Pub Date : 2021-07-28DOI: 10.1109/iccc52777.2021.9580289
Qisi Zeng, Zhengchuan Chen, Yunjian Jia, Min Wang
Resource allocation for server would significantly affect the timeless of interested status updates in various queuing systems. In this work, we study a non-preemptive M/M/1/1 queueing system with two sources in which updates are forwarded independently to an interested monitor by sharing a communication channel. In order to improve the timeliness of this system under limited service resource, an important policy, dynamic resource sharing policy is proposed which allocates the channel resource for transmission of the arrived update based on the state of the queue. By modeling the queue as a stochastic hybrid system, the closed form of average AoI of the proposed scheme is achieved. Numerical results show that a non-preemptive system with dynamic resources sharing policy can significantly improve the AoI performance compared with benchmark scheme.
{"title":"Dynamic Resource Sharing for Non-preemptive M/M/1/1 Queueing System : An Age of Information Perspective","authors":"Qisi Zeng, Zhengchuan Chen, Yunjian Jia, Min Wang","doi":"10.1109/iccc52777.2021.9580289","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580289","url":null,"abstract":"Resource allocation for server would significantly affect the timeless of interested status updates in various queuing systems. In this work, we study a non-preemptive M/M/1/1 queueing system with two sources in which updates are forwarded independently to an interested monitor by sharing a communication channel. In order to improve the timeliness of this system under limited service resource, an important policy, dynamic resource sharing policy is proposed which allocates the channel resource for transmission of the arrived update based on the state of the queue. By modeling the queue as a stochastic hybrid system, the closed form of average AoI of the proposed scheme is achieved. Numerical results show that a non-preemptive system with dynamic resources sharing policy can significantly improve the AoI performance compared with benchmark scheme.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129212044","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580393
Jiling Yan, Jianyu Xiao, Xuemin Hong
Virtual machine placement (VMP) in large-scale cloud computing clusters is a challenging problem with practical importance. Deep Q-learning (DQN) based algorithm is a promising means to solve difficult VMP problems with complex optimization goals and dynamically changing environments. However, native DQN algorithms suffer from shortcomings such as Q value overestimation, difficulty in convergence, and failure to maximize long-term reward. To overcome these shortcomings, this paper proposes an advanced VMP algorithm based on Dueling-DDQN. Moreover, specific optimization techniques are introduced to enhance the exploration strategy and the capability of achieving long-term reward. Experiment results show that the proposed algorithm outperforms native DQN in terms of convergence speed, Q-value estimation accuracy and stability. Meanwhile, the proposed algorithm can achieve multiple optimization goals such as reducing power consumption, ensuring resource load balance and Improving user service Quality.
{"title":"Dueling-DDQN Based Virtual Machine Placement Algorithm for Cloud Computing Systems","authors":"Jiling Yan, Jianyu Xiao, Xuemin Hong","doi":"10.1109/iccc52777.2021.9580393","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580393","url":null,"abstract":"Virtual machine placement (VMP) in large-scale cloud computing clusters is a challenging problem with practical importance. Deep Q-learning (DQN) based algorithm is a promising means to solve difficult VMP problems with complex optimization goals and dynamically changing environments. However, native DQN algorithms suffer from shortcomings such as Q value overestimation, difficulty in convergence, and failure to maximize long-term reward. To overcome these shortcomings, this paper proposes an advanced VMP algorithm based on Dueling-DDQN. Moreover, specific optimization techniques are introduced to enhance the exploration strategy and the capability of achieving long-term reward. Experiment results show that the proposed algorithm outperforms native DQN in terms of convergence speed, Q-value estimation accuracy and stability. Meanwhile, the proposed algorithm can achieve multiple optimization goals such as reducing power consumption, ensuring resource load balance and Improving user service Quality.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"50 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114090098","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580420
Dinghui Zhong, Danhao Deng, Chaowei Wang, Weidong Wang
Non-Orthogonal Multiple Access (NOMA) is considered as a promising technique candidate for the next-generation of cellular networks. An effective user pairing strategy in a cluster can increase the capacity of downlink NOMA system consistently. In this paper, we propose a novel hybrid user pairing to process a case where the number of far users in a cell is larger than the number of near users. Conventional NOMA divides users into multiple groups according to their channel gains, however, there will be a large amount of far users left when the pairing of near users is completed in this scenario. In such case, we allow multiple far users being paired with one near user to optimally utilize the spectrum of far users in the NOMA system, and multiple far users share the same bandwidth. We have compared the proposed algorithm with conventional NOMA, OMA and some algorithms proposed in other papers, simulation results show that the proposed algorithm can significantly increase the system capacity. The superiority of the proposed algorithm is also analyzed from the perspective of user fairness.
{"title":"Maximizing Downlink Non-Orthogonal Multiple Access System Capacity by A Hybrid User Pairing Strategy","authors":"Dinghui Zhong, Danhao Deng, Chaowei Wang, Weidong Wang","doi":"10.1109/iccc52777.2021.9580420","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580420","url":null,"abstract":"Non-Orthogonal Multiple Access (NOMA) is considered as a promising technique candidate for the next-generation of cellular networks. An effective user pairing strategy in a cluster can increase the capacity of downlink NOMA system consistently. In this paper, we propose a novel hybrid user pairing to process a case where the number of far users in a cell is larger than the number of near users. Conventional NOMA divides users into multiple groups according to their channel gains, however, there will be a large amount of far users left when the pairing of near users is completed in this scenario. In such case, we allow multiple far users being paired with one near user to optimally utilize the spectrum of far users in the NOMA system, and multiple far users share the same bandwidth. We have compared the proposed algorithm with conventional NOMA, OMA and some algorithms proposed in other papers, simulation results show that the proposed algorithm can significantly increase the system capacity. The superiority of the proposed algorithm is also analyzed from the perspective of user fairness.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123749018","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580207
Pengcheng Chen, Bin Lyu, Zhen Yang
Wireless powered mobile edge computing (MEC) has been a promising solution to improve the computation performance of the wireless networks. However, wireless devices (WDs) can not harvest sufficient energy and the link used for offloading tasks is hostile due to the doubly attenuation. Fortunately, the efficiency of wireless power transfer and spectrum can be improved significantly by intelligent reflecting surface (IRS), which can steer the incident signal collaboratively. This paper proposes a wireless powered MEC network assisted by the IRS, where the WDs follow a binary offloading rule. Our objective is to maximize the system computation rate by jointly optimizing the downlink and uplink passive beamforming of all IRSs, computing modes of the WDs and time allocation for wireless power transfer (WPT) and task offloading. The block coordinate descent (BCD) method is introduced to decompose the original problem into three sub-problems. The major difficulty is caused by the combinatorial nature of the WDs' computing mode selection. To solve this problem, we propose a duplex coordinate descent with dictionary (DCDD) method to obtain a sub-optimal solution with high efficiency. Numerical results show that the proposed scheme can achieve significant performance gains over the benchmark schemes without IRS.
{"title":"Intelligent Reflecting Surface Enhanced Wireless Powered Mobile Edge Computing","authors":"Pengcheng Chen, Bin Lyu, Zhen Yang","doi":"10.1109/iccc52777.2021.9580207","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580207","url":null,"abstract":"Wireless powered mobile edge computing (MEC) has been a promising solution to improve the computation performance of the wireless networks. However, wireless devices (WDs) can not harvest sufficient energy and the link used for offloading tasks is hostile due to the doubly attenuation. Fortunately, the efficiency of wireless power transfer and spectrum can be improved significantly by intelligent reflecting surface (IRS), which can steer the incident signal collaboratively. This paper proposes a wireless powered MEC network assisted by the IRS, where the WDs follow a binary offloading rule. Our objective is to maximize the system computation rate by jointly optimizing the downlink and uplink passive beamforming of all IRSs, computing modes of the WDs and time allocation for wireless power transfer (WPT) and task offloading. The block coordinate descent (BCD) method is introduced to decompose the original problem into three sub-problems. The major difficulty is caused by the combinatorial nature of the WDs' computing mode selection. To solve this problem, we propose a duplex coordinate descent with dictionary (DCDD) method to obtain a sub-optimal solution with high efficiency. Numerical results show that the proposed scheme can achieve significant performance gains over the benchmark schemes without IRS.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123760961","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 mobile video streaming, 360-degree videos can provide users with immersive and memorable experience. Due to the panoramic and high resolution features, limited bandwidth and stringent latency requirements, the transmission of full high-definition 360-degree video may cause severe stalling, significantly lowering the users' quality of experience (QoE). As the video content seen by the user largely relies on the user's viewing direction and the size of field of view, in this paper, we investigate viewpoint prediction and dynamic tile selection to improve users' QoE for mobile 360-degree video streaming. Specifically, we first design a recurrent neural network integrated with attention mechanism to predict the user's viewpoint in the next video segment. We then propose a dynamic tile-selection method which selects and transmits the tiles that are most likely to be viewed in a segment through online learning. Experimental results based on a real-world dataset show that, the proposed viewpoint prediction neural network and dynamic tile selection method can effectively improve the prediction accuracy and improve the users' QoE.
{"title":"QoE-driven Mobile 360 Video Streaming: Predictive View Generation and Dynamic Tile Selection","authors":"Zhixuan Huang, Peng Yang, Ning Zhang, Feng Lyu, Qihao Li, Wen Wu, X. Shen","doi":"10.1109/iccc52777.2021.9580281","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580281","url":null,"abstract":"In mobile video streaming, 360-degree videos can provide users with immersive and memorable experience. Due to the panoramic and high resolution features, limited bandwidth and stringent latency requirements, the transmission of full high-definition 360-degree video may cause severe stalling, significantly lowering the users' quality of experience (QoE). As the video content seen by the user largely relies on the user's viewing direction and the size of field of view, in this paper, we investigate viewpoint prediction and dynamic tile selection to improve users' QoE for mobile 360-degree video streaming. Specifically, we first design a recurrent neural network integrated with attention mechanism to predict the user's viewpoint in the next video segment. We then propose a dynamic tile-selection method which selects and transmits the tiles that are most likely to be viewed in a segment through online learning. Experimental results based on a real-world dataset show that, the proposed viewpoint prediction neural network and dynamic tile selection method can effectively improve the prediction accuracy and improve the users' QoE.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"37 24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134506337","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580297
Jiadong Yu, Xiaolan Liu, Yue Gao
The space-air-ground integrated network (SAGIN) has drawn increasing attention for its potential to support ubiquitous wireless communications. As one of the link segments, it is non-trivial to track the 3D dynamic channel information in space-air links with multiple unmanned aerial vehicles (UAVs) and Ka-band orbiting low earth orbit (LEO) satellite. In this paper, we proposed a multi-dimensional Markov model (MD-MM) which investigates spatial and temporal probabilistic relationships of multi-user (MU) hidden support vector, single-user (SU) joint hidden support vector, and SU hidden value vector to represent the 3D dynamic channel. Moreover, we developed a novel multidimensional dynamic turbo approximate message passing (MD-DTAMP) algorithm to track the 3D dynamic on-grid channel with multiple UAVs in the system. Numerical results prove that the proposed algorithm shows superior channel tracking performance with smaller pilot overheads.
{"title":"On-Grid 3D Dynamic Channel Tracking for Space-Air Communications with Multiple UAVs","authors":"Jiadong Yu, Xiaolan Liu, Yue Gao","doi":"10.1109/iccc52777.2021.9580297","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580297","url":null,"abstract":"The space-air-ground integrated network (SAGIN) has drawn increasing attention for its potential to support ubiquitous wireless communications. As one of the link segments, it is non-trivial to track the 3D dynamic channel information in space-air links with multiple unmanned aerial vehicles (UAVs) and Ka-band orbiting low earth orbit (LEO) satellite. In this paper, we proposed a multi-dimensional Markov model (MD-MM) which investigates spatial and temporal probabilistic relationships of multi-user (MU) hidden support vector, single-user (SU) joint hidden support vector, and SU hidden value vector to represent the 3D dynamic channel. Moreover, we developed a novel multidimensional dynamic turbo approximate message passing (MD-DTAMP) algorithm to track the 3D dynamic on-grid channel with multiple UAVs in the system. Numerical results prove that the proposed algorithm shows superior channel tracking performance with smaller pilot overheads.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123186644","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580318
Zihan Lin, Pengmin Li, Yilin Xiao, Liang Xiao, Fucai Luo
Federated learning enables mobile edge computing (MEC) to train the object detection model with privacy protection and reduced communication overhead. However, the selection of the mobile devices and the training dataset that determines the energy consumption of the mobile devices and the detection accuracy and latency has to be optimized without relying on the known channel and jamming model against jamming attacks that aim to degrade the model training performance. In this paper, we propose a reinforcement learning (RL) based efficient federated learning training scheme against jamming. This scheme designs a fast RL algorithm with shared parameters to choose the training policy of the object detection model at the mobile devices based on the channel gain, the previous training, transmission and computation performance. The edge server uses a shared Q-table to determine the policy for each mobile device to accelerate the learning process. Simulation results show that this scheme can effectively improve the object detection accuracy, decrease the energy consumption and reduce the latency compared with the benchmark scheme.
{"title":"Learning Based Efficient Federated Learning for Object Detection in MEC Against Jamming","authors":"Zihan Lin, Pengmin Li, Yilin Xiao, Liang Xiao, Fucai Luo","doi":"10.1109/iccc52777.2021.9580318","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580318","url":null,"abstract":"Federated learning enables mobile edge computing (MEC) to train the object detection model with privacy protection and reduced communication overhead. However, the selection of the mobile devices and the training dataset that determines the energy consumption of the mobile devices and the detection accuracy and latency has to be optimized without relying on the known channel and jamming model against jamming attacks that aim to degrade the model training performance. In this paper, we propose a reinforcement learning (RL) based efficient federated learning training scheme against jamming. This scheme designs a fast RL algorithm with shared parameters to choose the training policy of the object detection model at the mobile devices based on the channel gain, the previous training, transmission and computation performance. The edge server uses a shared Q-table to determine the policy for each mobile device to accelerate the learning process. Simulation results show that this scheme can effectively improve the object detection accuracy, decrease the energy consumption and reduce the latency compared with the benchmark scheme.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"184 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122085072","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580435
Fugang Wang, Shushi Gu, Qinyu Zhang, Ning Zhang, W. Xiang
Satellite clustered distributed storage system (SCDSS) is a space-ground integrated network architecture which can provide global wide-coverage and inter-connections among data centers around world. Some soft errors caused by single event upsets (SEUs) in outer space make many failures of on-orbit storage devices, which causes stored data lost. In consequence, effective storage codes, e.g., regenerating codes(RCs) and generalized regenerating codes(GRCs), are crucial to ensure the availability of data with the objective of minimizing transmission cost when repairing the failure nodes. However, heterogeneity is an inevitable problem that result in high cost, due to the diversity of communication links with different transmit powers, link bandwidths and communication distances. Existing coding strategies can not provide an effective solution to deal with the heterogeneity of bandwidth costs among different satellite clusters. In this paper, we propose an asymmetric repair strategy of RCs and GRCs, and derive the upper bound of achievable capacity for data storage in heterogeneous clusters. Then, based on the satellite link analysis, we define cost coefficient, and give the expression of data repair cost, which can be optimized by solving a linear programming problem. Finally, numerical results demonstrate that, compared with the repair cost of typical coding strategies of RCs and GRCs, our asymmetric repair strategy performs better performance in reducing the repair cost, as an effective solution for data availability maintenance in SCDSS.
{"title":"Cost Optimal Regenerating Codes Design for Satellite Clustered Distributed Storage System","authors":"Fugang Wang, Shushi Gu, Qinyu Zhang, Ning Zhang, W. Xiang","doi":"10.1109/iccc52777.2021.9580435","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580435","url":null,"abstract":"Satellite clustered distributed storage system (SCDSS) is a space-ground integrated network architecture which can provide global wide-coverage and inter-connections among data centers around world. Some soft errors caused by single event upsets (SEUs) in outer space make many failures of on-orbit storage devices, which causes stored data lost. In consequence, effective storage codes, e.g., regenerating codes(RCs) and generalized regenerating codes(GRCs), are crucial to ensure the availability of data with the objective of minimizing transmission cost when repairing the failure nodes. However, heterogeneity is an inevitable problem that result in high cost, due to the diversity of communication links with different transmit powers, link bandwidths and communication distances. Existing coding strategies can not provide an effective solution to deal with the heterogeneity of bandwidth costs among different satellite clusters. In this paper, we propose an asymmetric repair strategy of RCs and GRCs, and derive the upper bound of achievable capacity for data storage in heterogeneous clusters. Then, based on the satellite link analysis, we define cost coefficient, and give the expression of data repair cost, which can be optimized by solving a linear programming problem. Finally, numerical results demonstrate that, compared with the repair cost of typical coding strategies of RCs and GRCs, our asymmetric repair strategy performs better performance in reducing the repair cost, as an effective solution for data availability maintenance in SCDSS.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122628846","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}
As a frontier in dynamic spectrum sharing, the citizens broadband radio service (CBRS) system has been proposed by FCC, where three-tiered users are allowed to share the same spectrum. To manage the interference among different layered users, a centralized spectrum access system (SAS) combined with a central database is utilized to coordinate the spectrum access of lower-tiered users. Therefore, the centralized management architecture of the CBRS system cannot efficiently manage very large scale and large quantity of users, and may also suffer severe security and privacy issues. To address these problems, in this paper, we propose a new blockchain-assisted dynamic spectrum management model based on existing CBRS model, where the blockchain technology is leveraged to improve the spectrum management efficiency and quality-of-service of the GAA users. Furthermore, we design a detailed flow of the spectrum management of GAA users, where a dedicated graph coloring algorithm is proposed to obtain the optimal channel assignment strategy. Simulation results have increased the ratio of GAA users licensed and improved spectrum utilization under the proposed algorithm.
{"title":"Blockchain-Assisted Dynamic Spectrum Sharing in the CBRS Band","authors":"Zuguang Li, Wei Wang, Jia Guo, Youwen Zhu, Lu Han, Qi-hui Wu","doi":"10.1109/iccc52777.2021.9580218","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580218","url":null,"abstract":"As a frontier in dynamic spectrum sharing, the citizens broadband radio service (CBRS) system has been proposed by FCC, where three-tiered users are allowed to share the same spectrum. To manage the interference among different layered users, a centralized spectrum access system (SAS) combined with a central database is utilized to coordinate the spectrum access of lower-tiered users. Therefore, the centralized management architecture of the CBRS system cannot efficiently manage very large scale and large quantity of users, and may also suffer severe security and privacy issues. To address these problems, in this paper, we propose a new blockchain-assisted dynamic spectrum management model based on existing CBRS model, where the blockchain technology is leveraged to improve the spectrum management efficiency and quality-of-service of the GAA users. Furthermore, we design a detailed flow of the spectrum management of GAA users, where a dedicated graph coloring algorithm is proposed to obtain the optimal channel assignment strategy. Simulation results have increased the ratio of GAA users licensed and improved spectrum utilization under the proposed algorithm.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125365233","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 : 2021-07-28DOI: 10.1109/iccc52777.2021.9580217
Ying Guo, Cheng Li, Chaoxian Zhang, Yao Yao, Bin Xia
In this paper, we look into the issue of feasibly sharing the spectrum between the radar and communication. Towards this, we investigate the full-duplex (FD) joint radar and communication multi-antenna system, where a node labeled ComRad of dual functionality is simultaneously communicating with a downlink and an uplink users and detecting the targets of interest. The achievable joint rate regions are obtained to evaluate the performance of the converged system. First, viewing the uplink channel and radar return channel as a multiple access channel, we propose an alternative successive interference cancellation scheme, based on which the achievable communication rate is obtained. Second, in case of a unified performance metric, we derive the exact closed-form of the radar estimation rate in terms of the direction, the range and the velocity, which quantifies how much information is obtained about the targets. Numerical results indicate that sharing the radar frequency bands with the communication operation in FD mode achieves larger rate regions compared to traditional schemes.
{"title":"Performance Analysis of the Full-Duplex Joint Radar and Communication System","authors":"Ying Guo, Cheng Li, Chaoxian Zhang, Yao Yao, Bin Xia","doi":"10.1109/iccc52777.2021.9580217","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580217","url":null,"abstract":"In this paper, we look into the issue of feasibly sharing the spectrum between the radar and communication. Towards this, we investigate the full-duplex (FD) joint radar and communication multi-antenna system, where a node labeled ComRad of dual functionality is simultaneously communicating with a downlink and an uplink users and detecting the targets of interest. The achievable joint rate regions are obtained to evaluate the performance of the converged system. First, viewing the uplink channel and radar return channel as a multiple access channel, we propose an alternative successive interference cancellation scheme, based on which the achievable communication rate is obtained. Second, in case of a unified performance metric, we derive the exact closed-form of the radar estimation rate in terms of the direction, the range and the velocity, which quantifies how much information is obtained about the targets. Numerical results indicate that sharing the radar frequency bands with the communication operation in FD mode achieves larger rate regions compared to traditional schemes.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131194120","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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