Since the outbreak of the epidemic, people not only need to pay attention to their own safety and health, but also need insurance services to protect themselves. However, there are some problems in the traditional insurance system. First, the information of clients is incomplete or untrue. Second, privacy is compromised. Third, transaction information is tampered with. These problems lead to various insurance disputes. Therefore, this paper develops an insurance system based on blockchain by using the characteristics of decentralization, transparency, and immutability. The construction of the system is divided into three steps. First, insurance contracts are published on the Merkel tree. Next, RSA encryption technology is used to protect clients' information security. Last, SHA256 secure hash algorithm and consensus mechanism are used to resist the external attack of the blockchain. On this basis, this paper designs and develops a safe insurance system. Also, it studies the performance of insurance systems and the consensus mechanism of blockchain. The former compares the differences between the traditional insurance system and the blockchain insurance system in each performance index during operation. The result shows that some performance indices of blockchain insurance system are lower than those of traditional insurance system. However, because of its higher security than traditional insurance system, blockchain technology is selected as the core technology of this system. Also, two consensus algorithms, PoW and PBFT, compares with each other in blockchain technology. The experimental results show that the PoW consensus algorithm is more suitable for blockchain insurance system.
{"title":"Design and Development of Insurance System Based on PoW Consensus Algorithm","authors":"Qing Zhang, Xinyu Yao, Wenjing Zhang, Yingchuan Yang, Ya Xu, Chao-Hsien Hsieh","doi":"10.1109/ICICSP55539.2022.10050543","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050543","url":null,"abstract":"Since the outbreak of the epidemic, people not only need to pay attention to their own safety and health, but also need insurance services to protect themselves. However, there are some problems in the traditional insurance system. First, the information of clients is incomplete or untrue. Second, privacy is compromised. Third, transaction information is tampered with. These problems lead to various insurance disputes. Therefore, this paper develops an insurance system based on blockchain by using the characteristics of decentralization, transparency, and immutability. The construction of the system is divided into three steps. First, insurance contracts are published on the Merkel tree. Next, RSA encryption technology is used to protect clients' information security. Last, SHA256 secure hash algorithm and consensus mechanism are used to resist the external attack of the blockchain. On this basis, this paper designs and develops a safe insurance system. Also, it studies the performance of insurance systems and the consensus mechanism of blockchain. The former compares the differences between the traditional insurance system and the blockchain insurance system in each performance index during operation. The result shows that some performance indices of blockchain insurance system are lower than those of traditional insurance system. However, because of its higher security than traditional insurance system, blockchain technology is selected as the core technology of this system. Also, two consensus algorithms, PoW and PBFT, compares with each other in blockchain technology. The experimental results show that the PoW consensus algorithm is more suitable for blockchain insurance system.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125887590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050614
Yejin Wang, Maonian Wu, Bo Zheng, Shaojun Zhu
In this paper, a new open source dialect speech corpus is proposed. It is by far the only open source Goetian dialect corpus, suitable for conducting speech recognition research and building a speech recognition system for Huzhou dialect. This corpus contains about 184 hours of speech and corresponding subtitle transcriptions. In addition, an automated method for building speech recognition corpus is proposed. Only the film and television materials with subtitles are needed to build the speech recognition corpus automatically. Tested on four classical speech recognition frameworks to demonstrate the effectiveness of the corpus for training different speech recognition systems.
{"title":"HuZhouSpeech: A Huzhou Dialect Speech Recognition Corpus","authors":"Yejin Wang, Maonian Wu, Bo Zheng, Shaojun Zhu","doi":"10.1109/ICICSP55539.2022.10050614","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050614","url":null,"abstract":"In this paper, a new open source dialect speech corpus is proposed. It is by far the only open source Goetian dialect corpus, suitable for conducting speech recognition research and building a speech recognition system for Huzhou dialect. This corpus contains about 184 hours of speech and corresponding subtitle transcriptions. In addition, an automated method for building speech recognition corpus is proposed. Only the film and television materials with subtitles are needed to build the speech recognition corpus automatically. Tested on four classical speech recognition frameworks to demonstrate the effectiveness of the corpus for training different speech recognition systems.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"2 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126079945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050643
Yuqi Wang, Xianpeng Wang, Xiang Lan, Zhiguang Han
In this paper, we describe an algorithm for frequency modulated continuous wave (FMCW) radar to monitor vital signs. The FMCW waveforms have inherent range-gating capability and are sensitive to small object displacements. Based on the advantages, we use the traditional direction-of-arrival (DOA) estimation algorithm-multiple signal classification (MUSIC) algorithm to monitor vital signs. The simulated annealing algorithm is applied to solve the raster search problem of MUSIC algorithm and improves its accuracy. Simulation results show that this algorithm is superior to traditional FFT algorithm. The feasibility of the algorithm is verified by processing the received data of FMCW sensor.
{"title":"Vital Signs Monitoring Using FMCW Millimeter-Wave Sensor via Simulated Annealing MUSIC Algorithm","authors":"Yuqi Wang, Xianpeng Wang, Xiang Lan, Zhiguang Han","doi":"10.1109/ICICSP55539.2022.10050643","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050643","url":null,"abstract":"In this paper, we describe an algorithm for frequency modulated continuous wave (FMCW) radar to monitor vital signs. The FMCW waveforms have inherent range-gating capability and are sensitive to small object displacements. Based on the advantages, we use the traditional direction-of-arrival (DOA) estimation algorithm-multiple signal classification (MUSIC) algorithm to monitor vital signs. The simulated annealing algorithm is applied to solve the raster search problem of MUSIC algorithm and improves its accuracy. Simulation results show that this algorithm is superior to traditional FFT algorithm. The feasibility of the algorithm is verified by processing the received data of FMCW sensor.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116047317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050663
Can Yao, C. Li, Xue Jin, Lei Zhang
Ship target detection in synthetic aperture radar (SAR) images via the classical constant false alarm rate (CFAR) algorithm is an important technique. However, each pixel in local sliding window detection is involved in parameter estimation multiple times, which leads to computational inefficiency, especially for large-scale SAR images. To solve the above issue, this paper proposes a fast two-parameter CFAR algorithm based on fast Fourier transform (FFT), named F2T-CFAR. First, FFT is employed to replace the sliding window detection and statistical properties are obtained by global computation. Second, we extract potential target points from the global detection results by threshold decision and subsequently cluster these potential points using the density-based spatial clustering of applications with noise (DBSCAN) algorithm to obtain the final ship target centers. Our F2T-CFAR significantly improves the computational speed compared to the two-threshold CFAR method. Experiments on the measured large-scale SAR images demonstrate the effectiveness of our F2T-CFAR algorithm.
{"title":"A Fast Two-Parameter CFAR Algorithm Based on FFT for Ship Detection in Large-Scale SAR Images","authors":"Can Yao, C. Li, Xue Jin, Lei Zhang","doi":"10.1109/ICICSP55539.2022.10050663","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050663","url":null,"abstract":"Ship target detection in synthetic aperture radar (SAR) images via the classical constant false alarm rate (CFAR) algorithm is an important technique. However, each pixel in local sliding window detection is involved in parameter estimation multiple times, which leads to computational inefficiency, especially for large-scale SAR images. To solve the above issue, this paper proposes a fast two-parameter CFAR algorithm based on fast Fourier transform (FFT), named F2T-CFAR. First, FFT is employed to replace the sliding window detection and statistical properties are obtained by global computation. Second, we extract potential target points from the global detection results by threshold decision and subsequently cluster these potential points using the density-based spatial clustering of applications with noise (DBSCAN) algorithm to obtain the final ship target centers. Our F2T-CFAR significantly improves the computational speed compared to the two-threshold CFAR method. Experiments on the measured large-scale SAR images demonstrate the effectiveness of our F2T-CFAR algorithm.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"84 11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122378020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050677
Mengchao Zhan, Feng Xi, Shengyao Chen
This paper introduces a new direction-of-arrival (DOA) estimation method for multi-snapshot narrowband signals. To reduce the system cost, we adopt one-bit compressed sensing in the process of sampling and quantization for analog signals. We propose a deep unfolded network (DUN) based on multiple measurement vectors (MMVs), known as the learned MMV-based binary iteration soft threshold (L-MMV-BIST) network, to estimate the DOAs from the one-bit measurements. This new DUN is designed by unfolding each update of the binary iterative soft threshold algorithm (ISTA) into a layer of a deep neural network, thus it has the ability to learn soft threshold and other iteration parameters adaptively. Our simulation results show that the L-MMV -BIST network can estimate DOA information from the one-bit measurements. In addition, this network outperforms traditional BIST algorithm in both computational complexity and recovery accuracy.
{"title":"A Multiple Measurement Vector-Based Deep Unfolded Network for One-bit DOA Estimation","authors":"Mengchao Zhan, Feng Xi, Shengyao Chen","doi":"10.1109/ICICSP55539.2022.10050677","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050677","url":null,"abstract":"This paper introduces a new direction-of-arrival (DOA) estimation method for multi-snapshot narrowband signals. To reduce the system cost, we adopt one-bit compressed sensing in the process of sampling and quantization for analog signals. We propose a deep unfolded network (DUN) based on multiple measurement vectors (MMVs), known as the learned MMV-based binary iteration soft threshold (L-MMV-BIST) network, to estimate the DOAs from the one-bit measurements. This new DUN is designed by unfolding each update of the binary iterative soft threshold algorithm (ISTA) into a layer of a deep neural network, thus it has the ability to learn soft threshold and other iteration parameters adaptively. Our simulation results show that the L-MMV -BIST network can estimate DOA information from the one-bit measurements. In addition, this network outperforms traditional BIST algorithm in both computational complexity and recovery accuracy.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122967192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Considering the problem of low recognition rate and a large number of parameters in end-to-end modulation recognition methods based on deep learning, a CNN-LSTM dual channel(DCNN-LSTM) modulation recognition method based on the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory(LSTM) network is proposed in this paper. Firstly, the proposed method extracts the frequency domain features of the IQ signal using one-dimensional convolution in the CNN channel and the time-domain features of the transformed AP data of the IQ signal in the LSTM channel. Then, fusing the features of the two channels by the Concatenate operation and convolution layer. Finally, the method uses Global Average Pooling (GAP) instead of Flatten, which integrates the feature information of the vectors without additional parameters. Experimentally, the number of parameters of the proposed method is respectively reduced by 98.4%, 77.8%, and 88.9% compared with CNN, LSTM, and SCRNN, while the recognition rate is respectively improved by 9.7%, 3.3%, and 0.4%. The method proposed in this paper has theoretical reference value for the research field of communication modulation signal recognition, and engineering reference significance for the study of the intelligent classification of spatial signals in complex environments.
针对基于深度学习的端到端调制识别方法识别率低、参数多的问题，提出了一种基于卷积神经网络(CNN)和长短期记忆(LSTM)网络相结合的CNN-LSTM双通道(DCNN-LSTM)调制识别方法。该方法首先利用CNN信道中的一维卷积和LSTM信道中IQ信号变换后的AP数据的时域特征提取IQ信号的频域特征;然后，通过连接操作和卷积层融合两个通道的特征。最后，该方法采用Global Average Pooling (GAP)代替Flatten，在不增加参数的情况下集成了向量的特征信息。实验结果表明，与CNN、LSTM和SCRNN相比，本文方法的参数个数分别减少了98.4%、77.8%和88.9%，识别率分别提高了9.7%、3.3%和0.4%。本文提出的方法对通信调制信号识别研究领域具有理论参考价值，对复杂环境下空间信号的智能分类研究具有工程参考意义。
{"title":"Modulation Recognition Method of Communication Signal Based on CNN-LSTM Dual Channel","authors":"Yanjie Ren, Xiaogang Tang, Binquan Zhang, Junhao Feng, Minghui Gao","doi":"10.1109/ICICSP55539.2022.10050630","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050630","url":null,"abstract":"Considering the problem of low recognition rate and a large number of parameters in end-to-end modulation recognition methods based on deep learning, a CNN-LSTM dual channel(DCNN-LSTM) modulation recognition method based on the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory(LSTM) network is proposed in this paper. Firstly, the proposed method extracts the frequency domain features of the IQ signal using one-dimensional convolution in the CNN channel and the time-domain features of the transformed AP data of the IQ signal in the LSTM channel. Then, fusing the features of the two channels by the Concatenate operation and convolution layer. Finally, the method uses Global Average Pooling (GAP) instead of Flatten, which integrates the feature information of the vectors without additional parameters. Experimentally, the number of parameters of the proposed method is respectively reduced by 98.4%, 77.8%, and 88.9% compared with CNN, LSTM, and SCRNN, while the recognition rate is respectively improved by 9.7%, 3.3%, and 0.4%. The method proposed in this paper has theoretical reference value for the research field of communication modulation signal recognition, and engineering reference significance for the study of the intelligent classification of spatial signals in complex environments.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122050925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050612
Siyuan Cang, Xueli Sheng, A. Jakobsson, Huayong Yang
Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is efficiently solved using the alternating direction method of multipliers (ADMM). The performance of the proposed algorithm is demonstrated using simulations and experimental data collected from South China Sea.
{"title":"Robust Deconvolution of Underwater Acoustic Channels Corrupted by Impulsive Noise","authors":"Siyuan Cang, Xueli Sheng, A. Jakobsson, Huayong Yang","doi":"10.1109/ICICSP55539.2022.10050612","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050612","url":null,"abstract":"Impulsive noise is one of the most challenging forms of interference in an underwater acoustic environment. In this paper, we present an underwater acoustic channel deconvolution method based on a sparse representation framework. The application of the method enables a channel impulse response reconstruction that is robust to impulsive noise. By exploiting the inherent structure in the channel response, the measured signal may be expressed as depending on the unknown channel in a multiplicative manner, enabling an efficient deconvolution framework. This allow us introduce an lp-norm optimization framework that is then adopted to deconvoluting the under-water acoustic channel in the presence of impulsive noise. The resulting framework is efficiently solved using the alternating direction method of multipliers (ADMM). The performance of the proposed algorithm is demonstrated using simulations and experimental data collected from South China Sea.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"50 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116828470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Government organizations are digitizing their services. The purpose is to improve efficiency and provide better services for users. But, every platform is inefficient to connect with each other so far. Therefore, with the characteristics of resource sharing, fast computing speed, and high reliability of distributed system, this paper develops a security and efficient government affairs system with a novel path recommendation algorithm. The purpose is to recommend appropriate government agency for offline affair of user. The algorithm contains three functions, distance priority, time priority, and mixed average priority. Then, the system recommends the appropriate standard by comparing the total cost of the three functions. However, this paper retrieves the location of real government departments and then generates users with uniform distribution for simulation experiments. There are some specific experimental results in this paper. First, as the user interval is smaller, the proportion gap between government agencies receiving users is getting smaller as well. Second, as the user interval is large, moderate, and small, the system then will select distance priority function, time priority function, mixed average priority function for recommendation, respectively.
{"title":"A Novel Path Recommendation Algorithm for Efficient and Secure Government Affairs System","authors":"Xinyun Yao, Yubo Song, Xingmin Zou, Qi Lu, Chao-Hsien Hsieh","doi":"10.1109/ICICSP55539.2022.10050645","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050645","url":null,"abstract":"Government organizations are digitizing their services. The purpose is to improve efficiency and provide better services for users. But, every platform is inefficient to connect with each other so far. Therefore, with the characteristics of resource sharing, fast computing speed, and high reliability of distributed system, this paper develops a security and efficient government affairs system with a novel path recommendation algorithm. The purpose is to recommend appropriate government agency for offline affair of user. The algorithm contains three functions, distance priority, time priority, and mixed average priority. Then, the system recommends the appropriate standard by comparing the total cost of the three functions. However, this paper retrieves the location of real government departments and then generates users with uniform distribution for simulation experiments. There are some specific experimental results in this paper. First, as the user interval is smaller, the proportion gap between government agencies receiving users is getting smaller as well. Second, as the user interval is large, moderate, and small, the system then will select distance priority function, time priority function, mixed average priority function for recommendation, respectively.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"304 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129857520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050568
Yirui Guo, Jun Zou, Guangzu Liu, Lin Guo
A beamforming and power allocation method for IRs-based NOMA systems is proposed in this paper. The method designs beamforming vectors under three different strategies, and optimizes the power distribution factor based on maximizing the sum transmission rate, and alternates between beamforming vector and power distribution factor, finally the optimal beamforming vector and the power distribution factor are obtained. At the same time, the sum transmission rate, the number of iterations are taken as the performance indexes of the proposed algorithm. The simulation results show that when designing the beamforming vector based on the principle of maximizing the useful signal energy, compared with the forced zero design and the traditional fixed-beamforming vector and fixed-power distribution factor strategy, it can significantly improve the sum transmission rate.
{"title":"Research on Beamforming and Power Allocation in IRS-BASED NOMA System","authors":"Yirui Guo, Jun Zou, Guangzu Liu, Lin Guo","doi":"10.1109/ICICSP55539.2022.10050568","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050568","url":null,"abstract":"A beamforming and power allocation method for IRs-based NOMA systems is proposed in this paper. The method designs beamforming vectors under three different strategies, and optimizes the power distribution factor based on maximizing the sum transmission rate, and alternates between beamforming vector and power distribution factor, finally the optimal beamforming vector and the power distribution factor are obtained. At the same time, the sum transmission rate, the number of iterations are taken as the performance indexes of the proposed algorithm. The simulation results show that when designing the beamforming vector based on the principle of maximizing the useful signal energy, compared with the forced zero design and the traditional fixed-beamforming vector and fixed-power distribution factor strategy, it can significantly improve the sum transmission rate.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128611898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.1109/ICICSP55539.2022.10050683
Daofang Feng, Wei Pan, Anlai Mao, Bingjian Jin, Yuanwen Li, Min Li
During the particle velocity reconstruction, the sound energy will be dissipated and the particle velocity will be underestimated, due to the attenuation characteristic of particle velocity and the interference of measurement noise. To solve the above problem, an equivalent source method based on the sound pressure differential filter (PDF-ESM) was proposed. The method uses the sound pressure differential filter to obtain the distribution information of the sound source and focus the sound energy. Meanwhile, it uses the sparse equivalent source method to solve the precise source strength and reconstruct the particle velocity. Simulation and experiment of coherent and incoherent sound sources over 200–1600 Hz show the particle velocity results computed by PDF-ESM have smaller side lobes after the sound energy is focused and smaller reconstruction errors.
{"title":"An Equivalent Source Method Based on Sound Pressure Differential Filter for Particle Velocity Reconstruction","authors":"Daofang Feng, Wei Pan, Anlai Mao, Bingjian Jin, Yuanwen Li, Min Li","doi":"10.1109/ICICSP55539.2022.10050683","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050683","url":null,"abstract":"During the particle velocity reconstruction, the sound energy will be dissipated and the particle velocity will be underestimated, due to the attenuation characteristic of particle velocity and the interference of measurement noise. To solve the above problem, an equivalent source method based on the sound pressure differential filter (PDF-ESM) was proposed. The method uses the sound pressure differential filter to obtain the distribution information of the sound source and focus the sound energy. Meanwhile, it uses the sparse equivalent source method to solve the precise source strength and reconstruct the particle velocity. Simulation and experiment of coherent and incoherent sound sources over 200–1600 Hz show the particle velocity results computed by PDF-ESM have smaller side lobes after the sound energy is focused and smaller reconstruction errors.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124673536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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