Pub Date : 2022-11-01DOI: 10.1109/WCSP55476.2022.10039414
Xiaohe Wang, Xinli Shi
The past decade has seen a rapid development of solving travelling salesman problem (TSP) and vehicle routing problem (VRP) with deep reinforcement learning. In order to solve problems that are closer to life, more researchers turn their attention to the variant VRP. In this article, we tackle the capacitated VRP with soft time window (CVRPSTW). In this problem, the vehicles have capacity limit and will be punished if arriving at the customer outside the time window. We use a deep reinforcement learning (DRL) based on the attention mechanism and point network to solve CVRPSTW. In the training part, we use policy gradient with rollout baseline. The experiment shows that the proposed DRL model can effectively solve this variant VRP.
{"title":"Deep Reinforcement Learning for the Capacitated Vehicle Routing Problem with Soft Time Window","authors":"Xiaohe Wang, Xinli Shi","doi":"10.1109/WCSP55476.2022.10039414","DOIUrl":"https://doi.org/10.1109/WCSP55476.2022.10039414","url":null,"abstract":"The past decade has seen a rapid development of solving travelling salesman problem (TSP) and vehicle routing problem (VRP) with deep reinforcement learning. In order to solve problems that are closer to life, more researchers turn their attention to the variant VRP. In this article, we tackle the capacitated VRP with soft time window (CVRPSTW). In this problem, the vehicles have capacity limit and will be punished if arriving at the customer outside the time window. We use a deep reinforcement learning (DRL) based on the attention mechanism and point network to solve CVRPSTW. In the training part, we use policy gradient with rollout baseline. The experiment shows that the proposed DRL model can effectively solve this variant VRP.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"16 1","pages":"352-355"},"PeriodicalIF":0.0,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86161382","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 : 2021-01-01DOI: 10.1109/WCSP52459.2021.9613669
Yingwen Liu, Jing Xu
{"title":"Modulation Recognition Method of MAPSK Signal","authors":"Yingwen Liu, Jing Xu","doi":"10.1109/WCSP52459.2021.9613669","DOIUrl":"https://doi.org/10.1109/WCSP52459.2021.9613669","url":null,"abstract":"","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"26 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74797930","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 : 2021-01-01DOI: 10.1109/WCSP52459.2021.9613299
Fang-Mei Zhou, Zhonglou Lu, Zhifeng Zhu, T. Cheng
{"title":"Artificial Intelligence Routing Method in Wireless Sensor Network for Sewage Treatment Monitoring","authors":"Fang-Mei Zhou, Zhonglou Lu, Zhifeng Zhu, T. Cheng","doi":"10.1109/WCSP52459.2021.9613299","DOIUrl":"https://doi.org/10.1109/WCSP52459.2021.9613299","url":null,"abstract":"","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"8 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75034025","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 : 2021-01-01DOI: 10.1109/WCSP52459.2021.9613464
T. Cheng, Fang Zhou
{"title":"Integrated Interference Solutions Between 5G and Satellite Systems","authors":"T. Cheng, Fang Zhou","doi":"10.1109/WCSP52459.2021.9613464","DOIUrl":"https://doi.org/10.1109/WCSP52459.2021.9613464","url":null,"abstract":"","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"81 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73674085","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 : 2021-01-01DOI: 10.1109/WCSP52459.2021.9613356
Q. Liao, Xiaoqian Wang, Gaoqian He
{"title":"Electromagnetically Induced Transparency in a Coupled NV Spin-Mechanical Resonator System","authors":"Q. Liao, Xiaoqian Wang, Gaoqian He","doi":"10.1109/WCSP52459.2021.9613356","DOIUrl":"https://doi.org/10.1109/WCSP52459.2021.9613356","url":null,"abstract":"","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"75 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83809180","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 : 2020-10-21DOI: 10.1109/WCSP49889.2020.9299730
Yue Yu, Ming-Quan Zeng, Zhijie Qiu, Lei Luo, Hong Chen
Artificial intelligence is a bellwether of today’s new technological revolution. As a branch of artificial intelligence, machine learning faces two main problems in practical application: 1) data owned by most enterprises are difficult to aggregate; and, 2) big data owners pay more and more attention to data privacy and security, which leads to the problem of data island. Federated learning (FL), as a distributed FL paradigm, which can enable all parties to achieve the purpose of co-building models while ensuring data privacy and exposure, provides a possible solution to the mentioned problems of machine learning. The FL takes full advantage of participants’ data and computing power and builds a more robust machine learning model without sharing the data. In an environment with strict data regulation, the FL can effectively solve the key problems, such as those related to data privacy and data rights. However, most of the existing FL-based frameworks do not pay attention to the impact of data source distribution on FL training. Therefore, this paper proposed a data-oriented FL framework called the Federated AI Engine(FAE), which can solve FL problems without leaving the data in control. The proposed framework provides a method that can be used to verify FL quickly for researchers who intend to try federal learning.
{"title":"A Data Protection-Oriented Design Procedure for a Federated Learning Framework","authors":"Yue Yu, Ming-Quan Zeng, Zhijie Qiu, Lei Luo, Hong Chen","doi":"10.1109/WCSP49889.2020.9299730","DOIUrl":"https://doi.org/10.1109/WCSP49889.2020.9299730","url":null,"abstract":"Artificial intelligence is a bellwether of today’s new technological revolution. As a branch of artificial intelligence, machine learning faces two main problems in practical application: 1) data owned by most enterprises are difficult to aggregate; and, 2) big data owners pay more and more attention to data privacy and security, which leads to the problem of data island. Federated learning (FL), as a distributed FL paradigm, which can enable all parties to achieve the purpose of co-building models while ensuring data privacy and exposure, provides a possible solution to the mentioned problems of machine learning. The FL takes full advantage of participants’ data and computing power and builds a more robust machine learning model without sharing the data. In an environment with strict data regulation, the FL can effectively solve the key problems, such as those related to data privacy and data rights. However, most of the existing FL-based frameworks do not pay attention to the impact of data source distribution on FL training. Therefore, this paper proposed a data-oriented FL framework called the Federated AI Engine(FAE), which can solve FL problems without leaving the data in control. The proposed framework provides a method that can be used to verify FL quickly for researchers who intend to try federal learning.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"43 1","pages":"968-974"},"PeriodicalIF":0.0,"publicationDate":"2020-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80109885","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 : 2019-01-01DOI: 10.1109/WCSP.2019.8928039
Mei Gao, Zhongwei Liu, Feng Jing, Haodan Ran, Shuyin Zhang
{"title":"Low Complexity Iterative Combining-Equalization Algorithm Based on SIC","authors":"Mei Gao, Zhongwei Liu, Feng Jing, Haodan Ran, Shuyin Zhang","doi":"10.1109/WCSP.2019.8928039","DOIUrl":"https://doi.org/10.1109/WCSP.2019.8928039","url":null,"abstract":"","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"54 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76885996","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 : 2018-03-22DOI: 10.1109/WISPNET.2018.8538578
R. Bala, R. Manoharan
The radical growth of Bitcoin revolutionized the field of digital currencies by offering a secure replacement for online electronic payments like card payments and Internet banking. Notably, Bitcoin has become popular since it maintains the anonymity of the users and enables peer-to-peer instant payments across the world. It is a decentralized money transfer protocol that does transactions without exposing user credentials and does verifications without any third-party intervention. Though it maintains anonymity, decentralization concept introduced vulnerabilities leading to severe security issues like double spending, block withholding and 51% attacks. These issues necessitate security specific enhancements in Bitcoin protocol. Therefore, this paper proposes a method of incorporating criteria check for miners to participate in mining process and a verification process to join the mining pool. The proposed idea mitigates double spending, block withholding, and 51% attacks. Further, a new approach is proposed namely, refining block creation and verification strategy for improving transaction rate without compromising security.
{"title":"Security Enhancement In Bitcoin Protocol","authors":"R. Bala, R. Manoharan","doi":"10.1109/WISPNET.2018.8538578","DOIUrl":"https://doi.org/10.1109/WISPNET.2018.8538578","url":null,"abstract":"The radical growth of Bitcoin revolutionized the field of digital currencies by offering a secure replacement for online electronic payments like card payments and Internet banking. Notably, Bitcoin has become popular since it maintains the anonymity of the users and enables peer-to-peer instant payments across the world. It is a decentralized money transfer protocol that does transactions without exposing user credentials and does verifications without any third-party intervention. Though it maintains anonymity, decentralization concept introduced vulnerabilities leading to severe security issues like double spending, block withholding and 51% attacks. These issues necessitate security specific enhancements in Bitcoin protocol. Therefore, this paper proposes a method of incorporating criteria check for miners to participate in mining process and a verification process to join the mining pool. The proposed idea mitigates double spending, block withholding, and 51% attacks. Further, a new approach is proposed namely, refining block creation and verification strategy for improving transaction rate without compromising security.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"8 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75251208","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 : 2018-03-22DOI: 10.1109/WISPNET.2018.8538693
H. M. T. Al-Hilfi, Shatha k. Jasim Al hummadi, M. Mustafa
With the growing and widespread variety of wireless networking technologies such as “Worldwide Interoperability for Microwave Access” (WiMAX) the number of users of internet devices continues to grow. For WiMAX, network stability is highly dependent on the “Quality of Service” (QoS) and connection with the internet requires adequate bandwidth, especially for voice and video services. The quality of service for voice and video services is a problem in internet communication as a whole. One way to maintain the stability of the service quality is to use a modulation technique, where the modulation technique enables adjustment of a signal modulation pattern which depends on the signal to noise ratio (SNR) condition. In this article, we study and compare the types of modulation QPSK, 16QAM, and 64QAM for WiMAX Network in Baghdad. The obtained test results are compared in terms of the delay, throughput, Block error rate (BLER) and signal to noise ratio (SNR) for different modulation techniques.
{"title":"Effect of Modulation Techniques on the Performance of Voice and Video Service for WiMAX Networks in Baghdad","authors":"H. M. T. Al-Hilfi, Shatha k. Jasim Al hummadi, M. Mustafa","doi":"10.1109/WISPNET.2018.8538693","DOIUrl":"https://doi.org/10.1109/WISPNET.2018.8538693","url":null,"abstract":"With the growing and widespread variety of wireless networking technologies such as “Worldwide Interoperability for Microwave Access” (WiMAX) the number of users of internet devices continues to grow. For WiMAX, network stability is highly dependent on the “Quality of Service” (QoS) and connection with the internet requires adequate bandwidth, especially for voice and video services. The quality of service for voice and video services is a problem in internet communication as a whole. One way to maintain the stability of the service quality is to use a modulation technique, where the modulation technique enables adjustment of a signal modulation pattern which depends on the signal to noise ratio (SNR) condition. In this article, we study and compare the types of modulation QPSK, 16QAM, and 64QAM for WiMAX Network in Baghdad. The obtained test results are compared in terms of the delay, throughput, Block error rate (BLER) and signal to noise ratio (SNR) for different modulation techniques.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"79 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75336898","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 : 2018-03-22DOI: 10.1109/WISPNET.2018.8538528
V. Balaji
Spectrum Sensing is a key module in Cognitive Radios (CR) for detecting spectrum holes. The performance of spectrum sensing algorithms is compromised due to channel impairments, such as, multi-path fading and shadowing. Cooperative Spectrum Sensing (CSS) scheme mitigates the above issues and improves the spatial diversity gain of Secondary Users (SUs). In this paper, we present Reinforcement Learning (RL) based CSS scheme with the objective of improving cooperative sensing accuracy by maximizing expected cumulative reward. Using reinforcement learning, the Fusion Center(FC) makes a global decision by interacting with the radio environment which consists of cooperative SUs and primary transmitter. The cooperative SUs are deployed randomly in a fading wireless channel environment modeled as a Markov Decision Process (MDP). The optimal solution of RL based CSS algorithm is formulated using policy iteration to meet the requirements of IEEE 802.22 Wireless Regional Area Network (WRAN) standard. The simulation results show that the RL based CSS scheme improves the detection performance under channel fading/shadowing and overall cooperative learning capability.
{"title":"Reinforcement Learning Based Decision Fusion Scheme for Cooperative Spectrum Sensing in Cognitive Radios","authors":"V. Balaji","doi":"10.1109/WISPNET.2018.8538528","DOIUrl":"https://doi.org/10.1109/WISPNET.2018.8538528","url":null,"abstract":"Spectrum Sensing is a key module in Cognitive Radios (CR) for detecting spectrum holes. The performance of spectrum sensing algorithms is compromised due to channel impairments, such as, multi-path fading and shadowing. Cooperative Spectrum Sensing (CSS) scheme mitigates the above issues and improves the spatial diversity gain of Secondary Users (SUs). In this paper, we present Reinforcement Learning (RL) based CSS scheme with the objective of improving cooperative sensing accuracy by maximizing expected cumulative reward. Using reinforcement learning, the Fusion Center(FC) makes a global decision by interacting with the radio environment which consists of cooperative SUs and primary transmitter. The cooperative SUs are deployed randomly in a fading wireless channel environment modeled as a Markov Decision Process (MDP). The optimal solution of RL based CSS algorithm is formulated using policy iteration to meet the requirements of IEEE 802.22 Wireless Regional Area Network (WRAN) standard. The simulation results show that the RL based CSS scheme improves the detection performance under channel fading/shadowing and overall cooperative learning capability.","PeriodicalId":6858,"journal":{"name":"2018 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"20 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78472924","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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