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}
As an emerging framework of distributed learning, federated learning (FL) has been a research focus since it enables clients to train deep learning models collaboratively without exposing their original data. Nevertheless, private information can still be inferred from the communicated model parameters by adversaries. In addition, due to the limited channel bandwidth, the model communication between clients and the server has become a serious bottleneck. In this paper, we consider an FL framework that utilizes local differential privacy, where the client adds artificial Gaussian noise to the local model update before aggregation. To reduce the communication overhead of the differential privacy-protected model, we propose the universal vector quantization for FL with local differential privacy mechanism, which quantizes the model parameters in a universal vector quantization approach. Furthermore, we analyze the privacy performance of the proposed approach and track the privacy loss by accounting the log moments. Experiments show that even if the quantization bit is relatively small, our method can achieve model compression without reducing the accuracy of the global model.
{"title":"Communication Reducing Quantization for Federated Learning with Local Differential Privacy Mechanism","authors":"Huixuan Zong, Qing Wang, Xiaofeng Liu, Yinchuan Li, Yunfeng Shao","doi":"10.1109/iccc52777.2021.9580315","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580315","url":null,"abstract":"As an emerging framework of distributed learning, federated learning (FL) has been a research focus since it enables clients to train deep learning models collaboratively without exposing their original data. Nevertheless, private information can still be inferred from the communicated model parameters by adversaries. In addition, due to the limited channel bandwidth, the model communication between clients and the server has become a serious bottleneck. In this paper, we consider an FL framework that utilizes local differential privacy, where the client adds artificial Gaussian noise to the local model update before aggregation. To reduce the communication overhead of the differential privacy-protected model, we propose the universal vector quantization for FL with local differential privacy mechanism, which quantizes the model parameters in a universal vector quantization approach. Furthermore, we analyze the privacy performance of the proposed approach and track the privacy loss by accounting the log moments. Experiments show that even if the quantization bit is relatively small, our method can achieve model compression without reducing the accuracy of the global model.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"13 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":"132544391","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/iccc52777.2021.9580249
Yibo Li, Junhui Zhao, Hongxue Diao, Lihua Yang
Location based service (LBS) plays an important role in smart city system. However, there is serious non-line of sight (NLOS) phenomenon in high-density urban areas, which affects the localization accuracy significantly. Based on signal detection theory, we propose a two-step localization method to identify NLOS signals and estimate position after mitigating the influence of NLOS. Firstly, depending on the prior probabilities, the NLOS signals are identified by generalized likelihood ratio (GLR) test or Neyman-Pearson (NP) criterion. Moreover, the NLOS signals are mitigated based on identified measurement condition. Finally, selecting residual weighting algorithm (S-RWGH) is used to estimate the target position. Simulation results show that the proposed algorithm can effectively improve the localization accuracy. Average location error is below 15 m when the NLOS rate is below 62.5 % in the urban environment.
{"title":"Signal Detection Theory-Based Localization Method in Urban NLOS Environment","authors":"Yibo Li, Junhui Zhao, Hongxue Diao, Lihua Yang","doi":"10.1109/iccc52777.2021.9580249","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580249","url":null,"abstract":"Location based service (LBS) plays an important role in smart city system. However, there is serious non-line of sight (NLOS) phenomenon in high-density urban areas, which affects the localization accuracy significantly. Based on signal detection theory, we propose a two-step localization method to identify NLOS signals and estimate position after mitigating the influence of NLOS. Firstly, depending on the prior probabilities, the NLOS signals are identified by generalized likelihood ratio (GLR) test or Neyman-Pearson (NP) criterion. Moreover, the NLOS signals are mitigated based on identified measurement condition. Finally, selecting residual weighting algorithm (S-RWGH) is used to estimate the target position. Simulation results show that the proposed algorithm can effectively improve the localization accuracy. Average location error is below 15 m when the NLOS rate is below 62.5 % in the urban environment.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"17 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":"133825438","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/iccc52777.2021.9580265
Ni Yang, Yinghong Ma, Long Suo, Yijun Lu, Suping Ren, Liwan Lin
Virtualization is the key technology of cloud computing, by which the physical resources in data center can be abstracted as a virtual resource pool for flexible resource allocation. To make full use of the data center resources, efficient virtual network embedding (VNE) is both an efficient and challenging solution. Traditional VNE algorithms focused on the generic topology in the Internet, while the data center network topology is regular and symmetric. In this paper, the most widely used fat-tree topology is considered, and a proximal adaptive VNE algorithm based on multi-dimensional load balancing is proposed. In this VNE algorithm, the bandwidth resource cost is reduced by proximal mapping, and the joint balancing of computation and communication loads is taken into account to achieve multi-dimension resource allocation balance. Simulation results show that the proposed algorithm can increase the resource utilization, and keep both the load balance of each single-dimension resource and the joint balance of different dimensions of resources.
{"title":"Proximal Virtual Network Embedding based on Multi-dimensional Load Balancing in Data Centers","authors":"Ni Yang, Yinghong Ma, Long Suo, Yijun Lu, Suping Ren, Liwan Lin","doi":"10.1109/iccc52777.2021.9580265","DOIUrl":"https://doi.org/10.1109/iccc52777.2021.9580265","url":null,"abstract":"Virtualization is the key technology of cloud computing, by which the physical resources in data center can be abstracted as a virtual resource pool for flexible resource allocation. To make full use of the data center resources, efficient virtual network embedding (VNE) is both an efficient and challenging solution. Traditional VNE algorithms focused on the generic topology in the Internet, while the data center network topology is regular and symmetric. In this paper, the most widely used fat-tree topology is considered, and a proximal adaptive VNE algorithm based on multi-dimensional load balancing is proposed. In this VNE algorithm, the bandwidth resource cost is reduced by proximal mapping, and the joint balancing of computation and communication loads is taken into account to achieve multi-dimension resource allocation balance. Simulation results show that the proposed algorithm can increase the resource utilization, and keep both the load balance of each single-dimension resource and the joint balance of different dimensions of resources.","PeriodicalId":425118,"journal":{"name":"2021 IEEE/CIC International Conference on Communications in China (ICCC)","volume":"131 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":"133020278","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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