Video analysis using artificial intelligence (AI) is widely adopted in various services. However, ground users with limited resources may not process such tasks locally. Fortunately, the ultra-dense low earth orbit (LEO) satellite networks allow multiple satellites to cooperatively handle these tasks to provide low-latency computing services. Therefore, this paper considers a cooperative computation offloading scheme for video analysis in ultra-dense LEO satellite-terrestrial networks, allowing for flexible task scheduling and video quality selection. Considering the privacy of satellites and the dynamic network environment, the cooperative computation offloading problem is established as a distributed Markov decision process (MDP) to reduce the task delay while increasing the accuracy of video analysis. Then, a multi-agent deep reinforcement learning (DRL) approach is proposed to obtain efficient offloading strategies. Finally, simulations are conducted to verify the feasibility and performance of the proposed scheme.
{"title":"Cooperative Computation Offloading for Video Analysis in Ultra-Dense LEO Satellite-Terrestrial Networks","authors":"Qi Zhao, Tianjiao Chen, Jiang Liu, Fangqi Liu, Yuke Zhou","doi":"10.1109/ICICSP55539.2022.10050637","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050637","url":null,"abstract":"Video analysis using artificial intelligence (AI) is widely adopted in various services. However, ground users with limited resources may not process such tasks locally. Fortunately, the ultra-dense low earth orbit (LEO) satellite networks allow multiple satellites to cooperatively handle these tasks to provide low-latency computing services. Therefore, this paper considers a cooperative computation offloading scheme for video analysis in ultra-dense LEO satellite-terrestrial networks, allowing for flexible task scheduling and video quality selection. Considering the privacy of satellites and the dynamic network environment, the cooperative computation offloading problem is established as a distributed Markov decision process (MDP) to reduce the task delay while increasing the accuracy of video analysis. Then, a multi-agent deep reinforcement learning (DRL) approach is proposed to obtain efficient offloading strategies. Finally, simulations are conducted to verify the feasibility and performance of the proposed scheme.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"64 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":"114694303","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/ICICSP55539.2022.10050660
Dongwen Xue, Yan Qun Yan, Zhuohan Li, Jiafeng Yang
The acoustic liner which installed at the internal part of the nacelle is applied to reduce the fan noise, which is the main noise source of the aircraft. Acoustic liner is submitted to high flow velocity over 0.6Ma and high frequency over 6000Hz. In order to research the sound absorption characteristics of the acoustic liner in the high frequency and high flow velocity range, the two-microphones method and the straightforward method were used for impedance eduction at high frequency and high flow velocity. In the straightforward method, the microphones distributed along the axial direction are located on the mid-length of the width of the upper wall opposite to the test liner to increase its frequency range. The applicability of a semi-empirical impedance model in the high frequency and high flow velocity range was evaluated. In the frequency range below 400Hz, the two-microphones method has higher test accuracy. The method based on the arrangement of the microphones located on the mid-length of the width of the upper wall opposite to the test liner can increase the upper limit of the impedance extraction frequency of the straightforward method. The two-microphones method is suitable for higher frequency and flow velocity ranges. For the classical perforated plate acoustic liner, the acoustic resistance increases with the increase of the flow velocity, and the acoustic impedance is hardly affected by the flow velocity. In the high flow velocity range, the impedance model predicted acoustic resistance slightly larger than the impedance measurement.
{"title":"Impedance Eduction of Acoustic Liners with High Grazing Flow and High Frequency","authors":"Dongwen Xue, Yan Qun Yan, Zhuohan Li, Jiafeng Yang","doi":"10.1109/ICICSP55539.2022.10050660","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050660","url":null,"abstract":"The acoustic liner which installed at the internal part of the nacelle is applied to reduce the fan noise, which is the main noise source of the aircraft. Acoustic liner is submitted to high flow velocity over 0.6Ma and high frequency over 6000Hz. In order to research the sound absorption characteristics of the acoustic liner in the high frequency and high flow velocity range, the two-microphones method and the straightforward method were used for impedance eduction at high frequency and high flow velocity. In the straightforward method, the microphones distributed along the axial direction are located on the mid-length of the width of the upper wall opposite to the test liner to increase its frequency range. The applicability of a semi-empirical impedance model in the high frequency and high flow velocity range was evaluated. In the frequency range below 400Hz, the two-microphones method has higher test accuracy. The method based on the arrangement of the microphones located on the mid-length of the width of the upper wall opposite to the test liner can increase the upper limit of the impedance extraction frequency of the straightforward method. The two-microphones method is suitable for higher frequency and flow velocity ranges. For the classical perforated plate acoustic liner, the acoustic resistance increases with the increase of the flow velocity, and the acoustic impedance is hardly affected by the flow velocity. In the high flow velocity range, the impedance model predicted acoustic resistance slightly larger than the impedance measurement.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"62 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":"114570608","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/ICICSP55539.2022.10050574
Yang Lv, Haoyuan Gao, Rui Wu, Xiao-pei Wu
Biometrics has received extensive attention due to its accuracy and convenience. However, commonly used biometric features still have deficiencies. Facial recognition is a potential threat to privacy, and iris recognition or heartbeat recognition requires specific acquisition equipment, resulting in additional costs. To address this issue, we proposed a novel biometric identification method using image photoplethysmographic (IPPG). IPPG signal is easy collection with a consumer camera and the pixel-averaging operation to extract IPPG signal will remove private facial information. As a vital sign, IPPG signal is difficult to fake using abiotic prostheses. We constructed a CNN-based identification with IPPG (ID-IPPG) to verify the performance of IPPG signals in human identification. The proposed model achieves 97.3% accuracy on IPPG signals dataset containing 12 subjects. Moreover, the model can effectively perform in living body detection. The results demonstrate that IPPG signals contain individual physiological information and the ID-IPPG has high accuracy and security for human identification.
{"title":"CNN-Based Human Identification Method Using Image Photoplethysmographic","authors":"Yang Lv, Haoyuan Gao, Rui Wu, Xiao-pei Wu","doi":"10.1109/ICICSP55539.2022.10050574","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050574","url":null,"abstract":"Biometrics has received extensive attention due to its accuracy and convenience. However, commonly used biometric features still have deficiencies. Facial recognition is a potential threat to privacy, and iris recognition or heartbeat recognition requires specific acquisition equipment, resulting in additional costs. To address this issue, we proposed a novel biometric identification method using image photoplethysmographic (IPPG). IPPG signal is easy collection with a consumer camera and the pixel-averaging operation to extract IPPG signal will remove private facial information. As a vital sign, IPPG signal is difficult to fake using abiotic prostheses. We constructed a CNN-based identification with IPPG (ID-IPPG) to verify the performance of IPPG signals in human identification. The proposed model achieves 97.3% accuracy on IPPG signals dataset containing 12 subjects. Moreover, the model can effectively perform in living body detection. The results demonstrate that IPPG signals contain individual physiological information and the ID-IPPG has high accuracy and security for human identification.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"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":"116817117","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/ICICSP55539.2022.10050686
Hai Huang, Shengqi Zhu, Xiongpeng He, Ximin Li, Jingwei Xu, Kun Liu
Existing imaging methods about Bistatic SAR(BiSAR) mostly consider small scene with single channel and ignore the negative effects of range ambiguity. In order to address this problem, a wide-swath imaging method based on multiple-input multiple-output(MIMO) BiSAR system is proposed in this paper. Firstly, the element pulse coding(EPC) MIMO BiSAR model is established by modulating both of elements and pulses. After that, the spatial filtering technique is utilized to separate signals from different range regions. Then, the Doppler preprocessing that based on the prior configuration information is performed to eliminate the Doppler centroid ambiguity. Finally, classical imaging method is performed, and the wide-swath imaging results can be obtained. Numerical simulations verify the proposed method.
现有的双基地SAR(BiSAR)成像方法多考虑单通道小场景，忽略了距离模糊的负面影响。为了解决这一问题，本文提出了一种基于多输入多输出(MIMO) BiSAR系统的宽幅成像方法。首先，通过对单元和脉冲进行调制，建立了单元脉冲编码(EPC) MIMO BiSAR模型;然后利用空间滤波技术分离不同距离区域的信号。然后，基于先验配置信息进行多普勒预处理，消除多普勒质心模糊。最后，采用经典成像方法，获得了宽幅成像结果。数值仿真验证了该方法的有效性。
{"title":"A Wide-Swath Imaging Method for the MIMO Bistatic SAR System","authors":"Hai Huang, Shengqi Zhu, Xiongpeng He, Ximin Li, Jingwei Xu, Kun Liu","doi":"10.1109/ICICSP55539.2022.10050686","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050686","url":null,"abstract":"Existing imaging methods about Bistatic SAR(BiSAR) mostly consider small scene with single channel and ignore the negative effects of range ambiguity. In order to address this problem, a wide-swath imaging method based on multiple-input multiple-output(MIMO) BiSAR system is proposed in this paper. Firstly, the element pulse coding(EPC) MIMO BiSAR model is established by modulating both of elements and pulses. After that, the spatial filtering technique is utilized to separate signals from different range regions. Then, the Doppler preprocessing that based on the prior configuration information is performed to eliminate the Doppler centroid ambiguity. Finally, classical imaging method is performed, and the wide-swath imaging results can be obtained. Numerical simulations verify the proposed method.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"1 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":"121733694","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}
In this paper, we present a novel method, named Particles Filter Assisted Projection (PFAP), to design unimodular waveform with local low range sidelobes. As the designing problem with unimodular constraint is often deemed as non-convex, and hard to tackle, here we borrow the multi-particles resampling idea to improve the robustness. By formulating the typical low range sidelobes mathematical problems, these nonlinear approximations can be solved via PFAP and FFT, where PFAP with resampling idea and particles assisted projection mechanism could enhance the global convergence under the non-convex constraint even with less iterations. Simulations demonstrates that PFAP outperforms some other prevalent ones.
{"title":"Robust Phase-Coded Waveform Design with Low Range Sidelobes Using Particles Filter Assisted Projection Method","authors":"Xiang Feng, T. Liu, Wenqing Cui, Chaolin Zhang, Zhanfeng Zhao, Yinan Zhao","doi":"10.1109/ICICSP55539.2022.10050542","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050542","url":null,"abstract":"In this paper, we present a novel method, named Particles Filter Assisted Projection (PFAP), to design unimodular waveform with local low range sidelobes. As the designing problem with unimodular constraint is often deemed as non-convex, and hard to tackle, here we borrow the multi-particles resampling idea to improve the robustness. By formulating the typical low range sidelobes mathematical problems, these nonlinear approximations can be solved via PFAP and FFT, where PFAP with resampling idea and particles assisted projection mechanism could enhance the global convergence under the non-convex constraint even with less iterations. Simulations demonstrates that PFAP outperforms some other prevalent ones.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"1 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":"129318812","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/ICICSP55539.2022.10050570
Xiaoyu Tang, Xiaoning Huang, Xi Lin
In the process of concept learning, students will gradually construct concepts and eventually form a profound and complete concept system. Analyzing what students discuss in class can help teachers effectively understand students' level of conceptual learning and contribute to the development of teaching evaluation level. In this paper, we analyze students' conceptual learning levels by introducing the BERT combination model in deep learning. The research steps mainly include the introduction and formulation of concept learning classification metrics, the collection and preprocessing of datasets, and the construction of combinatorial optimization based on BERT models.Finally, the BERT-RCNN model achieved the best results, with an precision of 83.33%, a recall of 83.34%, and an F1-score of 83.34%.
{"title":"Discussion on the Effect of Classroom Concept Learning Based on BERT Text Classification","authors":"Xiaoyu Tang, Xiaoning Huang, Xi Lin","doi":"10.1109/ICICSP55539.2022.10050570","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050570","url":null,"abstract":"In the process of concept learning, students will gradually construct concepts and eventually form a profound and complete concept system. Analyzing what students discuss in class can help teachers effectively understand students' level of conceptual learning and contribute to the development of teaching evaluation level. In this paper, we analyze students' conceptual learning levels by introducing the BERT combination model in deep learning. The research steps mainly include the introduction and formulation of concept learning classification metrics, the collection and preprocessing of datasets, and the construction of combinatorial optimization based on BERT models.Finally, the BERT-RCNN model achieved the best results, with an precision of 83.33%, a recall of 83.34%, and an F1-score of 83.34%.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"1 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":"129886574","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/ICICSP55539.2022.10050580
Minghao Yan, Qinxin Lu
The dependence of deep learning models on large-scale labeled training data limits their application in real-world scenarios. To address this problem, researchers have proposed few-shot learning. However, most existing few-shot learning methods tend to ignore the contribution of local detailed information with class characteristics to classification. In this paper, we propose the dynamic reinforcement and alignment graph convolution networks (DRAGCN). Our proposed model can learn to generate the reinforcement basis that contains valuable information of local details with class characters based on experiential knowledge and obtain the reinforced feature maps by solving the neural ordinary differential equations (Neural ODE). These reinforced feature maps of the input images are constructed as graph-structured data, and the node features and edge features of the graph are optimized with the semantic alignment graph convolution networks, which introduces the semantic alignment operation to prevent the over-smoothing phenomenon. Experimental results on two popular datasets show that the proposed DRAGCN outperforms existing methods on few-shot learning tasks.
{"title":"Dynamic Reinforcement and Alignment Graph Convolution Networks for Few-Shot Learning","authors":"Minghao Yan, Qinxin Lu","doi":"10.1109/ICICSP55539.2022.10050580","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050580","url":null,"abstract":"The dependence of deep learning models on large-scale labeled training data limits their application in real-world scenarios. To address this problem, researchers have proposed few-shot learning. However, most existing few-shot learning methods tend to ignore the contribution of local detailed information with class characteristics to classification. In this paper, we propose the dynamic reinforcement and alignment graph convolution networks (DRAGCN). Our proposed model can learn to generate the reinforcement basis that contains valuable information of local details with class characters based on experiential knowledge and obtain the reinforced feature maps by solving the neural ordinary differential equations (Neural ODE). These reinforced feature maps of the input images are constructed as graph-structured data, and the node features and edge features of the graph are optimized with the semantic alignment graph convolution networks, which introduces the semantic alignment operation to prevent the over-smoothing phenomenon. Experimental results on two popular datasets show that the proposed DRAGCN outperforms existing methods on few-shot learning tasks.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"1 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":"123785458","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}
In this paper, we propose a novel method named Alternating Frequency-based Sequential Projection Fusion (AFSPF) to design waveform with low range sidelobes, Doppler tolerance and low probability of intercept under non-convex constraint. Firstly, the novel waveform model has been formulated by Sine-chaotic mapping parts and LFM ones. Then, the engineering mathematical problem corresponding to multiple non-cooperative targets or interference is formulated in the alternating way. Furthermore, using the multi-variable decomposition idea, the original problem is divided into triple-variable ones, which could be solved via AFSPF. Here, AFSPF assisted by sequential fusion and FFT operation, would enhance the global optimization convergence under unimodular constraint. Finally, simulations and numerical results show comparisons with several popular methods.
{"title":"Design Waveform with Low Range Sidelobes, Doppler Tolerance and Low Probability of Intercept Based on Alternating Sequential Projection Fusion","authors":"Yu Fan, Xiang Feng, Yinan Zhao, Zhanfeng Zhao, Feng-cong Li, Wenqing Cui","doi":"10.1109/ICICSP55539.2022.10050626","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050626","url":null,"abstract":"In this paper, we propose a novel method named Alternating Frequency-based Sequential Projection Fusion (AFSPF) to design waveform with low range sidelobes, Doppler tolerance and low probability of intercept under non-convex constraint. Firstly, the novel waveform model has been formulated by Sine-chaotic mapping parts and LFM ones. Then, the engineering mathematical problem corresponding to multiple non-cooperative targets or interference is formulated in the alternating way. Furthermore, using the multi-variable decomposition idea, the original problem is divided into triple-variable ones, which could be solved via AFSPF. Here, AFSPF assisted by sequential fusion and FFT operation, would enhance the global optimization convergence under unimodular constraint. Finally, simulations and numerical results show comparisons with several popular methods.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"71 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":"126629600","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/ICICSP55539.2022.10050711
Yujie Zhang, Hui Ma
Forward-looking imaging systems are mainly divided into phased-array (PA) radar and multiple-input-multiple-output (MIMO) radar according to whether the transmitted signals are coherent or not. Since PA radar can improve the signal-to-noise ratio (SNR) through beamforming, while MIMO radar can achieve higher spatial resolution through channel separation at the receiver. In this paper, the noise-robustness and super-resolution performance of the two systems are analyzed. A fair comparison is conducted under the equal conditions, including algorithm, hardware, etc. We use a half-wavelength uniform array to transmit linear frequency modulation (LFM) signals for PA radar and orthogonal signals for MIMO radar. We first establishes signal models of PA system and MIMO system respectively, where the sparse Bayesian learning algorithm is used for the scene imaging. The simulation results show that the imaging quality of phased array radar is better than that of MIMO radar under low SNR, but worse than MIMO radar under high SNR, which shows that the PA radar is more suitable for imaging under low SNR, while MIMO radar is better under high SNR.
{"title":"Comparison of the Performance of Forward-Looking Imaging Systems: Phased-Array or MIMO Radar","authors":"Yujie Zhang, Hui Ma","doi":"10.1109/ICICSP55539.2022.10050711","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050711","url":null,"abstract":"Forward-looking imaging systems are mainly divided into phased-array (PA) radar and multiple-input-multiple-output (MIMO) radar according to whether the transmitted signals are coherent or not. Since PA radar can improve the signal-to-noise ratio (SNR) through beamforming, while MIMO radar can achieve higher spatial resolution through channel separation at the receiver. In this paper, the noise-robustness and super-resolution performance of the two systems are analyzed. A fair comparison is conducted under the equal conditions, including algorithm, hardware, etc. We use a half-wavelength uniform array to transmit linear frequency modulation (LFM) signals for PA radar and orthogonal signals for MIMO radar. We first establishes signal models of PA system and MIMO system respectively, where the sparse Bayesian learning algorithm is used for the scene imaging. The simulation results show that the imaging quality of phased array radar is better than that of MIMO radar under low SNR, but worse than MIMO radar under high SNR, which shows that the PA radar is more suitable for imaging under low SNR, while MIMO radar is better under high SNR.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"12 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":"126081316","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/ICICSP55539.2022.10050604
Huai-ting Xu, Xiao-ying Lei
In Vehicular Ad-hoc Networks (VANETs), nodes are equipped to collaboratively broadcast emergency messages in case of any transportation emergence events, which can improve the road safety. However, heavily repeated rebroadcasting of messages leads to severe redundancy and collisions, bringing in inefficient channel utilization and low reliability. In order to improve this issue, we propose a probabilistic rebroadcast method to reduce the traffic load caused by repeated rebroadcasting of a same message. Instead of transmitting an emergency message once receives one, a node broadcasts under a certain probability, which is determined according to the node density, traveling velocity, and the distance of the node itself to the source node. Moreover, a waiting process is applied to eliminate the collisions caused by simultaneous broadcasting from multiple nodes. Through extensive simulations, we demonstrate that proposed mechanism can effectively reduce traffic loads and alleviate transmission collisions.
{"title":"A Light Traffic Load and Highly Reliable Emergency Message Broadcasting Mechanism for VANETs","authors":"Huai-ting Xu, Xiao-ying Lei","doi":"10.1109/ICICSP55539.2022.10050604","DOIUrl":"https://doi.org/10.1109/ICICSP55539.2022.10050604","url":null,"abstract":"In Vehicular Ad-hoc Networks (VANETs), nodes are equipped to collaboratively broadcast emergency messages in case of any transportation emergence events, which can improve the road safety. However, heavily repeated rebroadcasting of messages leads to severe redundancy and collisions, bringing in inefficient channel utilization and low reliability. In order to improve this issue, we propose a probabilistic rebroadcast method to reduce the traffic load caused by repeated rebroadcasting of a same message. Instead of transmitting an emergency message once receives one, a node broadcasts under a certain probability, which is determined according to the node density, traveling velocity, and the distance of the node itself to the source node. Moreover, a waiting process is applied to eliminate the collisions caused by simultaneous broadcasting from multiple nodes. Through extensive simulations, we demonstrate that proposed mechanism can effectively reduce traffic loads and alleviate transmission collisions.","PeriodicalId":281095,"journal":{"name":"2022 5th International Conference on Information Communication and Signal Processing (ICICSP)","volume":"21 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":"133333836","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：