews algorithms, which use heuristics with CLMS to speed up convergence. Simulations show these algorithms outperform CLMS and augmented CLMS in convergence rate while achieving similar performance in terms of half power beamwidth and side lobe level of the array factor. The key advantage of these algorithms is faster convergence for the output signal of smart antenna systems compared to baseline algorithms like CLMS.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
HIGH-SPEED LOW-POWER VITERBI DECODER DESIGN FOR TCM DECODERSLalitha Gosukonda
This document presents a design for a high-speed low-power Viterbi decoder for trellis coded modulation decoders. It proposes a precomputation architecture incorporated with the T-algorithm to reduce power consumption without significantly degrading decoding speed. The architecture calculates branch metric minimum values in advance and compares them to path metrics to eliminate unlikely paths early. Implementation in Verilog and synthesis results show the proposed architecture operates at a lower supply voltage for moderate throughput applications, achieving quadratic power reduction over conventional decoders.
Modified DV-Hop Algorithm for Localization in Wireless Sensor Networksijeei-iaes
Wireless sensor networks (WSNs) help monitoring physical environments with improved accuracy. Localization has been a major challenge in such networks because without finding the location of the sensor that is informing sensed data, the informed data will not be useful. Localization algorithm is categorized as: anchor based approach and anchor free approach in which DV-Hop algorithm is anchor based approach. In this paper, we modify the DV-Hop algorithm; deprivation of DV-Hop algorithm is that this algorithm works badly in sparse topology, so we have done some improvements shown in this paper and compare the simulation results of both algorithms (DV-Hop and Modified DV-Hop algorithm). The result shows that accuracy of modified DV-Hop algorithm is better than DV-Hop algorithm and modified DV-Hop algorithm also works in sparse networks.
This thesis examines direction dependent antenna modulation using a Butler matrix and four element antenna array. It provides theoretical background on these concepts and details the design and simulation of a 4x4 Butler matrix and dipole antenna array in CST. MATLAB simulations show direction dependent M-ary modulation schemes achieved using the Butler matrix. Constellations in the desired direction have better shape and power levels than in other directions, proving this approach can improve wireless security. The thesis discusses results and recommendations to further develop directional modulation transmitter systems.
Fpga implementation of soft decision low power convolutional decoder using vi...ecejntuk
1. This document discusses an FPGA implementation of a soft decision low power convolutional decoder using the Viterbi algorithm.
2. It reviews literature on adaptive Viterbi decoding techniques that can improve error performance and reduce computational requirements compared to the standard Viterbi algorithm.
3. Convolutional encoding with Viterbi decoding is described as a forward error correction technique well-suited for channels with additive white Gaussian noise. The document provides examples of how error rates increase as the signal-to-noise ratio decreases.
IRJET- Comparison of ATTEMPT and SIMPLE Protocols for Wireless Body Area Netw...IRJET Journal
This document compares the ATTEMPT and SIMPLE protocols for wireless body area networks (WBANs). ATTEMPT is an opportunistic protocol that relies on relay nodes when the sink node moves out of range, increasing power consumption and packet loss. SIMPLE aims to balance energy usage and improve throughput by selecting low-cost forwarder nodes to route data to the sink in a multi-hop fashion using TDMA scheduling. The document provides detailed descriptions of the initialization, routing, scheduling and data transmission phases of the ATTEMPT and SIMPLE protocols and discusses their advantages and disadvantages for energy efficiency in WBAN applications.
This document discusses a method for eliminating ground stationary low elevation targets (GSLETs) in automotive high resolution radar sensors. It presents a multiple bank correlation algorithm that estimates target height from its multipath return signal in order to identify and eliminate very low, non-hazardous targets. The algorithm contains three main components: 1) predicting the target's amplitude response as a function of range for all possible heights, 2) matching the received signal to the predicted signal for the correct height, and 3) applying detection criteria and thresholds to determine if the target should be eliminated. Simulated and collected radar data are analyzed to assess the performance of the algorithm at eliminating low height nuisance objects.
This document describes a novel snapshot-based approach for direction of arrival (DOA) estimation using the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. It compares ESPRIT to the multiple signal classification (MUSIC) algorithm.
The ESPRIT and MUSIC algorithms are simulated using MATLAB to estimate the DOA of signals received by antenna arrays with different numbers of antenna elements. ESPRIT is shown to provide DOA estimates with less bias than MUSIC. Resolution and sensitivity to noise are also discussed. The novel snapshot-based approach for ESPRIT uses multiple snapshots to estimate the array correlation matrix and improves DOA estimation accuracy.
IRJET- Rapid Spectrum Sensing Algorithm in Cooperative Spectrum Sensing for a...IRJET Journal
This document discusses rapid spectrum sensing algorithms for cooperative spectrum sensing in large cognitive radio networks. It begins with an introduction to cognitive radio and spectrum sensing. It then discusses optimizing cooperative spectrum sensing through determining the optimal voting rule, optimizing the energy detection threshold, and calculating the optimal number of cognitive radios needed. It also describes modeling spectrum sensing using energy detection and calculating the probability of false alarm and detection. Finally, it discusses the receiver operating characteristic of the "AND" voting rule under additive white Gaussian noise. The goal is to suggest a rapid spectrum sensing algorithm for large networks that requires fewer cognitive radios while achieving the necessary error rate bounds.
This document describes the simulation and performance analysis of a MIMO system with spatial multiplexing using polarization diversity. It discusses how dual polarized antennas can be used when antenna spacing constraints cannot be met. The document presents the channel model used, which considers spatial correlation fading and cross-polarization discrimination. It then details the steps of the MATLAB simulation, which generates channel matrices and symbol vectors, adds noise, performs optimal detection, and calculates the symbol error rate for varying SNR values. A plot of SNR versus symbol error count shows the performance of the system.
Discrete wavelet transform-based RI adaptive algorithm for system identificationIJECEIAES
In this paper, we propose a new adaptive filtering algorithm for system identifica- tion. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCT-LMS), discretewavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
The document discusses interleaved analog-to-digital converters (ADCs). It begins by explaining that interleaving multiple ADCs allows for an effective sample rate that is a multiple of the individual ADCs' rates. This provides benefits like increased bandwidth. The document then discusses the basics of how interleaving works using clock phase relationships. It explains that while interleaving provides advantages, there are also challenges in the form of mismatches between the ADCs that can cause spurs in the output spectrum. Specifically, it outlines offset, gain, timing, and bandwidth mismatches. The document concludes by stating that knowing about and addressing these mismatches enables the effective use of interleaved ADCs to meet demanding application requirements.
parametric method of power spectrum Estimationjunjer
The document discusses parametric methods of power spectrum estimation. It explains that parametric methods estimate the parameters of a mathematical model that describes the signal generation process. This involves selecting a model such as autoregressive (AR), moving average (MA), or autoregressive moving average (ARMA), estimating the model parameters from the data, and then using the estimated parameters to calculate the power spectrum. The document provides details on how to estimate the power spectrum using AR, MA, and ARMA models. It also discusses maximum entropy spectral estimation and high-resolution spectral estimation based on eigen-analysis.
Mitigating Interference to GPS Operation Using Variable Forgetting Factor Bas...IJCNCJournal
In this paper, an interference method based on signal processing is proposed. The approach is based on
utilizing the maximum likelihood properties of the received signal. The approach is built on maximizing the
probability of the desired data. The GPS data, which is constructed using Binary Phase Shift Keying
(BPSK) modulation, is transmitted as “1’s” and as “0’s.” carried on 1575.42MHz carrier called the L1
frequency. The statistics of the GPS data and interference are utilized in terms of their distribution and
variance. The statistics are used to update (adaptively) the forgetting factor (Lambda) of the Recursive
Least Squares (RLS) filter. The proposed method is called Maximum Likelihood Variable Forgetting Factor
(ML VFF). The adaptive update takes on assigning lambda to the maximum of the probabilities of the
symbols based on the statistics mentioned.
A blind channel shortening for multiuser, multicarrier CDMA system over multi...TELKOMNIKA JOURNAL
In this paper we derive the Multicarrier Equalization by Restoration of Redundancy (MERRY) algorithm: A blind, adaptive channel shortening algorithm for updating a Time-domain Equalizer (TEQ) in a system employing MultiCarrier Code Division Multiple Access (MC-CDMA) modulation. We show that the MERRY algorithm applied to the MC-CDMA system converges considerably more rapidly than in the Orthogonal Frequency Division Multiplexing (OFDM) system [1]. Simulations results are provided to demonstrate the performance of the algorithm.
IRJET- Simulation and Performance Estimation of BPSK in Rayleigh Channel ...IRJET Journal
The document discusses simulation and performance estimation of BPSK modulation in Rayleigh fading channels using three diversity combining techniques: selection combining (SC), maximal ratio combining (MRC), and equal gain combining (EGC). It provides mathematical analysis of how these techniques calculate bit error rate (BER) and compares their performance. The key findings are that MRC achieves the best performance with lowest required SNR, followed by EGC, while SC requires the highest SNR to achieve a given BER. Performance is improved by increasing the number of diversity branches for all techniques.
This paper discusses channel estimation for MIMO-OFDM systems using power delay profile (PDP) techniques. It proposes implementing a PDP estimation method that uses all pilot symbols from transmit antennas to obtain an accurate PDP. This addresses issues caused by insufficient channel impulse response samples and null subcarriers in traditional PDP estimation. The paper finds that using the proposed PDP technique in linear minimum mean square error (LMMSE) channel estimation improves performance by reducing distortion and approaching that of Wiener filtering. Simulation results show the implemented PDP-based LMMSE channel estimation outperforms conventional 1D least squares estimation methods.
Area Versus Speed Trade-off Analysis of a WiMAX Deinterleaver Circuit Designijsrd.com
Trade-off is one of the main design parameters in the field of electronic circuit design. Whereas smaller electronics devices which use less hardware due to techniques like hardware multiplexing or due to smaller devices created due to techniques developed by nanotechnology and MEMS, are more appealing, a trade-off between area, power and speed is inevitable. This paper analyses the trade-off in the design of Wimax deinterleaver. The main aim is to reduce the hardware utilization in a deinterleaver but speed and power consumption are important parameters which cannot be overlooked.
Capacity Enhancement of MIMO-OFDM System in Rayleigh Fading ChannelIOSR Journals
MIMO-OFDM system in Rayleigh Fading Channel is very popular technique for mobile
communication now a day’s for research. Here we want increase the capacity of MIMO-OFDM of system by
using adaptive modulation, Algebraic Space-Time Codes (ASTC) encoder for MIMO Systems are based on
quaternion algebras .we found that ergodic capacity has some limitation which reduce the system’s
performance to overcome this we use ASTC code . ASTC code are full rank, full rate and non vanishing constant
minimum determinant for increasing spectral efficiency and reducing Peak to Average Power Ratio (PAPR) .
Capacity Enhancement of MIMO-OFDM System in Rayleigh Fading ChannelIOSR Journals
Abstract: MIMO-OFDM system in Rayleigh Fading Channel is very popular technique for mobile communication now a day’s for research. Here we want increase the capacity of MIMO-OFDM of system by using adaptive modulation, Algebraic Space-Time Codes (ASTC) encoder for MIMO Systems are based on quaternion algebras .we found that ergodic capacity has some limitation which reduce the system’s performance to overcome this we use ASTC code . ASTC code are full rank, full rate and non vanishing constant minimum determinant for increasing spectral efficiency and reducing Peak to Average Power Ratio (PAPR) . Keywords— Adaptive modulation ASTC code, Capacity, BER, Ergodic capacity, PAPR, Spectral Efficiency and SNR
This document summarizes a study on analyzing the impact of impulse noise on OFDM systems using three adaptive algorithms: LMS, NLMS, and RLS. It first describes OFDM systems and impulse noise modeling. It then provides details on the three algorithms - LMS uses a least mean square approach, NLMS is a normalized version of LMS, and RLS uses a recursive least squares approach. Simulation results show transmitted OFDM signals and spectra, as well as BER plots for the different algorithms under varying SNR levels. RLS is found to have the best performance with minimum BER, followed by NLMS, and then LMS. The document concludes RLS is the best algorithm to use for its sustainability to higher
BER Analysis ofImpulse Noise inOFDM System Using LMS,NLMS&RLSiosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
FPGA Design & Simulation Modeling of Baseband Data Transmission SystemIOSR Journals
This document describes the design, simulation, and modeling of a baseband data transmission system using FPGA and MATLAB. It presents the theoretical background of baseband signaling and matched filters. A system is implemented with an RC filter for pre-detection filtering to improve the bit error rate. The complete system is simulated in MATLAB and results are compared to theoretical predictions. The simulation agrees with theory and shows a 2.35 dB degradation when using an RC filter compared to an optimal matched filter. The combination of theoretical background, simulation, and experimental results helps strengthen student understanding.
HIGH-SPEED LOW-POWER VITERBI DECODER DESIGN FOR TCM DECODERSLalitha Gosukonda
This document presents a design for a high-speed low-power Viterbi decoder for trellis coded modulation decoders. It proposes a precomputation architecture incorporated with the T-algorithm to reduce power consumption without significantly degrading decoding speed. The architecture calculates branch metric minimum values in advance and compares them to path metrics to eliminate unlikely paths early. Implementation in Verilog and synthesis results show the proposed architecture operates at a lower supply voltage for moderate throughput applications, achieving quadratic power reduction over conventional decoders.
Modified DV-Hop Algorithm for Localization in Wireless Sensor Networksijeei-iaes
Wireless sensor networks (WSNs) help monitoring physical environments with improved accuracy. Localization has been a major challenge in such networks because without finding the location of the sensor that is informing sensed data, the informed data will not be useful. Localization algorithm is categorized as: anchor based approach and anchor free approach in which DV-Hop algorithm is anchor based approach. In this paper, we modify the DV-Hop algorithm; deprivation of DV-Hop algorithm is that this algorithm works badly in sparse topology, so we have done some improvements shown in this paper and compare the simulation results of both algorithms (DV-Hop and Modified DV-Hop algorithm). The result shows that accuracy of modified DV-Hop algorithm is better than DV-Hop algorithm and modified DV-Hop algorithm also works in sparse networks.
This thesis examines direction dependent antenna modulation using a Butler matrix and four element antenna array. It provides theoretical background on these concepts and details the design and simulation of a 4x4 Butler matrix and dipole antenna array in CST. MATLAB simulations show direction dependent M-ary modulation schemes achieved using the Butler matrix. Constellations in the desired direction have better shape and power levels than in other directions, proving this approach can improve wireless security. The thesis discusses results and recommendations to further develop directional modulation transmitter systems.
Fpga implementation of soft decision low power convolutional decoder using vi...ecejntuk
1. This document discusses an FPGA implementation of a soft decision low power convolutional decoder using the Viterbi algorithm.
2. It reviews literature on adaptive Viterbi decoding techniques that can improve error performance and reduce computational requirements compared to the standard Viterbi algorithm.
3. Convolutional encoding with Viterbi decoding is described as a forward error correction technique well-suited for channels with additive white Gaussian noise. The document provides examples of how error rates increase as the signal-to-noise ratio decreases.
IRJET- Comparison of ATTEMPT and SIMPLE Protocols for Wireless Body Area Netw...IRJET Journal
This document compares the ATTEMPT and SIMPLE protocols for wireless body area networks (WBANs). ATTEMPT is an opportunistic protocol that relies on relay nodes when the sink node moves out of range, increasing power consumption and packet loss. SIMPLE aims to balance energy usage and improve throughput by selecting low-cost forwarder nodes to route data to the sink in a multi-hop fashion using TDMA scheduling. The document provides detailed descriptions of the initialization, routing, scheduling and data transmission phases of the ATTEMPT and SIMPLE protocols and discusses their advantages and disadvantages for energy efficiency in WBAN applications.
This document discusses a method for eliminating ground stationary low elevation targets (GSLETs) in automotive high resolution radar sensors. It presents a multiple bank correlation algorithm that estimates target height from its multipath return signal in order to identify and eliminate very low, non-hazardous targets. The algorithm contains three main components: 1) predicting the target's amplitude response as a function of range for all possible heights, 2) matching the received signal to the predicted signal for the correct height, and 3) applying detection criteria and thresholds to determine if the target should be eliminated. Simulated and collected radar data are analyzed to assess the performance of the algorithm at eliminating low height nuisance objects.
This document describes a novel snapshot-based approach for direction of arrival (DOA) estimation using the estimation of signal parameters via rotational invariance techniques (ESPRIT) algorithm. It compares ESPRIT to the multiple signal classification (MUSIC) algorithm.
The ESPRIT and MUSIC algorithms are simulated using MATLAB to estimate the DOA of signals received by antenna arrays with different numbers of antenna elements. ESPRIT is shown to provide DOA estimates with less bias than MUSIC. Resolution and sensitivity to noise are also discussed. The novel snapshot-based approach for ESPRIT uses multiple snapshots to estimate the array correlation matrix and improves DOA estimation accuracy.
IRJET- Rapid Spectrum Sensing Algorithm in Cooperative Spectrum Sensing for a...IRJET Journal
This document discusses rapid spectrum sensing algorithms for cooperative spectrum sensing in large cognitive radio networks. It begins with an introduction to cognitive radio and spectrum sensing. It then discusses optimizing cooperative spectrum sensing through determining the optimal voting rule, optimizing the energy detection threshold, and calculating the optimal number of cognitive radios needed. It also describes modeling spectrum sensing using energy detection and calculating the probability of false alarm and detection. Finally, it discusses the receiver operating characteristic of the "AND" voting rule under additive white Gaussian noise. The goal is to suggest a rapid spectrum sensing algorithm for large networks that requires fewer cognitive radios while achieving the necessary error rate bounds.
This document describes the simulation and performance analysis of a MIMO system with spatial multiplexing using polarization diversity. It discusses how dual polarized antennas can be used when antenna spacing constraints cannot be met. The document presents the channel model used, which considers spatial correlation fading and cross-polarization discrimination. It then details the steps of the MATLAB simulation, which generates channel matrices and symbol vectors, adds noise, performs optimal detection, and calculates the symbol error rate for varying SNR values. A plot of SNR versus symbol error count shows the performance of the system.
Discrete wavelet transform-based RI adaptive algorithm for system identificationIJECEIAES
In this paper, we propose a new adaptive filtering algorithm for system identifica- tion. The algorithm is based on the recursive inverse (RI) adaptive algorithm which suffers from low convergence rates in some applications; i.e., the eigenvalue spread of the autocorrelation matrix is relatively high. The proposed algorithm applies discrete-wavelet transform (DWT) to the input signal which, in turn, helps to overcome the low convergence rate of the RI algorithm with relatively small step-size(s). Different scenarios has been investigated in different noise environments in system identification setting. Experiments demonstrate the advantages of the proposed DWT recursive inverse (DWT-RI) filter in terms of convergence rate and mean-square-error (MSE) compared to the RI, discrete cosine transform LMS (DCT-LMS), discretewavelet transform LMS (DWT-LMS) and recursive-least-squares (RLS) algorithms under same conditions.
The document discusses interleaved analog-to-digital converters (ADCs). It begins by explaining that interleaving multiple ADCs allows for an effective sample rate that is a multiple of the individual ADCs' rates. This provides benefits like increased bandwidth. The document then discusses the basics of how interleaving works using clock phase relationships. It explains that while interleaving provides advantages, there are also challenges in the form of mismatches between the ADCs that can cause spurs in the output spectrum. Specifically, it outlines offset, gain, timing, and bandwidth mismatches. The document concludes by stating that knowing about and addressing these mismatches enables the effective use of interleaved ADCs to meet demanding application requirements.
parametric method of power spectrum Estimationjunjer
The document discusses parametric methods of power spectrum estimation. It explains that parametric methods estimate the parameters of a mathematical model that describes the signal generation process. This involves selecting a model such as autoregressive (AR), moving average (MA), or autoregressive moving average (ARMA), estimating the model parameters from the data, and then using the estimated parameters to calculate the power spectrum. The document provides details on how to estimate the power spectrum using AR, MA, and ARMA models. It also discusses maximum entropy spectral estimation and high-resolution spectral estimation based on eigen-analysis.
Mitigating Interference to GPS Operation Using Variable Forgetting Factor Bas...IJCNCJournal
In this paper, an interference method based on signal processing is proposed. The approach is based on
utilizing the maximum likelihood properties of the received signal. The approach is built on maximizing the
probability of the desired data. The GPS data, which is constructed using Binary Phase Shift Keying
(BPSK) modulation, is transmitted as “1’s” and as “0’s.” carried on 1575.42MHz carrier called the L1
frequency. The statistics of the GPS data and interference are utilized in terms of their distribution and
variance. The statistics are used to update (adaptively) the forgetting factor (Lambda) of the Recursive
Least Squares (RLS) filter. The proposed method is called Maximum Likelihood Variable Forgetting Factor
(ML VFF). The adaptive update takes on assigning lambda to the maximum of the probabilities of the
symbols based on the statistics mentioned.
A blind channel shortening for multiuser, multicarrier CDMA system over multi...TELKOMNIKA JOURNAL
In this paper we derive the Multicarrier Equalization by Restoration of Redundancy (MERRY) algorithm: A blind, adaptive channel shortening algorithm for updating a Time-domain Equalizer (TEQ) in a system employing MultiCarrier Code Division Multiple Access (MC-CDMA) modulation. We show that the MERRY algorithm applied to the MC-CDMA system converges considerably more rapidly than in the Orthogonal Frequency Division Multiplexing (OFDM) system [1]. Simulations results are provided to demonstrate the performance of the algorithm.
IRJET- Simulation and Performance Estimation of BPSK in Rayleigh Channel ...IRJET Journal
The document discusses simulation and performance estimation of BPSK modulation in Rayleigh fading channels using three diversity combining techniques: selection combining (SC), maximal ratio combining (MRC), and equal gain combining (EGC). It provides mathematical analysis of how these techniques calculate bit error rate (BER) and compares their performance. The key findings are that MRC achieves the best performance with lowest required SNR, followed by EGC, while SC requires the highest SNR to achieve a given BER. Performance is improved by increasing the number of diversity branches for all techniques.
This paper discusses channel estimation for MIMO-OFDM systems using power delay profile (PDP) techniques. It proposes implementing a PDP estimation method that uses all pilot symbols from transmit antennas to obtain an accurate PDP. This addresses issues caused by insufficient channel impulse response samples and null subcarriers in traditional PDP estimation. The paper finds that using the proposed PDP technique in linear minimum mean square error (LMMSE) channel estimation improves performance by reducing distortion and approaching that of Wiener filtering. Simulation results show the implemented PDP-based LMMSE channel estimation outperforms conventional 1D least squares estimation methods.
Area Versus Speed Trade-off Analysis of a WiMAX Deinterleaver Circuit Designijsrd.com
Trade-off is one of the main design parameters in the field of electronic circuit design. Whereas smaller electronics devices which use less hardware due to techniques like hardware multiplexing or due to smaller devices created due to techniques developed by nanotechnology and MEMS, are more appealing, a trade-off between area, power and speed is inevitable. This paper analyses the trade-off in the design of Wimax deinterleaver. The main aim is to reduce the hardware utilization in a deinterleaver but speed and power consumption are important parameters which cannot be overlooked.
Capacity Enhancement of MIMO-OFDM System in Rayleigh Fading ChannelIOSR Journals
MIMO-OFDM system in Rayleigh Fading Channel is very popular technique for mobile
communication now a day’s for research. Here we want increase the capacity of MIMO-OFDM of system by
using adaptive modulation, Algebraic Space-Time Codes (ASTC) encoder for MIMO Systems are based on
quaternion algebras .we found that ergodic capacity has some limitation which reduce the system’s
performance to overcome this we use ASTC code . ASTC code are full rank, full rate and non vanishing constant
minimum determinant for increasing spectral efficiency and reducing Peak to Average Power Ratio (PAPR) .
Capacity Enhancement of MIMO-OFDM System in Rayleigh Fading ChannelIOSR Journals
Abstract: MIMO-OFDM system in Rayleigh Fading Channel is very popular technique for mobile communication now a day’s for research. Here we want increase the capacity of MIMO-OFDM of system by using adaptive modulation, Algebraic Space-Time Codes (ASTC) encoder for MIMO Systems are based on quaternion algebras .we found that ergodic capacity has some limitation which reduce the system’s performance to overcome this we use ASTC code . ASTC code are full rank, full rate and non vanishing constant minimum determinant for increasing spectral efficiency and reducing Peak to Average Power Ratio (PAPR) . Keywords— Adaptive modulation ASTC code, Capacity, BER, Ergodic capacity, PAPR, Spectral Efficiency and SNR
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PERFORMANCE EVALUATION OF ADAPTIVE ARRAY ANTENNAS IN COGNITIVE RELAY NETWORK
1. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
15
PERFORMANCE EVALUATION OF ADAPTIVE ARRAY
ANTENNAS IN COGNITIVE RELAY NETWORK
Eman Sadik1
, Mona Shokair2
, Abd Elmaged Sharshar3
and Said Elhalafawy4
1,2,3,4
Department of Electronics and Electrical Communication, Faculty of Electronic
Engineering, El- Menoufia University, Menouf, Egypt.
ABSTRACT
Adaptive Array Antennas (AAAs) are expected to play a key role in meeting the demands of the wireless
communication systems of the future. AAAs in cognitive relay network is proposed to reduce the symbol
error rate and improve the system performance. Many algorithms such as wiener solution and least mean
square (LMS) will be explained to show how AAAs in cognitive relay network achieves this object. AAAs
at different locations will be investigated under AWGN and Rayleigh fading channel. Moreover,
enhancement the system performance by showing the effect of increasing the number of AAAs element at
the relay node, increasing the source gain and decreasing the relay gain. In addition, increasing the rate
adaptation and number of iterations in LMS algorithm has significant improvement in the system.
KEYWORDS
Adaptive Array Antennas, cognitive relay network and least mean square algorithm
1. INTRODUCTION
Cognitive radio is used to designate intelligent wireless communication system that is able to
adapt changes occurring in the surrounding environment [1]. It allows Secondary User (SU)
network to coexist with Primary User (PU) network through spectrum sharing, provided that the
secondary spectrum access will not affect the PUs performance [2], [3].
To enhance cognitive radio performance, the cooperative communications that it’s used in [4],
where one or more nodes help the communication between source and destination by acting as
relays, achieve spatial diversity even in a network composed of a single antenna device. In [5],
three protocols of cooperative communications are presented; Amplify and Forward (AF),
Decode and Forward (DF) and Adaptive Relay Protocol (ARP). In the AF protocol, the relay
amplifies the received signal and forwards it to the destination. In the DF protocol, the relay tries
to decode the source message and then re-encodes and forwards it to the destination. ARP is
used to overcome the disadvantage of these two protocols. In our system, AF protocol is used as
its low complexity than the other mentioned.
Another critical issue in cognitive radio is to improve the performance of the system by using
AAAs [6-8]. AAAs is one of the key technologies that are expected to dramatically improve
future wireless communication systems because it has the potential to expand coverage, increase
capacity and improve signal quality. AAAs algorithms, which use reference signal (desired
signal) will be explained in this paper. Other AAAs algorithms, which doesn’t use reference
signal are not considered here. Types of AAAs algorithms used with desired signal are wiener
solution, method of steepest descent, Least Mean Squares (LMS), Normalized Least Mean
2. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
16
Squares (NLMS) and Recursive Least Square (RLS). Wiener solution and LMS algorithms will
be used in this paper. In these algorithms, desired signal is sent during training period. By using
the received desired signal at AAAs, optimum weights can be computed. After the training
period, data is sent and AAAs use the weights computed previously to process the received
signal. AAAs in cognitive relay network will be analysis in this paper to give more improvement
in the system performance.
The reminder of this paper is organized as follows: Section II describes the system model for
the analysis of AAAs in cognitive relay network including wiener solution and LMS algorithms.
Simulation results are illustrated in Section III. Finally, conclusions are made in Section V.
2. SYSTEM MODEL
Figure 1. Adaptive array antenna in cognitive relay network.
AAAs in cognitive relay network at the source, relay and destination is illustrated in Figure 1,
where S, R and D denotes the source, relay and destination respectively. The relay node is
randomly located between the source and the destination to provide most enhancements for the
link. The common channels of S and D will be reserved for the usage of direct link. The
channels used by R for receiving and transmitting are called indirect channels. They are used for
amplifying the received data, and then retransmit it to the destination node.
An antenna array consists of N identical antenna elements arranged in a particular geometry,
where the geometry of the array determines the amount of coverage in a spatial region. AAAs
algorithms, which use the desired signal, will be used in this paper. In these algorithms, desired
signal is sent and by using the received desired signal at AAAs, optimum weights can be
computed. Then, data is sent and AAAs uses the previously computed weights to process the
received signal.
3. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
17
In the following AAAs algorithms are described which try to minimize the mean square error
between the desired signal d (k) and the array output signal y (k).
2.1. Wiener Solution
The error signal e (k) can be expressed as the difference between y (k) and d (k) at sampling
instant k as follows [8],
e ( k) = d(k) –y(k) (1)
Where d(k) is the desired signal and the mean squared error is defined by,
J(k) = E[|e(k)|
] = E[d(k) – y(k)
] (2)
The optimum weights control can be given as
(). = (k)
() (3)
Where = [()
(()∗
)
] is the autocorrelation matrix of the input signal (), =
[()(()
)∗
] is the cross correlation matrix between the complex conjugate of the input
signal and the desired signal.
The output y(k) of linear combination of data for M elements at time k is denoted as,
y(k) = ∑
!
!# ()!() (4)
In vector form the last equation can be written as,
Y(k) = X(k)
%() (5)
Where (. )
is the transpose operator.
2.2. LMS Algorithm
The block diagram of Least Mean Square algorithm is represented in Figure 2. The LMS is an
iterative beamforming algorithm that uses the estimate of the gradient vector from the available
data. The weight vector is updated in accordance with an algorithm that adapts to the incoming
data. The simplicity of LMS algorithm comes from the fact that it doesn’t require measurements
of the correlation functions nor matrix inversion. The updated weight is denoted by [9],
w(k+1) = w(k) + 2 () '∗
() (6)
where μ is defined as the rate of adaptation, controlled by the processing gain of the antenna
array (step size parameter) and e∗
(k) is the complex conjugate of error signal.
4. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
18
Figure 2. Block diagram representation of LMS algorithm.
3. SIMULATION RESULTS
In this section, the numerical results supporting the analysis of adaptive array antenna in
cognitive relay network are presented. Here, the cognitive relay network is demonstrated
consisting of a source, a destination and a cognitive relay node between them. The performance
of AAAs in cognitive relay network is illustrated using wiener solution and LMS algorithms
under AWGN and Rayleigh fading channel. Assume that, the number of transmitted symbols N
is equal to10+
. For simplicity, it is assumed that, the same transmitted power of source and
relay will be applied.
In the following the effect of many parameters will be studied as follows:
3.1. Effect of AAAs at different locations in cognitive relay network
Figure 3 compares Symbol Error Rate (SER) of AAAs at source, relay and destination node
using wiener solution algorithm. Numerical results are obtained by transmitted power of source
,- =
.
, transmitted power of relay ,/ =
.
. As shown in this figure, locating AAAs at the
source has better performance than locating AAAs at the relay and destination.
5. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
19
Figure 3. SER of AAAs at different locations in cognitive relay network.
As the AAAs at the relay node using wiener solution algorithm has the worst performance as
shown in Figure 3, some parameters are studied to enhance the performance of the system.
3.1.1. Increasing the source node gain
Figure 4 shows the numerical results of increasing the antenna gain at the source (0-) node
when AAAs at the relay node under using wiener solution algorithm. From this figure, it can be
concluded that significant improvement in performance is observed by increasing (0-) .
Figure 4. Impact of increasing the source gain when AAAs at the relay node.
3.1.2. Decreasing the relay node gain
The effect of decreasing the antenna gain at the relay (0/) is illustrated in Figure 5 when AAAs
at the relay node using wiener solution algorithm. It is shown in this figure that improving the
system performance is obtained by decreasing 0/ which explained by occurring interference on
the signal.
0 2 4 6 8 10 12 14 16 18 20
10
-5
10
-4
10
-3
10
-2
10
-1
10
0
SNR(dB)
SER
Wiener Solution Algorithm
AAAs at the Source
AAAs at the Relay
AAAs at the Destination
-10 -8 -6 -4 -2 0 2 4 6 8 10
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
SNR(dB)
SER
AAAs at the Relay Node using Winner Solution Algorithm
Gs=Gt/2
Gs=2Gt/3
Gs=3Gt/4
6. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
20
Figure 5. Effect of decreasing the relay gain when AAAs at the relay node.
3.1.3. Increasing AAAs elements
Figure 6 depicts the impact of increasing the number of antennas element of AAAs at the relay
node. We can conclude from this figure that, the performance of the system using AAAs with
three antennas element outperforms using AAAs with two antennas element.
Figure 6. SER at different AAAs elements.
3.1.3.1. Effect of different types of fading channels and noise
The simulative results of AAAs at the source node using wiener solution algorithm under
different fading channels are illustrated in Figure 7. For instance, at SNR =8dB, the SER is
approximately about 101
under AWGN, 10
under Rayleigh fading channel and 10
under
-10 -8 -6 -4 -2 0 2 4 6 8 10
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
SNR(dB)
SER
AAAs at the Relay Node using Winner Solution Algorithm
Gr=Gt/4
Gr=Gt/3
Gr=Gt/2
-10 -8 -6 -4 -2 0 2 4 6 8 10
0.35
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
SNR(dB)
SER
AAAs at the Relay Node using Wiener Solution Algorithm
AAAs with 2 antennas element
AAAs with 3 antennas element
7. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
21
AWGN plus Rayleigh fading channel. The numerical results indicate that AAAs at the source
under AWGN outperforms the other types.
Figure 7. AAAs at the source node under different types of fading channel using wiener
solution.
The effect of different fading channels of AAAs at the source using LMS algorithm is depicted
in figure 8. For instance, at SNR = 15dB, the SER is approximately 10
under AWGN and
102.3
under Rayleigh fading channel. The results show that AAAs at the source under AWGN
has better performance than under Rayleigh fading channel.
Figure 8. AAAs at the source node under different types of fading channel using LMS algorithm.
3.1.3.2. Effect of different step size parameter in LMS algorithm.
Figure 9 provides AAAs at the source using LMS algorithm with AWGN under different step
size parameters. As shown in this figure, by increasing the step size parameter, enhancing the
performance of the system.
0 2 4 6 8 10 12 14 16 18 20
10
-5
10
-4
10
-3
10
-2
10
-1
10
0
SNR(dB)
SER
AAAs at the Source using Wiener Solution Algorithm
Rayleigh Fading Channel
AWGN
Rayleigh Fading Channel+AWGN
10 15 20 25 30 35
10
-4
10
-3
10
-2
10
-1
10
0
SNR(dB)
SER
AAAs at the Source using LMS Algorithm
AWGN
Rayleigh Fading Channel
8. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
22
Figure 9. Compares different step size parameter in LMS algorithm.
3.1.3.3. Effect of different number of iterations in LMS algorithm.
AAAs at the source using LMS algorithm with AWGN under various number of iteration is
shown in Figure 10. From this figure, it’s found that; the performance of the system is improved
by increasing the number of iterations.
Figure 10. Shows different number of iteration in LMS algorithm.
3. CONCLUSIONS
In this paper, Adaptive array antennas in cognitive relay network are presented to enhance the
performance of the network. Wiener solution and least mean square algorithms are analyzed to
calculate the optimum weights. Putting AAAs at different locations such as at the source, relay
and destination are analytically derived. In addition, the system enhancement is investigated
under AWGN and Rayleigh fading channel is proposed. Moreover, increasing the step size
parameter and the number of iteration in LMS algorithm, improve the system performance. The
10 15 20 25 30 35 40
10
-4
10
-3
10
-2
10
-1
10
0
SNR(dB)
SER
AAAs at the Source using LMS with AWGN
mu=0.01
mu=0.02
mu=0.03
mu=0.04
0 2 4 6 8 10 12 14
10
-5
10
-4
10
-3
10
-2
10
-1
10
0
SNR(dB)
SER
AAAs at the Source using LMS with AWGN
No of Iteration=100
No of Iteration=1000
9. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
23
simulation results show that combining adaptive array antennas and cognitive relay network
present significant improvement in the performance of the system.
REFERENCES
[1] J. Mitola, (2000) “Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio,”
Ph.D. dissertation, KTH Royal Inst. of Technol., Stockholm, Sweden.
[2] R. Manna,Y. Louie, Y. li and B. Vucetic, (2011) “Cooperative Spectrum Sharing in Cognitive Radio
Networks with Multiple Antennas”, IEEE Transactions on Signal Processing, vol. 59, no. 11.
[3] E. Sadik, M. Shokair, A. Sharshar and S. Elhalafawy, (2014) “Investigation of Multiple Antennas in
Cooperative Cognitive Relay Network ”, CiiT International Journal of Programmable Device
Circuits and Systems, vol. 6, no. 3, pp. 84-88.
[4] A. Nosratinia, T. E. Hunter, and A. Hedayat, (2004) “Cooperative Communication in Wireless
Networks”, IEEE Communications Magazine, vol. 42, no. 10, pp. 74-80.
[5] E. Sadik, M. Shokair and S. Elhalafawy, (2013) “Performance of Multiple Antennas Cognitive Relay
Networks ”, International Journal of Computer Applications, vol. 81, no. 1, pp. 27-32.
[6] M. Shokair and Y. Akaiwa, (2005) “A Feedback Type Adaptive Array Antenna with One Bit
Feedback Information and Adaptive Update Size in FDD System”, IEICE Transactions, vol. 88-B
(10), pp. 4074-4080.
[7] M. Shokair and Y. Akaiwa, (2006) “Performance of Feedback-type Adaptive Array Antenna in FDD
System with Rake Receiver”, IEICE Transactions on Communications, vol. 89-B, no. 1, pp. 539 -
544.
[8] M. Shokair and Y. Akaiwa, (2003) “The Performance of Feedback-type Adaptive Array Antenna in
FDD/CDMA System with Rake Receiver”, The 57th IEEE Semiannual Vehicular Technology
Conference, vol. 2.
[9] M. Yasin, P. Akhtar and Valiuddin, (2010) “Performance Analysis of LMS and NLMS Algorithms
for a Smart Antenna System”, International Journal of Computer Applications, vol.4, no. 9, pp. 0975
– 8887.
Authors
Eman Sadik was born in Menoufia, Egypt, in 1990. she received her B.Sc. degree in
electronics and electrical Communications engineering from the Faculty of Electronic
Engineering, Menoufia University, Egypt, in 2009.she is an Electrical Engineer at
Faculty of electronic engineer, Menoufia University. Her graduation project was about
open eNB with excellent degree. Her research interests include wireless mobile
communications and next generation networks.
Mona Shokair received the B.Sc., and M.Sc. degrees in electronics engineering from
Menoufia University, Menoufia,Egypt, in 1993, and 1997, respectively. She received the
Ph.D. degree from Kyushu University, Japan, in 2005. She received VTS chapter IEEE
award from Japan, in 2003. She published about 40 papers until 2011. She received the
Associated Professor degree in 2011. Presently, she is an Associated Professor at
Menoufia University. Her research interests include adaptive array antennas, CDMA
system, WIMAX system, OFDM system, and next generation networks.
Abdul-Mageed Sharshar received the B.Sc., and M.Sc. degrees in electronics
engineering from Menoufia University, Menoufia, Egypt, in 1978, and 1982,
respectively. He received the Ph.D. degree from England, London University, in 1991.
Presently, he is Lecturer at faculty of electronic engineering, Menoufia University. He
has published several scientific papers in national and international conferences and
journals. His current research areas of interest include Antennas and Microwaves.
10. Circuits and Systems: An International Journal (CSIJ), Vol.1, No.4, October 2014.
24
Said Elhalafawy received the B.Sc., and M.Sc. degrees in electronics engineering from Menoufia
University,Menoufia, Egypt, in 1978, and 1984, respectively. He received the Ph.D.
degree from Plzen, Czech Republic, in 1990. Presently, he is the dean and Professor at
faculty of electronic engineering, Menoufia University. He has published several
scientific papers in national and international conferences and journals. His current
research areas of interest include image processing, speech processing, digital
communications and electromagnetic applications.