Coherent fast frequency hopping (CFFH) is attracting growing attention owing to its good antijamming performance and the coherent combining ability. However, compared with the conventional non-coherent fast frequency hopping, CFFH requires a more precise system synchronization. In this paper, we propose a new fine synchronization algorithm for CFFH. This algorithm consists two stages, namely, open-loop stage and closed-loop stage. In the open-loop stage, a grid-based search parameter estimation method is proposed. In the closed-loop stage, we construct a fully coherent phase-locked loop (PLL) and a delay-locked loop (DLL) with decoding feedback structure to perform further fine estimation of the system clock skew and time delay, respectively. Moreover, we analyze the effect of the search parameter settings on the estimation error and derive the root mean squared error (RMSE) of estimates in the steady state of the closed-loop stage. Finally, through simulation, the RMSE performance are compared with the corresponding Cramer-Rao low bound (CRLB) and conventional code loop estimation to show the effectiveness of proposed algorithm.
{"title":"A fine synchronization method for coherent fast frequency hopping","authors":"Xuanhe Yang, Weike Zhang, Shixun Luo, Chang Li, Xiaqing Miao, Aihua Wang","doi":"10.23919/jcc.fa.2022-0599.202310","DOIUrl":"https://doi.org/10.23919/jcc.fa.2022-0599.202310","url":null,"abstract":"Coherent fast frequency hopping (CFFH) is attracting growing attention owing to its good antijamming performance and the coherent combining ability. However, compared with the conventional non-coherent fast frequency hopping, CFFH requires a more precise system synchronization. In this paper, we propose a new fine synchronization algorithm for CFFH. This algorithm consists two stages, namely, open-loop stage and closed-loop stage. In the open-loop stage, a grid-based search parameter estimation method is proposed. In the closed-loop stage, we construct a fully coherent phase-locked loop (PLL) and a delay-locked loop (DLL) with decoding feedback structure to perform further fine estimation of the system clock skew and time delay, respectively. Moreover, we analyze the effect of the search parameter settings on the estimation error and derive the root mean squared error (RMSE) of estimates in the steady state of the closed-loop stage. Finally, through simulation, the RMSE performance are compared with the corresponding Cramer-Rao low bound (CRLB) and conventional code loop estimation to show the effectiveness of proposed algorithm.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136200056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/jcc.ea.2021-0512.202302
Linjie Zhang, Xiaoyan Zhu, Jianfeng Ma
The continuously booming of information technology has shed light on developing a variety of communication networks, multimedia, social networks and Internet of Things applications. However, users inevitably suffer from the intrusion of malicious users. Some studies focus on static characteristics of malicious users, which is easy to be bypassed by camouflaged malicious users. In this paper, we present a malicious user detection method based on ensemble feature selection and adversarial training. Firstly, the feature selection alleviates the dimension disaster problem and achieves more accurate classification performance. Secondly, we embed features into the multidimensional space and aggregate it into a feature map to encode the explicit content preference and implicit interaction preference. Thirdly, we use an effective ensemble learning which could avoid over-fitting and has good noise resistance. Finally, we propose a datadriven neural network detection model with the regularization technique adversarial training to deeply analyze the characteristics. It simplifies the parameters, obtaining more robust interaction features and pattern features. We demonstrate the effectiveness of our approach with numerical simulation results for malicious user detection, where the robustness issues are notable concerns.
{"title":"A study of ensemble feature selection and adversarial training for malicious user detection","authors":"Linjie Zhang, Xiaoyan Zhu, Jianfeng Ma","doi":"10.23919/jcc.ea.2021-0512.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2021-0512.202302","url":null,"abstract":"The continuously booming of information technology has shed light on developing a variety of communication networks, multimedia, social networks and Internet of Things applications. However, users inevitably suffer from the intrusion of malicious users. Some studies focus on static characteristics of malicious users, which is easy to be bypassed by camouflaged malicious users. In this paper, we present a malicious user detection method based on ensemble feature selection and adversarial training. Firstly, the feature selection alleviates the dimension disaster problem and achieves more accurate classification performance. Secondly, we embed features into the multidimensional space and aggregate it into a feature map to encode the explicit content preference and implicit interaction preference. Thirdly, we use an effective ensemble learning which could avoid over-fitting and has good noise resistance. Finally, we propose a datadriven neural network detection model with the regularization technique adversarial training to deeply analyze the characteristics. It simplifies the parameters, obtaining more robust interaction features and pattern features. We demonstrate the effectiveness of our approach with numerical simulation results for malicious user detection, where the robustness issues are notable concerns.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136139699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/jcc.fa.2023-0067.202310
Zhongjie Li, Weijie Yuan, Qinghua Guo, Nan Wu, Ji Zhang
Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.
{"title":"UAMP-based delay-Doppler channel estimation for OTFS systems","authors":"Zhongjie Li, Weijie Yuan, Qinghua Guo, Nan Wu, Ji Zhang","doi":"10.23919/jcc.fa.2023-0067.202310","DOIUrl":"https://doi.org/10.23919/jcc.fa.2023-0067.202310","url":null,"abstract":"Orthogonal time frequency space (OTFS) technique, which modulates data symbols in the delay-Doppler (DD) domain, presents a potential solution for supporting reliable information transmission in high-mobility vehicular networks. In this paper, we study the issues of DD channel estimation for OTFS in the presence of fractional Doppler. We first propose a channel estimation algorithm with both low complexity and high accuracy based on the unitary approximate message passing (UAMP), which exploits the structured sparsity of the effective DD domain channel using hidden Markov model (HMM). The empirical state evolution (SE) analysis is then leveraged to predict the performance of our proposed algorithm. To refine the hyperparameters in the proposed algorithm, we derive the update criterion for the hyperparameters through the expectation-maximization (EM) algorithm. Finally, Our simulation results demonstrate that our proposed algorithm can achieve a significant gain over various baseline schemes.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136200054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/jcc.ea.2022-0096.202302
Chuang Peng, Rangang Zhu, Mengbo Zhang, Lunwen Wang
Spectrum prediction is one of the new techniques in cognitive radio that predicts changes in the spectrum state and plays a crucial role in improving spectrum sensing performance. Prediction models previously trained in the source band tend to perform poorly in the new target band because of changes in the channel. In addition, cognitive radio devices require dynamic spectrum access, which means that the time to retrain the model in the new band is minimal. To increase the amount of data in the target band, we use the GAN to convert the data of source band into target band. First, we analyze the data differences between bands and calculate FID scores to identify the available bands with the slightest difference from the target predicted band. The original GAN structure is unsuitable for converting spectrum data, and we propose the spectrum data conversion GAN (SDC-GAN). The generator module consists of a convolutional network and an LSTM module that can integrate multiple features of the data and can convert data from the source band to the target band. Finally, we use the generated target band data to train the prediction model. The experimental results validate the effectiveness of the proposed algorithm.
{"title":"Cross-band spectrum prediction algorithm based on data conversion using generative adversarial networks","authors":"Chuang Peng, Rangang Zhu, Mengbo Zhang, Lunwen Wang","doi":"10.23919/jcc.ea.2022-0096.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2022-0096.202302","url":null,"abstract":"Spectrum prediction is one of the new techniques in cognitive radio that predicts changes in the spectrum state and plays a crucial role in improving spectrum sensing performance. Prediction models previously trained in the source band tend to perform poorly in the new target band because of changes in the channel. In addition, cognitive radio devices require dynamic spectrum access, which means that the time to retrain the model in the new band is minimal. To increase the amount of data in the target band, we use the GAN to convert the data of source band into target band. First, we analyze the data differences between bands and calculate FID scores to identify the available bands with the slightest difference from the target predicted band. The original GAN structure is unsuitable for converting spectrum data, and we propose the spectrum data conversion GAN (SDC-GAN). The generator module consists of a convolutional network and an LSTM module that can integrate multiple features of the data and can convert data from the source band to the target band. Finally, we use the generated target band data to train the prediction model. The experimental results validate the effectiveness of the proposed algorithm.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136139700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.23919/jcc.ea.2021-0523.202302
Renjie Liang, Haiyang Lyu, Jiancun Fan
In the fifth generation (5G) wireless system, a closed-loop power control (CLPC) scheme based on deep Q learning network (DQN) is introduced to intelligently adjust the transmit power of the base station (BS), which can improve the user equipment (UE) received signal to interference plus noise ratio (SINR) to a target threshold range. However, the selected power control (PC) action in DQN is not accurately matched the fluctuations of the wireless environment. Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network (DNN). As a result, the Q-value of the sub-optimal PC action exceed the optimal one. To solve this problem, we propose the improved DQN scheme. In the proposed scheme, we add an additional DNN to the conventional DQN, and set a shorter training interval to speed up the training of the DNN in order to fully train it. Finally, the proposed scheme can ensure that the Q value of the optimal action remains maximum. After multiple episodes of training, the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment. As a result, the UE received SINR can achieve the target threshold range faster and keep more stable. The simulation results prove that the proposed scheme outperforms the conventional schemes.
{"title":"A deep reinforcement learning-based power control scheme for the 5G wireless systems","authors":"Renjie Liang, Haiyang Lyu, Jiancun Fan","doi":"10.23919/jcc.ea.2021-0523.202302","DOIUrl":"https://doi.org/10.23919/jcc.ea.2021-0523.202302","url":null,"abstract":"In the fifth generation (5G) wireless system, a closed-loop power control (CLPC) scheme based on deep Q learning network (DQN) is introduced to intelligently adjust the transmit power of the base station (BS), which can improve the user equipment (UE) received signal to interference plus noise ratio (SINR) to a target threshold range. However, the selected power control (PC) action in DQN is not accurately matched the fluctuations of the wireless environment. Since the experience replay characteristic of the conventional DQN scheme leads to a possibility of insufficient training in the target deep neural network (DNN). As a result, the Q-value of the sub-optimal PC action exceed the optimal one. To solve this problem, we propose the improved DQN scheme. In the proposed scheme, we add an additional DNN to the conventional DQN, and set a shorter training interval to speed up the training of the DNN in order to fully train it. Finally, the proposed scheme can ensure that the Q value of the optimal action remains maximum. After multiple episodes of training, the proposed scheme can generate more accurate PC actions to match the fluctuations of the wireless environment. As a result, the UE received SINR can achieve the target threshold range faster and keep more stable. The simulation results prove that the proposed scheme outperforms the conventional schemes.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136139705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In ultra-dense networks (UDN), multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations (BSs). The data rate and quality of service can be improved. However, BSs in user-centric paradigm are required to serve more users due to this multiple association scheme. The improvement of system performance may be limited by the improving load of BSs. In this letter, we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN. Based on open loop power control (OLPC), a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio (SINR) for any typical user. As for any BS in different tiers, by leveraging stochastic geometry, we derive the Probability Mass Function (PMF) of the number of the served users, the Cumulative Distribution Function (CDF) of total power consumption, and the CDF bounds of downlink sum data rate. The accuracy of the theoretical analysis is validated by numerical simulations, and the effect the system parameters on the load of BSs is also presented.
{"title":"Load distribution of base stations in user-centric heterogeneous UDN","authors":"Xuanli Wu, Xu Chen, Ziyi Xie, Wei Wu, Tianzhu Pan, Yong Li","doi":"10.23919/JCC.ea.2021-0751.202302","DOIUrl":"https://doi.org/10.23919/JCC.ea.2021-0751.202302","url":null,"abstract":"In ultra-dense networks (UDN), multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations (BSs). The data rate and quality of service can be improved. However, BSs in user-centric paradigm are required to serve more users due to this multiple association scheme. The improvement of system performance may be limited by the improving load of BSs. In this letter, we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN. Based on open loop power control (OLPC), a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio (SINR) for any typical user. As for any BS in different tiers, by leveraging stochastic geometry, we derive the Probability Mass Function (PMF) of the number of the served users, the Cumulative Distribution Function (CDF) of total power consumption, and the CDF bounds of downlink sum data rate. The accuracy of the theoretical analysis is validated by numerical simulations, and the effect the system parameters on the load of BSs is also presented.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"227-234"},"PeriodicalIF":4.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41709121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial intelligence (AI) models are promising to improve the accuracy of wireless positioning systems, particularly in indoor environments where unpredictable radio propagation channel is a great challenge. Although great efforts have been made to explore the effectiveness of different AI models, it is still an open problem whether these models, trained with the data collected from all base stations (BSs), could work when some BSs are unavailable. In this paper, we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work. Particularly, a Siamese Network based Wireless Positioning Model (SNWPM) is proposed to predict the location of mobile user equipment from channel state information (CSI) collected from 5G BSs. Furthermore, a Feature Aware Attention Module (FAAM) is introduced to reinforce the capability of feature extraction from CSI data. Experiments are conducted on the 2022 Wireless Communication AI Competition (WAIC) dataset. The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable. Compared with other AI models, the proposed SNWPM can reduce the positioning error by nearly 50% to more than 60% while using less parameters and lower computation resources.
{"title":"SNWPM: A Siamese network based wireless positioning model resilient to partial base stations unavailable","authors":"Yasong Zhu, Jiabao Wang, Yi Sun, Bing Xu, Peng Liu, Zhisong Pan, Wangdong Qi","doi":"10.23919/jcc.fa.2023-0064.202309","DOIUrl":"https://doi.org/10.23919/jcc.fa.2023-0064.202309","url":null,"abstract":"Artificial intelligence (AI) models are promising to improve the accuracy of wireless positioning systems, particularly in indoor environments where unpredictable radio propagation channel is a great challenge. Although great efforts have been made to explore the effectiveness of different AI models, it is still an open problem whether these models, trained with the data collected from all base stations (BSs), could work when some BSs are unavailable. In this paper, we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work. Particularly, a Siamese Network based Wireless Positioning Model (SNWPM) is proposed to predict the location of mobile user equipment from channel state information (CSI) collected from 5G BSs. Furthermore, a Feature Aware Attention Module (FAAM) is introduced to reinforce the capability of feature extraction from CSI data. Experiments are conducted on the 2022 Wireless Communication AI Competition (WAIC) dataset. The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable. Compared with other AI models, the proposed SNWPM can reduce the positioning error by nearly 50% to more than 60% while using less parameters and lower computation resources.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135299505","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.23919/jcc.fa.2021-0732.202309
Xi Chen, Qihui Wei, Yafeng Zhan, Linling Kuang
Providing alternative PNT service to GNSS-challenged users will be an important function of next-generation NGSO broadband satellite communication systems. Herein, a packet-based PNT service architecture in NGSO broadband systems is proposed in which a primary satellite and selected assistant satellites work together to provide PNT service to requesting users. Its positioning performance bounds are mathematically formulated by rigorously analyzing the bounds constrained by different waveforms. Simulations are conducted on different configurations of Walker Delta MEO constellations and Walker Star LEO constellations for corroboration, revealing the following: (1) Both MEO and LEO constellations achieve sub-meter-level positioning precision given enough satellites. (2) Compared to the GNSS Doppler-based velocity estimation method, the position advance based velocity estimation algorithm is more precise and applicable to the PNT service in NGSO broadband systems. (3) To provide PNT service to users in GNSS-challenged environments, the primary and each assistant satellite need only ∼0.1%o of the time of one downlink beam.
为gnss挑战用户提供替代PNT服务将是下一代NGSO宽带卫星通信系统的一项重要功能。本文提出了一种基于分组的NGSO宽带系统PNT业务架构，该架构由主卫星和选定的辅助卫星共同向请求用户提供PNT服务。通过对不同波形约束边界的严格分析，建立了定位性能边界的数学公式。对Walker Delta MEO星座和Walker Star LEO星座的不同配置进行了仿真验证，结果表明:(1)在卫星数量足够的情况下，MEO和LEO星座的定位精度都达到了亚米级。(2)与基于GNSS多普勒的速度估计方法相比，基于位置推进的速度估计算法精度更高，适用于NGSO宽带系统中的PNT业务。(3)为了向gnss挑战环境中的用户提供PNT服务，主卫星和每个辅助卫星只需要一个下行波束的~ 0.1%的时间。
{"title":"Performance analysis of the packet-based PNT service in NGSO broadband satellite communication systems","authors":"Xi Chen, Qihui Wei, Yafeng Zhan, Linling Kuang","doi":"10.23919/jcc.fa.2021-0732.202309","DOIUrl":"https://doi.org/10.23919/jcc.fa.2021-0732.202309","url":null,"abstract":"Providing alternative PNT service to GNSS-challenged users will be an important function of next-generation NGSO broadband satellite communication systems. Herein, a packet-based PNT service architecture in NGSO broadband systems is proposed in which a primary satellite and selected assistant satellites work together to provide PNT service to requesting users. Its positioning performance bounds are mathematically formulated by rigorously analyzing the bounds constrained by different waveforms. Simulations are conducted on different configurations of Walker Delta MEO constellations and Walker Star LEO constellations for corroboration, revealing the following: (1) Both MEO and LEO constellations achieve sub-meter-level positioning precision given enough satellites. (2) Compared to the GNSS Doppler-based velocity estimation method, the position advance based velocity estimation algorithm is more precise and applicable to the PNT service in NGSO broadband systems. (3) To provide PNT service to users in GNSS-challenged environments, the primary and each assistant satellite need only ∼0.1%o of the time of one downlink beam.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135299506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.23919/JCC.ea.2021-0807.202302
Qi Zhang, Jun Zhang, Shi Jin
Grant-free random access (RA) is attractive for future network due to the minimized access delay. In this paper, we investigate the grantfree RA in multicell massive multiple-input multiple-output (MIMO) systems with pilot reuse. With backoff mechanism, user equipments (UEs) in each cell are randomly activated, and active UEs randomly select orthogonal pilots from a predefined pilot pool, which results in a random pilot contamination among cells. With the help of indicators that capture the uncertainties of UE activation and pilot selection, we derive a closed-form approximation of the spectral efficiency per cell after averaging over the channel fading as well as UEs' random behaviors. Based on the analysis, the optimal backoff parameter and pilot length that maximize the spectral efficiency can be obtained. We find that the backoff mechanism is necessary for the system with large number of UEs, as it can bring significant gains on the spectral efficiency. Moreover, as UE number grows, more backoff time is needed.
{"title":"Grant-free random access in pilot-reused multiceli massive MIMO systems with backoff mechanisms","authors":"Qi Zhang, Jun Zhang, Shi Jin","doi":"10.23919/JCC.ea.2021-0807.202302","DOIUrl":"https://doi.org/10.23919/JCC.ea.2021-0807.202302","url":null,"abstract":"Grant-free random access (RA) is attractive for future network due to the minimized access delay. In this paper, we investigate the grantfree RA in multicell massive multiple-input multiple-output (MIMO) systems with pilot reuse. With backoff mechanism, user equipments (UEs) in each cell are randomly activated, and active UEs randomly select orthogonal pilots from a predefined pilot pool, which results in a random pilot contamination among cells. With the help of indicators that capture the uncertainties of UE activation and pilot selection, we derive a closed-form approximation of the spectral efficiency per cell after averaging over the channel fading as well as UEs' random behaviors. Based on the analysis, the optimal backoff parameter and pilot length that maximize the spectral efficiency can be obtained. We find that the backoff mechanism is necessary for the system with large number of UEs, as it can bring significant gains on the spectral efficiency. Moreover, as UE number grows, more backoff time is needed.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"20 1","pages":"185-195"},"PeriodicalIF":4.1,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41839289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-01DOI: 10.23919/jcc.2023.10251767
Shi Jin, Christos Masouros, Fan Liu, Jie Xu, Jie Yang
Integrated sensing and communication (ISAC) is anticipated to play a pivotal role in realizing the ability to sense, control, and optimize wireless environments, as well as providing ubiquitous connectivity with ultra-high throughput and reliability, and ultra-low latency for future wireless networks. Therefore, it can meet the requirements of mass data transmission, centimeter-level localization, and highly fine-grained environmental sensing for new applications, such as extended reality, holographic communication, autonomous driving, smart healthcare, and intelligent industry. The technology of ISAC deviates from traditional pattern of isolated design for communication and sensing. It can efficiently utilize wireless resources and potentially achieve mutual benefits by combining sensing and communication systems. The ultimate goal of the ISAC system has two aspects. On the one hand, the wireless communication system gains new functions, including device tracking, target localization, object identification, and radio environment mapping. On the other hand, communication performance is enhanced through sensing. However, the research on ISAC is still in its infancy, and the fundamental and comprehensive theoretical methods and technical standards have not yet been established.
{"title":"Integrated sensing and communication for future wireless networks","authors":"Shi Jin, Christos Masouros, Fan Liu, Jie Xu, Jie Yang","doi":"10.23919/jcc.2023.10251767","DOIUrl":"https://doi.org/10.23919/jcc.2023.10251767","url":null,"abstract":"Integrated sensing and communication (ISAC) is anticipated to play a pivotal role in realizing the ability to sense, control, and optimize wireless environments, as well as providing ubiquitous connectivity with ultra-high throughput and reliability, and ultra-low latency for future wireless networks. Therefore, it can meet the requirements of mass data transmission, centimeter-level localization, and highly fine-grained environmental sensing for new applications, such as extended reality, holographic communication, autonomous driving, smart healthcare, and intelligent industry. The technology of ISAC deviates from traditional pattern of isolated design for communication and sensing. It can efficiently utilize wireless resources and potentially achieve mutual benefits by combining sensing and communication systems. The ultimate goal of the ISAC system has two aspects. On the one hand, the wireless communication system gains new functions, including device tracking, target localization, object identification, and radio environment mapping. On the other hand, communication performance is enhanced through sensing. However, the research on ISAC is still in its infancy, and the fundamental and comprehensive theoretical methods and technical standards have not yet been established.","PeriodicalId":9814,"journal":{"name":"China Communications","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135299504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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