Pub Date : 2025-06-30DOI: 10.1109/JSAC.2025.3584503
Hao Chen;Ruizhe Long;Ying-Chang Liang;Gui Zhou
Symbiotic radio (SR) has emerged as a promising technology for enabling efficient spectrum and power sharing between active and backscattering transmissions. In this paper, we investigate the reconfigurable intelligent surface (RIS)-assisted SR system, where the primary transmission uses orthogonal frequency division multiplexing (OFDM) and the RIS transmits the secondary signal by backscattering the primary signal. The primary OFDM block and the secondary symbol have identical symbol periods but may not be perfectly synchronized, which can introduce inter-carrier interference (ICI) in the received OFDM blocks, thereby hindering joint signal detection. To address this issue, we propose a novel pilot structure and receiver design for SR. Specifically, the RIS sent a training sequence at the beginning of the secondary transmission, enabling the receiver to detect the presence of ICI and estimate essential parameters. If ICI is detected, two effective methods for synchronization offset estimation are proposed. Then, joint signal detection is improved by properly decoupling primary and secondary signals, mitigating the impact of synchronization offsets. On the other hand, if ICI is absent, the secondary signal arrival is identified using the training sequence, and joint signal detection is directly performed without suffering ICI. Simulation results validate the accuracy of the proposed estimation methods and show that the proposed detection methods ensure the reliable detection of both primary and secondary signals, even in the presence of ICI.
{"title":"Realizing Spectrum and Power Sharing With Wi-Fi: A RIS-Assisted Symbiotic Radio Perspective","authors":"Hao Chen;Ruizhe Long;Ying-Chang Liang;Gui Zhou","doi":"10.1109/JSAC.2025.3584503","DOIUrl":"10.1109/JSAC.2025.3584503","url":null,"abstract":"Symbiotic radio (SR) has emerged as a promising technology for enabling efficient spectrum and power sharing between active and backscattering transmissions. In this paper, we investigate the reconfigurable intelligent surface (RIS)-assisted SR system, where the primary transmission uses orthogonal frequency division multiplexing (OFDM) and the RIS transmits the secondary signal by backscattering the primary signal. The primary OFDM block and the secondary symbol have identical symbol periods but may not be perfectly synchronized, which can introduce inter-carrier interference (ICI) in the received OFDM blocks, thereby hindering joint signal detection. To address this issue, we propose a novel pilot structure and receiver design for SR. Specifically, the RIS sent a training sequence at the beginning of the secondary transmission, enabling the receiver to detect the presence of ICI and estimate essential parameters. If ICI is detected, two effective methods for synchronization offset estimation are proposed. Then, joint signal detection is improved by properly decoupling primary and secondary signals, mitigating the impact of synchronization offsets. On the other hand, if ICI is absent, the secondary signal arrival is identified using the training sequence, and joint signal detection is directly performed without suffering ICI. Simulation results validate the accuracy of the proposed estimation methods and show that the proposed detection methods ensure the reliable detection of both primary and secondary signals, even in the presence of ICI.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3846-3860"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520571","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 : 2025-06-30DOI: 10.1109/JSAC.2025.3584514
Jia-Xing You;Guu-Chang Yang;Wing C. Kwong
Cognitive radio (CR) technologies have long been studied and continue to attract attention for their potential to enhance wireless spectrum sharing and utilization. In CR ad hoc wireless networks (CRAHWNs), unlicensed secondary nodes (SNs) are equipped with CR transceivers capable of continuously scanning for unoccupied wireless channels. This scanning process is managed through channel-hopping (CH) rendezvous schemes, which assign CH sequences to SNs, enabling dynamic control of frequency-hopping patterns used by their CR transceivers. Traditional CH schemes operate under “global” labeling, where all SNs share an identical mapping between logical channels in their CH sequences and the transmission/reception frequencies utilized by their CR transceivers. However, when SNs operate with differing channel-to-frequency mappings—arising from regional variations or restricted access to a common frequency set—rendezvous attempts fail, preventing data exchange. Despite its importance, the development of CH sequences capable of supporting “autonomous” labeling, enabling SNs with diverse channel-to-frequency mappings to achieve successful rendezvous, remains unexplored. This paper introduces a novel class of asynchronous “universal-label” CH sequences designed to seamlessly adapt to both global and autonomous labeling frameworks. Performance evaluations demonstrate that the proposed sequences achieve an optimal balance of essential properties. These advancements enable efficient spectrum sharing and utilization in CRAHWNs, even under challenging autonomous labeling scenarios.
{"title":"Universal-Label Channel-Hopping Sequences for Efficient Spectrum Sharing and Utilization Among Unlicensed Nodes in Ad Hoc Wireless Networks","authors":"Jia-Xing You;Guu-Chang Yang;Wing C. Kwong","doi":"10.1109/JSAC.2025.3584514","DOIUrl":"10.1109/JSAC.2025.3584514","url":null,"abstract":"Cognitive radio (CR) technologies have long been studied and continue to attract attention for their potential to enhance wireless spectrum sharing and utilization. In CR ad hoc wireless networks (CRAHWNs), unlicensed secondary nodes (SNs) are equipped with CR transceivers capable of continuously scanning for unoccupied wireless channels. This scanning process is managed through channel-hopping (CH) rendezvous schemes, which assign CH sequences to SNs, enabling dynamic control of frequency-hopping patterns used by their CR transceivers. Traditional CH schemes operate under “global” labeling, where all SNs share an identical mapping between logical channels in their CH sequences and the transmission/reception frequencies utilized by their CR transceivers. However, when SNs operate with differing channel-to-frequency mappings—arising from regional variations or restricted access to a common frequency set—rendezvous attempts fail, preventing data exchange. Despite its importance, the development of CH sequences capable of supporting “autonomous” labeling, enabling SNs with diverse channel-to-frequency mappings to achieve successful rendezvous, remains unexplored. This paper introduces a novel class of asynchronous “universal-label” CH sequences designed to seamlessly adapt to both global and autonomous labeling frameworks. Performance evaluations demonstrate that the proposed sequences achieve an optimal balance of essential properties. These advancements enable efficient spectrum sharing and utilization in CRAHWNs, even under challenging autonomous labeling scenarios.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3861-3874"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520562","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 : 2025-06-30DOI: 10.1109/JSAC.2025.3584434
Lingnan Xie;Linning Peng;Junqing Zhang;Ang Gao;Hua Fu;Junxian Shi
In radio frequency fingerprint identification (RFFI) systems, mitigating channel interference remains a critical challenge. This paper introduces a robust RFFI system to tackle this issue effectively. Specifically, taking the IEEE 802.11 signal as the case study, a signal representation is designed based on the logarithmic spectrum, while an RFF extractor based on the U-Net neural network is employed which is guided by a proposed Channel2Channel (C2C) algorithm and powered by a designed data augmentation method. Furthermore, a collaborative identification mechanism is proposed based on a support vector machine (SVM) classifier, where a multi-frame RFF fusion method is designed to exploit the diversity across different frames of received signal. Extensive experimental evaluations are performed in various real-world scenarios using 7 mobile phones and a universal software radio peripheral (USRP) X310 receiver, where an average classification accuracy of 95.72% is obtained with a single frame of received signal, outperforming the neural network-based benchmarks, and an average accuracy of 99.46% is acquired with 10 signal frames based on the proposed collaborative identification method. In addition, the deployability of the system on a resource-constrained computing platform is also validated.
{"title":"Channel2Channel: Toward Robust Radio Frequency Fingerprint Extraction and Identification","authors":"Lingnan Xie;Linning Peng;Junqing Zhang;Ang Gao;Hua Fu;Junxian Shi","doi":"10.1109/JSAC.2025.3584434","DOIUrl":"10.1109/JSAC.2025.3584434","url":null,"abstract":"In radio frequency fingerprint identification (RFFI) systems, mitigating channel interference remains a critical challenge. This paper introduces a robust RFFI system to tackle this issue effectively. Specifically, taking the IEEE 802.11 signal as the case study, a signal representation is designed based on the logarithmic spectrum, while an RFF extractor based on the U-Net neural network is employed which is guided by a proposed Channel2Channel (C2C) algorithm and powered by a designed data augmentation method. Furthermore, a collaborative identification mechanism is proposed based on a support vector machine (SVM) classifier, where a multi-frame RFF fusion method is designed to exploit the diversity across different frames of received signal. Extensive experimental evaluations are performed in various real-world scenarios using 7 mobile phones and a universal software radio peripheral (USRP) X310 receiver, where an average classification accuracy of 95.72% is obtained with a single frame of received signal, outperforming the neural network-based benchmarks, and an average accuracy of 99.46% is acquired with 10 signal frames based on the proposed collaborative identification method. In addition, the deployability of the system on a resource-constrained computing platform is also validated.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3737-3751"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520566","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}
Multi-band massive multiple-input multiple-output (MIMO) communication can promote the cooperation of licensed and unlicensed spectra, effectively enhancing spectrum efficiency for Wi-Fi and other wireless systems. As an enabler for multi-band transmission, channel fingerprints (CF), also known as the channel knowledge map or radio environment map, are used to assist channel state information (CSI) acquisition and reduce computational complexity. In this paper, we propose CF-CGN (Channel Fingerprints with Cycle-consistent Generative Networks) to extrapolate CF for multi-band massive MIMO transmission where licensed and unlicensed spectra cooperate to provide ubiquitous connectivity. Specifically, we first model CF as a multichannel image and transform the extrapolation problem into an image translation task, which converts CF from one frequency to another by exploring the shared characteristics of statistical CSI in the beam domain. Then, paired generative networks are designed and coupled by variable-weight cycle consistency losses to fit the reciprocal relationship at different bands. Matched with the coupled networks, a joint training strategy is developed accordingly, supporting synchronous optimization of all trainable parameters. During the inference process, we also introduce a refining scheme to improve the extrapolation accuracy based on the resolution of CF. Numerical results illustrate that our proposed CF-CGN can achieve bidirectional extrapolation with an error of $5~sim ~17$ dB lower than the benchmarks in different communication scenarios, demonstrating its excellent generalization ability. We further show that the sum rate performance assisted by CF-CGN-based CF is close to that with perfect CSI for multi-band massive MIMO transmission.
{"title":"CF-CGN: Channel Fingerprints Extrapolation for Multi-Band Massive MIMO Transmission Based on Cycle-Consistent Generative Networks","authors":"Chenjie Xie;Li You;Zhenzhou Jin;Jinke Tang;Xiqi Gao;Xiang-Gen Xia","doi":"10.1109/JSAC.2025.3584499","DOIUrl":"10.1109/JSAC.2025.3584499","url":null,"abstract":"Multi-band massive multiple-input multiple-output (MIMO) communication can promote the cooperation of licensed and unlicensed spectra, effectively enhancing spectrum efficiency for Wi-Fi and other wireless systems. As an enabler for multi-band transmission, channel fingerprints (CF), also known as the channel knowledge map or radio environment map, are used to assist channel state information (CSI) acquisition and reduce computational complexity. In this paper, we propose CF-CGN (Channel Fingerprints with Cycle-consistent Generative Networks) to extrapolate CF for multi-band massive MIMO transmission where licensed and unlicensed spectra cooperate to provide ubiquitous connectivity. Specifically, we first model CF as a multichannel image and transform the extrapolation problem into an image translation task, which converts CF from one frequency to another by exploring the shared characteristics of statistical CSI in the beam domain. Then, paired generative networks are designed and coupled by variable-weight cycle consistency losses to fit the reciprocal relationship at different bands. Matched with the coupled networks, a joint training strategy is developed accordingly, supporting synchronous optimization of all trainable parameters. During the inference process, we also introduce a refining scheme to improve the extrapolation accuracy based on the resolution of CF. Numerical results illustrate that our proposed CF-CGN can achieve bidirectional extrapolation with an error of <inline-formula> <tex-math>$5~sim ~17$ </tex-math></inline-formula> dB lower than the benchmarks in different communication scenarios, demonstrating its excellent generalization ability. We further show that the sum rate performance assisted by CF-CGN-based CF is close to that with perfect CSI for multi-band massive MIMO transmission.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3722-3736"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520570","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 : 2025-06-30DOI: 10.1109/JSAC.2025.3584431
Qinglin Zhao;Fangxin Xu;Li Feng;MengChu Zhou;Meng Shen;Peiyun Zhang;Yi Sun
The widespread adoption of WiFi has made throughput efficiency a critical concern in wireless networks. While Full-Duplex (FD) technology promises to double network capacity by enabling simultaneous transmission and reception, existing FD-WiFi designs focus on the data transmission phase, leaving the fundamental inefficiencies in channel contention unaddressed. This paper presents CollFree, a novel WiFi protocol that exploits FD capabilities during both contention and data transmission phases. At its core, CollFree introduces a Slotwise Arbitration (SA) mechanism that enables each node to simultaneously transmit contention signals and sense channel status in each contention slot. This dual-mode operation significantly reduces contention time and facilitates collision- free data transmissions through a unique winner-determination process. We then develop theoretical models to analyze CollFree’s contention performance and throughput efficiency under both perfect and imperfect Clear Channel Assessment (CCA) conditions, providing guidelines for parameter optimization in practical deployments. Extensive simulations demonstrate that CollFree enhances throughput efficiency by over 20% compared to state-of-the-art FD-WiFi systems while maintaining distributed control and compatibility with current WiFi standards. These results suggest that it represents a significant step toward realizing the full potential of FD technology in next-generation WiFi networks.
{"title":"CollFree: Exploiting Full-Duplex Capabilities in WiFi Contention for Enhanced Throughput Efficiency","authors":"Qinglin Zhao;Fangxin Xu;Li Feng;MengChu Zhou;Meng Shen;Peiyun Zhang;Yi Sun","doi":"10.1109/JSAC.2025.3584431","DOIUrl":"10.1109/JSAC.2025.3584431","url":null,"abstract":"The widespread adoption of WiFi has made throughput efficiency a critical concern in wireless networks. While Full-Duplex (FD) technology promises to double network capacity by enabling simultaneous transmission and reception, existing FD-WiFi designs focus on the data transmission phase, leaving the fundamental inefficiencies in channel contention unaddressed. This paper presents CollFree, a novel WiFi protocol that exploits FD capabilities during both contention and data transmission phases. At its core, CollFree introduces a Slotwise Arbitration (SA) mechanism that enables each node to simultaneously transmit contention signals and sense channel status in each contention slot. This dual-mode operation significantly reduces contention time and facilitates collision- free data transmissions through a unique winner-determination process. We then develop theoretical models to analyze CollFree’s contention performance and throughput efficiency under both perfect and imperfect Clear Channel Assessment (CCA) conditions, providing guidelines for parameter optimization in practical deployments. Extensive simulations demonstrate that CollFree enhances throughput efficiency by over 20% compared to state-of-the-art FD-WiFi systems while maintaining distributed control and compatibility with current WiFi standards. These results suggest that it represents a significant step toward realizing the full potential of FD technology in next-generation WiFi networks.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3875-3888"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520621","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 : 2025-06-30DOI: 10.1109/JSAC.2025.3584502
Haiyang Miao;Jianhua Zhang;Pan Tang;Lei Tian;Weirang Zuo;Hongbo Xing;Guangyi Liu
Multiple-input-multiple-output (MIMO) has been a promising technology in wireless communication systems. Channel models are of great importance for the development and assessment of system. With the increase of carrier frequency and MIMO size, the channel model needs to consider near-field spherical wave and spatial non-stationary characteristics, which is different from conventional far-field planar-wave-based geometry-based stochastic model (GBSM) in the 3rd Generation Partnership Project (3GPP). This paper focuses on comparing the channel characteristics and modeling in the far- and near-field region. In this work, we design the measurement campaign in the 6 GHz band (5.9-6.1 GHz) involving the unlicensed spectrum. The uniform planar array (UPA) is adopted from far-field to near-field, where the communication distance is decreasing from 21 m to 6 m (Rayleigh distance is about 14.8 m). Compared to the far-field, the spatial non-stationary phenomenon of channel parameters can be more clearly observed along the array in the near-field region. Then, we propose the extension channel model based on the channel modeling of 3GPP TR 38.901. The array domain is introduced to characterize the spatial non-stationarity of channel parameters (e.g., power, delay, angle). Subsequently, the channel characteristic parameters along the array are analyzed in the near-field range, and the non-stationary model related to the antenna array is established, including power, path loss, delay spread, angular spread, and Ricean K-factor. Finally, the model validation and parametrization are presented in detail with the actual indoor near-field MIMO channel measurements in the 6 GHz band, such as power, angle, and so on. The design and scheme of antenna array spacing are given under the influence of spatial non-stationary characteristics. These work will be helpful for the development and operation of MIMO technology in unlicensed spectra for wireless communication systems.
{"title":"Far-Field to Near-Field: Experimental Studies of MIMO Channel Characterization and Modeling in the 6 GHz Band","authors":"Haiyang Miao;Jianhua Zhang;Pan Tang;Lei Tian;Weirang Zuo;Hongbo Xing;Guangyi Liu","doi":"10.1109/JSAC.2025.3584502","DOIUrl":"10.1109/JSAC.2025.3584502","url":null,"abstract":"Multiple-input-multiple-output (MIMO) has been a promising technology in wireless communication systems. Channel models are of great importance for the development and assessment of system. With the increase of carrier frequency and MIMO size, the channel model needs to consider near-field spherical wave and spatial non-stationary characteristics, which is different from conventional far-field planar-wave-based geometry-based stochastic model (GBSM) in the 3rd Generation Partnership Project (3GPP). This paper focuses on comparing the channel characteristics and modeling in the far- and near-field region. In this work, we design the measurement campaign in the 6 GHz band (5.9-6.1 GHz) involving the unlicensed spectrum. The uniform planar array (UPA) is adopted from far-field to near-field, where the communication distance is decreasing from 21 m to 6 m (Rayleigh distance is about 14.8 m). Compared to the far-field, the spatial non-stationary phenomenon of channel parameters can be more clearly observed along the array in the near-field region. Then, we propose the extension channel model based on the channel modeling of 3GPP TR 38.901. The array domain is introduced to characterize the spatial non-stationarity of channel parameters (e.g., power, delay, angle). Subsequently, the channel characteristic parameters along the array are analyzed in the near-field range, and the non-stationary model related to the antenna array is established, including power, path loss, delay spread, angular spread, and Ricean K-factor. Finally, the model validation and parametrization are presented in detail with the actual indoor near-field MIMO channel measurements in the 6 GHz band, such as power, angle, and so on. The design and scheme of antenna array spacing are given under the influence of spatial non-stationary characteristics. These work will be helpful for the development and operation of MIMO technology in unlicensed spectra for wireless communication systems.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3889-3902"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520660","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 : 2025-06-18DOI: 10.1109/JSAC.2025.3576465
{"title":"IEEE Journal on Selected Areas in Communications Publication Information","authors":"","doi":"10.1109/JSAC.2025.3576465","DOIUrl":"https://doi.org/10.1109/JSAC.2025.3576465","url":null,"abstract":"","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 7","pages":"C2-C2"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039755","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314798","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-18DOI: 10.1109/JSAC.2025.3557932
Jun Chen;Alexandros G. Dimakis;Yong Fang;Ashish Khisti;Ayfer Özgür;Nir Shlezinger
{"title":"Guest Editorial: Rethinking the Information Identification, Representation, and Transmission Pipeline: New Approaches to Data Compression and Communication","authors":"Jun Chen;Alexandros G. Dimakis;Yong Fang;Ashish Khisti;Ayfer Özgür;Nir Shlezinger","doi":"10.1109/JSAC.2025.3557932","DOIUrl":"https://doi.org/10.1109/JSAC.2025.3557932","url":null,"abstract":"","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 7","pages":"2328-2332"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039751","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144314678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-18DOI: 10.1109/JSAC.2025.3576467
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/JSAC.2025.3576467","DOIUrl":"10.1109/JSAC.2025.3576467","url":null,"abstract":"","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 7","pages":"C3-C3"},"PeriodicalIF":0.0,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11039750","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144319843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-06-10DOI: 10.1109/JSAC.2025.3574624
Dezhao Chen;Tongxin Huang;Jianghong Shi;Xuemin Hong;Yang Yang
The converging trends of reinforcement learning (RL) control and cloud-fog automation in industrial cyber-physical systems impose multiple challenges for communications to cope with stringent requirements in latency, reliability, control effectiveness and bifurcating user demands. Progressive goal-oriented (GO) communication is a promising technology to tackle the above challenges. This paper takes a two-step approach to design the first progressive codec of GO communications tailored for RL control tasks. The first step is to design a variable-rate coding scheme that extends the boundaries of rate regimes. This step is achieved by empowering the hierarchical variational autoencoder (HVAE) framework with novel algorithms such as mutual information based soft state abstraction (MISA). The second step is to transform variable-rate encoding into progressive encoding. This is achieved by applying residual-based encoding techniques upon latent representations learned by deep neural networks. Experiments on the Cartpole Swingup task demonstrate that the proposed progressive codec can facilitate smooth transitions from the ultra-low rate regime to regular rate regime, while achieving the state-of-the-art performance in terms of rate-distortion-effectiveness tradeoff.
{"title":"Progressive Goal-Oriented Communications for Reinforcement Learning Control Over Multi-Tier Computing Systems","authors":"Dezhao Chen;Tongxin Huang;Jianghong Shi;Xuemin Hong;Yang Yang","doi":"10.1109/JSAC.2025.3574624","DOIUrl":"10.1109/JSAC.2025.3574624","url":null,"abstract":"The converging trends of reinforcement learning (RL) control and cloud-fog automation in industrial cyber-physical systems impose multiple challenges for communications to cope with stringent requirements in latency, reliability, control effectiveness and bifurcating user demands. Progressive goal-oriented (GO) communication is a promising technology to tackle the above challenges. This paper takes a two-step approach to design the first progressive codec of GO communications tailored for RL control tasks. The first step is to design a variable-rate coding scheme that extends the boundaries of rate regimes. This step is achieved by empowering the hierarchical variational autoencoder (HVAE) framework with novel algorithms such as mutual information based soft state abstraction (MISA). The second step is to transform variable-rate encoding into progressive encoding. This is achieved by applying residual-based encoding techniques upon latent representations learned by deep neural networks. Experiments on the Cartpole Swingup task demonstrate that the proposed progressive codec can facilitate smooth transitions from the ultra-low rate regime to regular rate regime, while achieving the state-of-the-art performance in terms of rate-distortion-effectiveness tradeoff.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 9","pages":"3056-3071"},"PeriodicalIF":17.2,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144260013","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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