To boost the performance of 4-ary pulse amplitude modulated(PAM) at low signal-to-noise ratio(SNR), bistable stochastic resonance(BSR) system is introduced into digital communications system and get a reliable signal ...To boost the performance of 4-ary pulse amplitude modulated(PAM) at low signal-to-noise ratio(SNR), bistable stochastic resonance(BSR) system is introduced into digital communications system and get a reliable signal detection scheme. In this paper, we first analyse BSR system for different amplitudes of 4-ary PAM signals. The steadystate of the bistable system will be statistically distinct, and the feasibility of the proposed detection scheme is confirmed. On this basis, we present a detailed study on steady-state transitions of the BSR system, and an explicit expression of the bistable system parameters is derived. By setting the bistable system parameters, bistable system, 4-ary PAM signal, and noise reach the resonance state, and the BSR-based detection scheme is implemented. Moreover, we derive an analytical expression to calculate the symbol error rate(SER) of 4-ary PAM signals with the BSR-based detection under additive white Gaussian noise(AWGN). Finally, the simulation results validate that BSR-based detection scheme can improve the detection performance while efficiently reducing the symbol error rate.展开更多
Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complex...Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resulting in slow convergence or high complexity.To address this issue,a low-complexity Approximate Message Passing(AMP)detection algorithm with Deep Neural Network(DNN)(denoted as AMP-DNN)is investigated in this paper.Firstly,an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation(BP)algorithm.Secondly,by unfolding the obtained AMP detection algorithm,a DNN is specifically designed for the optimal performance gain.For the proposed AMP-DNN,the number of trainable parameters is only related to that of layers,regardless of modulation scheme,antenna number and matrix calculation,thus facilitating fast and stable training of the network.In addition,the AMP-DNN can detect different channels under the same distribution with only one training.The superior performance of the AMP-DNN is also verified by theoretical analysis and experiments.It is found that the proposed algorithm enables the reduction of BER without signal prior information,especially in the spatially correlated channel,and has a lower computational complexity compared with existing state-of-the-art methods.展开更多
The structure and performance of space-time multiuser detection receiver at base stations of WCDMA system is analyzed, in which smart antenna is employed. WCDMA uplink signal model is established in this paper. Space-...The structure and performance of space-time multiuser detection receiver at base stations of WCDMA system is analyzed, in which smart antenna is employed. WCDMA uplink signal model is established in this paper. Space-time multiuser receiver presented in this paper combines 2D-RAKE with parallel interference cancellation (PIC), and the improved parallel interference cancellation methods are given. A novel space-time multiuser detection scheme, 2DRAKE-GPPIC is proposed. This scheme employs smart antenna to suppress unexpected DOA (Direction Of Arrival) signal, uses RAKE receiver to combine different delays of expected signal, and utilizes grouped partial parallel interference cancellation (GPPIC) algorithm to suppress further the interference signal in the main lobe of array antennas. The simulation results reveal that the scheme of space-time multiuser detection presented in this paper has better performance for WCDMA system.展开更多
Semantic duplicates in databases represent today an important data quality challenge which leads to bad decisions. In large databases, we sometimes find ourselves with tens of thousands of duplicates, which necessitat...Semantic duplicates in databases represent today an important data quality challenge which leads to bad decisions. In large databases, we sometimes find ourselves with tens of thousands of duplicates, which necessitates an automatic deduplication. For this, it is necessary to detect duplicates, with a fairly reliable method to find as many duplicates as possible and powerful enough to run in a reasonable time. This paper proposes and compares on real data effective duplicates detection methods for automatic deduplication of files based on names, working with French texts or English texts, and the names of people or places, in Africa or in the West. After conducting a more complete classification of semantic duplicates than the usual classifications, we introduce several methods for detecting duplicates whose average complexity observed is less than O(2n). Through a simple model, we highlight a global efficacy rate, combining precision and recall. We propose a new metric distance between records, as well as rules for automatic duplicate detection. Analyses made on a database containing real data for an administration in Central Africa, and on a known standard database containing names of restaurants in the USA, have shown better results than those of known methods, with a lesser complexity.展开更多
The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the...The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems.In this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two stages.The first stage estimates the channel parameters,and the second performsmulti-user detection.The proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural networks.This study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO receivers.The FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.展开更多
In order to suppress the multiple access interference (MAI) in 3G, which limits the capacity of a CDMA communication system, a fast relevance vector machine (FRVM) is employed in the multiuser detection (MUD) scheme. ...In order to suppress the multiple access interference (MAI) in 3G, which limits the capacity of a CDMA communication system, a fast relevance vector machine (FRVM) is employed in the multiuser detection (MUD) scheme. This method aims to overcome the shortcomings of many ordinary support vector machine (SVM) based MUD schemes, such as the long training time and the inaccuracy of the decision data, and enhance the performance of a CDMA communication system. Computer simulation results demonstrate that the proposed FRVM based multiuser detection has lower bit error rate, costs short training time, needs fewer kernel functions and possesses better near-far resistance.展开更多
Symbiotic radio(SR)is an emerging green technology for the Internet of Things(IoT).One key challenge of the SR systems is to design efficient and low-complexity detectors,which is the focus of this paper.We first driv...Symbiotic radio(SR)is an emerging green technology for the Internet of Things(IoT).One key challenge of the SR systems is to design efficient and low-complexity detectors,which is the focus of this paper.We first drive the mathematical expression of the optimal maximum-likelihood(ML)detector,and then propose a suboptimal iterative detector with low complexity.Finally,we show through numerical results that our proposed detector can obtain near-optimal bit error rate(BER)performance at a low computational cost.展开更多
Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential...Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential-detector is proposed for impulse radio ultra wideband (IR-UWB) communication systems. The system employs bit-level differential phase shift keying (DPSK) combined with code division (CD) for IR-UWB signals to support multiple-access (MA). It is analyzed under additive white Gaussian noise (AWGN) corrupted by multiple-access interference (MAI) channel. Its BER performance is compared against a reference coherent receiver using Monte-Carlo simulation method. A closed form expression for its average probability of error is derived analytically. Simulation results and theoretical analysis confirm the applicability of the proposed differential-detector for IR-UWB communication systems.展开更多
Reed-Solomon （RS） codes have been widely adopted in many modern communication systems. This paper describes a new method for error detection in the syndrome calculator block of RS decoders. The main feature of this ...Reed-Solomon （RS） codes have been widely adopted in many modern communication systems. This paper describes a new method for error detection in the syndrome calculator block of RS decoders. The main feature of this method is to prove that it is possible to compute only a few syndrome coeffi- cients -- less than half-- to detect whether the codeword is correct. The theoretical estimate of the prob- ability that the new algorithm failed is shown to depend on the number of syndrome coefficients computed. The algorithm is tested using the RS（204,188） code with the first four coefficients. With a bit error rate of 1 ~ 104, this method reduces the power consumption by 6% compared to the basic RS（204,188） decoder. The error detection algorithm for the syndrome calculator block does not require modification of the basic hardware implementation of the syndrome coefficients computation. The algorithm significantly reduces the computation complexity of the syndrome calculator block, thus lowering the power needed.展开更多
With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social netw...With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social network.This paper explores the social dynamics of such networks by analyzing the eigenvector centrality of vehicles and classifying communication levels based on their centrality rankings.To support this analysis,a communication system is designed using a multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing framework,incorporating the derived communication levels.Within this system,a particle swarm optimization(PSO)algorithm is employed to optimize a radial basis function(RBF)neural network for channel estimation.This approach significantly improves performance,achieving a bit error rate(BER)below 10−4 at relatively low signal-to-noise ratios(SNRs).Moreover,the proposed method enables the system to approach the theoretical channel capacity limit under low SNR conditions.The communication level detection method presented in this work also achieves 100%accuracy across various signal detection techniques.Overall,the proposed signal detection framework offers promising potential for enhancing the performance and reliability of future vehicular communication systems.展开更多
基金supported by the National Natural Science Foundation of China (61631015, 61501354, 61501356, and 61573202)the Fundamental Research Funds of the Ministry of Education (7215433803)+5 种基金the Foundation of State Key Laboratory of Integrated Services Networks (ISN1101002)Higher School Subject Innovation Engineering Plan (B08038)Science and Technology Innovation Team Key Plan of Shaanxi Province (2016KCT-01)The Fundamental Research Funds of the Ministry of Education, China (Grant No. JB160101)The Key Laboratory Foundation of Ministry of Industry and Information Technology (KF20181912)China Postdoctoral Science Foundation (2018M631122)
文摘To boost the performance of 4-ary pulse amplitude modulated(PAM) at low signal-to-noise ratio(SNR), bistable stochastic resonance(BSR) system is introduced into digital communications system and get a reliable signal detection scheme. In this paper, we first analyse BSR system for different amplitudes of 4-ary PAM signals. The steadystate of the bistable system will be statistically distinct, and the feasibility of the proposed detection scheme is confirmed. On this basis, we present a detailed study on steady-state transitions of the BSR system, and an explicit expression of the bistable system parameters is derived. By setting the bistable system parameters, bistable system, 4-ary PAM signal, and noise reach the resonance state, and the BSR-based detection scheme is implemented. Moreover, we derive an analytical expression to calculate the symbol error rate(SER) of 4-ary PAM signals with the BSR-based detection under additive white Gaussian noise(AWGN). Finally, the simulation results validate that BSR-based detection scheme can improve the detection performance while efficiently reducing the symbol error rate.
基金supported by Major Project of Science and Technology Research Program of Chongqing Education Commission of China(Grant No.KJZD-M201900601)China Postdoctoral Science Foundation(Grant No.2021MD703932)Project Supported by Engineering Research Center of Mobile Communications,Ministry of Education,China(Grant No.cqupt-mct-202006)。
文摘Signal detection plays an essential role in massive Multiple-Input Multiple-Output(MIMO)systems.However,existing detection methods have not yet made a good tradeoff between Bit Error Rate(BER)and computational complexity,resulting in slow convergence or high complexity.To address this issue,a low-complexity Approximate Message Passing(AMP)detection algorithm with Deep Neural Network(DNN)(denoted as AMP-DNN)is investigated in this paper.Firstly,an efficient AMP detection algorithm is derived by scalarizing the simplification of Belief Propagation(BP)algorithm.Secondly,by unfolding the obtained AMP detection algorithm,a DNN is specifically designed for the optimal performance gain.For the proposed AMP-DNN,the number of trainable parameters is only related to that of layers,regardless of modulation scheme,antenna number and matrix calculation,thus facilitating fast and stable training of the network.In addition,the AMP-DNN can detect different channels under the same distribution with only one training.The superior performance of the AMP-DNN is also verified by theoretical analysis and experiments.It is found that the proposed algorithm enables the reduction of BER without signal prior information,especially in the spatially correlated channel,and has a lower computational complexity compared with existing state-of-the-art methods.
文摘The structure and performance of space-time multiuser detection receiver at base stations of WCDMA system is analyzed, in which smart antenna is employed. WCDMA uplink signal model is established in this paper. Space-time multiuser receiver presented in this paper combines 2D-RAKE with parallel interference cancellation (PIC), and the improved parallel interference cancellation methods are given. A novel space-time multiuser detection scheme, 2DRAKE-GPPIC is proposed. This scheme employs smart antenna to suppress unexpected DOA (Direction Of Arrival) signal, uses RAKE receiver to combine different delays of expected signal, and utilizes grouped partial parallel interference cancellation (GPPIC) algorithm to suppress further the interference signal in the main lobe of array antennas. The simulation results reveal that the scheme of space-time multiuser detection presented in this paper has better performance for WCDMA system.
文摘Semantic duplicates in databases represent today an important data quality challenge which leads to bad decisions. In large databases, we sometimes find ourselves with tens of thousands of duplicates, which necessitates an automatic deduplication. For this, it is necessary to detect duplicates, with a fairly reliable method to find as many duplicates as possible and powerful enough to run in a reasonable time. This paper proposes and compares on real data effective duplicates detection methods for automatic deduplication of files based on names, working with French texts or English texts, and the names of people or places, in Africa or in the West. After conducting a more complete classification of semantic duplicates than the usual classifications, we introduce several methods for detecting duplicates whose average complexity observed is less than O(2n). Through a simple model, we highlight a global efficacy rate, combining precision and recall. We propose a new metric distance between records, as well as rules for automatic duplicate detection. Analyses made on a database containing real data for an administration in Central Africa, and on a known standard database containing names of restaurants in the USA, have shown better results than those of known methods, with a lesser complexity.
文摘The numbers of multimedia applications and their users increase with each passing day.Different multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network systems.In this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two stages.The first stage estimates the channel parameters,and the second performsmulti-user detection.The proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural networks.This study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO receivers.The FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.
文摘In order to suppress the multiple access interference (MAI) in 3G, which limits the capacity of a CDMA communication system, a fast relevance vector machine (FRVM) is employed in the multiuser detection (MUD) scheme. This method aims to overcome the shortcomings of many ordinary support vector machine (SVM) based MUD schemes, such as the long training time and the inaccuracy of the decision data, and enhance the performance of a CDMA communication system. Computer simulation results demonstrate that the proposed FRVM based multiuser detection has lower bit error rate, costs short training time, needs fewer kernel functions and possesses better near-far resistance.
文摘Symbiotic radio(SR)is an emerging green technology for the Internet of Things(IoT).One key challenge of the SR systems is to design efficient and low-complexity detectors,which is the focus of this paper.We first drive the mathematical expression of the optimal maximum-likelihood(ML)detector,and then propose a suboptimal iterative detector with low complexity.Finally,we show through numerical results that our proposed detector can obtain near-optimal bit error rate(BER)performance at a low computational cost.
文摘Noncoherent communication receivers (differential-detectors) have simple design, however, they always incur bit error rate (BER) performance loss up to 3dB compared to coherent receivers. In this paper, a differential-detector is proposed for impulse radio ultra wideband (IR-UWB) communication systems. The system employs bit-level differential phase shift keying (DPSK) combined with code division (CD) for IR-UWB signals to support multiple-access (MA). It is analyzed under additive white Gaussian noise (AWGN) corrupted by multiple-access interference (MAI) channel. Its BER performance is compared against a reference coherent receiver using Monte-Carlo simulation method. A closed form expression for its average probability of error is derived analytically. Simulation results and theoretical analysis confirm the applicability of the proposed differential-detector for IR-UWB communication systems.
基金Supported by the National High-Tech Research and Development (863) Program of China (No. 2007AA01Z2B3)
文摘Reed-Solomon （RS） codes have been widely adopted in many modern communication systems. This paper describes a new method for error detection in the syndrome calculator block of RS decoders. The main feature of this method is to prove that it is possible to compute only a few syndrome coeffi- cients -- less than half-- to detect whether the codeword is correct. The theoretical estimate of the prob- ability that the new algorithm failed is shown to depend on the number of syndrome coefficients computed. The algorithm is tested using the RS（204,188） code with the first four coefficients. With a bit error rate of 1 ~ 104, this method reduces the power consumption by 6% compared to the basic RS（204,188） decoder. The error detection algorithm for the syndrome calculator block does not require modification of the basic hardware implementation of the syndrome coefficients computation. The algorithm significantly reduces the computation complexity of the syndrome calculator block, thus lowering the power needed.
基金supported by the Open Fund Project of Key Laboratory of Marine Environmental Survey Technology and Application,Ministry of Natural Resources(No.MESTA-2024-B004).
文摘With the rapid advancement of the automotive industry,the demand for vehicle-centric communication continues to grow.In vehicular ad hoc networks(VANETs),the interactions among vehicles can be modeled as a social network.This paper explores the social dynamics of such networks by analyzing the eigenvector centrality of vehicles and classifying communication levels based on their centrality rankings.To support this analysis,a communication system is designed using a multiple-input multiple-output(MIMO)orthogonal frequency division multiplexing framework,incorporating the derived communication levels.Within this system,a particle swarm optimization(PSO)algorithm is employed to optimize a radial basis function(RBF)neural network for channel estimation.This approach significantly improves performance,achieving a bit error rate(BER)below 10−4 at relatively low signal-to-noise ratios(SNRs).Moreover,the proposed method enables the system to approach the theoretical channel capacity limit under low SNR conditions.The communication level detection method presented in this work also achieves 100%accuracy across various signal detection techniques.Overall,the proposed signal detection framework offers promising potential for enhancing the performance and reliability of future vehicular communication systems.
