Pub Date : 2025-06-30DOI: 10.1109/JSAC.2025.3584564
Stefano Avallone;Pasquale Imputato
The IEEE 802.11 working group is currently finalizing the 802.11be amendment, which defines the features that will be supported by Wi-Fi 7 devices. A prominent new feature, termed Multi-Link Operations (MLO), is the ability for a device to operate on multiple links, i.e., on multiple frequency channels. Among the various MLO modes defined, Enhanced Multi-Link Single Radio (EMLSR) is attracting the interest of many vendors due to its potential for exploiting operations on multiple links through reduced hardware capabilities. In this paper, we first provide an overview of the standard specifications for EMLSR and describe the model underlying its implementation that we have contributed to the ns-3 simulator. The implemented model is rather flexible and enables to simulate various architectures differing for implementation cost, power consumption and performance. Then, we thoroughly evaluate several EMLSR configurations with the goal of shedding light on the possible alternatives that are available. We consider both a scenario of saturated conditions without interfering traffic and a scenario of non-saturated conditions with interfering traffic. Our study shows that the main differences in performance among the various EMLSR configurations are observed in the uplink direction and that EMLSR operations enable to reduce latency with respect to single-link devices at the cost of a slight increase in power consumption.
{"title":"Understanding the New Enhanced Multi-Link Single Radio Feature of IEEE 802.11be WLANs","authors":"Stefano Avallone;Pasquale Imputato","doi":"10.1109/JSAC.2025.3584564","DOIUrl":"10.1109/JSAC.2025.3584564","url":null,"abstract":"The IEEE 802.11 working group is currently finalizing the 802.11be amendment, which defines the features that will be supported by Wi-Fi 7 devices. A prominent new feature, termed Multi-Link Operations (MLO), is the ability for a device to operate on multiple <italic>links</i>, i.e., on multiple frequency channels. Among the various MLO modes defined, Enhanced Multi-Link Single Radio (EMLSR) is attracting the interest of many vendors due to its potential for exploiting operations on multiple links through reduced hardware capabilities. In this paper, we first provide an overview of the standard specifications for EMLSR and describe the model underlying its implementation that we have contributed to the ns-3 simulator. The implemented model is rather flexible and enables to simulate various architectures differing for implementation cost, power consumption and performance. Then, we thoroughly evaluate several EMLSR configurations with the goal of shedding light on the possible alternatives that are available. We consider both a scenario of saturated conditions without interfering traffic and a scenario of non-saturated conditions with interfering traffic. Our study shows that the main differences in performance among the various EMLSR configurations are observed in the uplink direction and that EMLSR operations enable to reduce latency with respect to single-link devices at the cost of a slight increase in power consumption.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3683-3694"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520572","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.2025.3584515
Juan Fang;Qinghua Li;Cheng Chen;Assaf Gurevitz;Yaron Yoffe
The IEEE 802.11 working group has formed a new Task Group, 802.11bn, to develop a new amendment to support ultra-high reliability (UHR) for Wi-Fi networks, which will eventually shape what Wi-Fi 8 will look like. In this paper, we propose a probabilistic shaping (PS) scheme to improve the spectrum and power efficiency in medium to high signal to noise ratio (SNR) regime for Wi-Fi 8. The integration and compatibility with legacy Wi-Fi systems, as well as other Wi-Fi 8 candidate technologies like unequal modulation (UEQM) are addressed. An architecture with a single low-density parity-check (LDPC) encoder and multiple shaping encoders is devised to adapt to different qualities of spatial channels. Furthermore, we propose practical techniques to resolve issues like error propagation, scrambler re-synchronization, and packet length determination to ensure compatibility with legacy scrambling, subframe detection, and packaging flow. It is shown that the proposed constellation shaping scheme provides average 0.89 dB shaping gains over the legacy Wi-Fi scheme, and the shaping gains remain when UEQM and lifted LDPC are applied.
{"title":"Probabilistic Shaping for Wi-Fi 8","authors":"Juan Fang;Qinghua Li;Cheng Chen;Assaf Gurevitz;Yaron Yoffe","doi":"10.1109/JSAC.2025.3584515","DOIUrl":"10.1109/JSAC.2025.3584515","url":null,"abstract":"The IEEE 802.11 working group has formed a new Task Group, 802.11bn, to develop a new amendment to support ultra-high reliability (UHR) for Wi-Fi networks, which will eventually shape what Wi-Fi 8 will look like. In this paper, we propose a probabilistic shaping (PS) scheme to improve the spectrum and power efficiency in medium to high signal to noise ratio (SNR) regime for Wi-Fi 8. The integration and compatibility with legacy Wi-Fi systems, as well as other Wi-Fi 8 candidate technologies like unequal modulation (UEQM) are addressed. An architecture with a single low-density parity-check (LDPC) encoder and multiple shaping encoders is devised to adapt to different qualities of spatial channels. Furthermore, we propose practical techniques to resolve issues like error propagation, scrambler re-synchronization, and packet length determination to ensure compatibility with legacy scrambling, subframe detection, and packaging flow. It is shown that the proposed constellation shaping scheme provides average 0.89 dB shaping gains over the legacy Wi-Fi scheme, and the shaping gains remain when UEQM and lifted LDPC are applied.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3708-3721"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520564","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.2025.3584427
Youngwook Son;Saewoong Bahk
There have been long efforts to refine Wi-Fi carrier sensing (CS) for more aggressive channel access, in pursuit of enhanced network performance. To this end, the recent 802.11ax amendment introduced a preamble detection (PD)-based spatial reuse, allowing concurrent transmissions between adjacent links via adjustable sensitivity levels. Against these conventional ideas, this paper presents a different perspective: Wi-Fi devices already have excessive transmission (TX) opportunities in practice, even without detecting each other under certain scenarios. We shed light on CS anomalies relevant to undetected preambles, which not only cause adjacent devices to transmit concurrently but are also triggered by the new PD-based mechanism, ultimately disrupting its intended operations. Our testbed experiments and in-depth scrutiny reveal the dominant impact of these anomalies on overall network behaviors. Based on these insights, we present two comprehensive frameworks, $textsf {REFRAIN}$ and $textsf {AdOPT}$ , to fully exploit TX opportunities enabled by the anomalies and PD-based mechanism respectively, for practical spatial reuse. Prototypes using commercial Wi-Fi devices and NI USRP show the feasibility and effectiveness of our approaches. Extensive simulation results further demonstrate that $textsf {REFRAIN}$ and $textsf {AdOPT}$ achieve up to 1.94$times$ and 1.61$times$ higher average throughput, only with reduced transmission attempts by half, highlighting their potential to elevate network capacity and efficiency in practical Wi-Fi networks.
{"title":"Bringing Spatial Reuse Into Practice for Distributed Wi-Fi Networks: Preamble Detection and Anomalies","authors":"Youngwook Son;Saewoong Bahk","doi":"10.1109/JSAC.2025.3584427","DOIUrl":"10.1109/JSAC.2025.3584427","url":null,"abstract":"There have been long efforts to refine Wi-Fi carrier sensing (CS) for more aggressive channel access, in pursuit of enhanced network performance. To this end, the recent 802.11ax amendment introduced a preamble detection (PD)-based spatial reuse, allowing concurrent transmissions between adjacent links via adjustable sensitivity levels. Against these conventional ideas, this paper presents a different perspective: Wi-Fi devices already have excessive transmission (TX) opportunities in practice, even without detecting each other under certain scenarios. We shed light on CS anomalies relevant to undetected preambles, which not only cause adjacent devices to transmit concurrently but are also triggered by the new PD-based mechanism, ultimately disrupting its intended operations. Our testbed experiments and in-depth scrutiny reveal the dominant impact of these anomalies on overall network behaviors. Based on these insights, we present two comprehensive frameworks, <inline-formula> <tex-math>$textsf {REFRAIN}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$textsf {AdOPT}$ </tex-math></inline-formula>, to fully exploit TX opportunities enabled by the anomalies and PD-based mechanism respectively, for practical spatial reuse. Prototypes using commercial Wi-Fi devices and NI USRP show the feasibility and effectiveness of our approaches. Extensive simulation results further demonstrate that <inline-formula> <tex-math>$textsf {REFRAIN}$ </tex-math></inline-formula> and <inline-formula> <tex-math>$textsf {AdOPT}$ </tex-math></inline-formula> achieve up to 1.94<inline-formula> <tex-math>$times$ </tex-math></inline-formula> and 1.61<inline-formula> <tex-math>$times$ </tex-math></inline-formula> higher average throughput, only with reduced transmission attempts by half, highlighting their potential to elevate network capacity and efficiency in practical Wi-Fi networks.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3616-3632"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520568","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.2025.3584497
Yayu Gao;Muyuan Shen;Yu Zou;Hao Yin;Sumit Roy
As a groundbreaking feature in IEEE 802.11be, multi-link operation (MLO) is expected to support emerging applications that are strongly delay-sensitive. A key to the effective use of MLO for such cases rests on the optimal allocation of application traffic across multiple links. Our initial simulation experiments in ns-3 reveal that the proposed traffic allocation policies in prior art are significantly sub-optimal in terms of achievable delay performance of multi-link devices (MLDs), particularly in the presence of legacy single-link devices (SLDs). In this work, we first develop a new analytical model for the mean end-to-end (E2E) delay, delay jitter and worst-case percentile latency performance of MLD-SLD-coexisting Wi-Fi 7 networks (largely unexplored to date) with saturated and unsaturated SLD traffic. Subsequently, the optimal traffic allocation strategies for minimizing the mean E2E delay and delay jitter are obtained and validated by ns-3 simulation results. It is shown that with the optimal policy, MLDs can achieve significantly better mean E2E delay, delay jitter, worst-case latency and delay cumulative distribution function (CDF) compared to existing solutions.
{"title":"Latency Optimal Traffic-to-Link Allocation for MLO/SLO Coexistence in Wi-Fi 7","authors":"Yayu Gao;Muyuan Shen;Yu Zou;Hao Yin;Sumit Roy","doi":"10.1109/JSAC.2025.3584497","DOIUrl":"10.1109/JSAC.2025.3584497","url":null,"abstract":"As a groundbreaking feature in IEEE 802.11be, multi-link operation (MLO) is expected to support emerging applications that are strongly delay-sensitive. A key to the effective use of MLO for such cases rests on the optimal allocation of application traffic across multiple links. Our initial simulation experiments in ns-3 reveal that the proposed traffic allocation policies in prior art are significantly sub-optimal in terms of achievable delay performance of multi-link devices (MLDs), particularly in the presence of legacy single-link devices (SLDs). In this work, we first develop a new analytical model for the mean end-to-end (E2E) delay, delay jitter and worst-case percentile latency performance of MLD-SLD-coexisting Wi-Fi 7 networks (largely unexplored to date) with saturated and unsaturated SLD traffic. Subsequently, the optimal traffic allocation strategies for minimizing the mean E2E delay and delay jitter are obtained and validated by ns-3 simulation results. It is shown that with the optimal policy, MLDs can achieve significantly better mean E2E delay, delay jitter, worst-case latency and delay cumulative distribution function (CDF) compared to existing solutions.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3633-3649"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520622","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.2025.3584510
Xin Li;Jingzhi Hu;Hongbo Wang;Zhe Chen;Jun Luo
As a technology with ubiquitous presence in unlicensed spectrum, Wi-Fi has demonstrated prominent capabilities in both communication and sensing. However, since the bandwidth requirements for communication and sensing differ significantly, channel bandwidths excessive for communication (e.g., 160 MHz) still fail to achieve multi-person sensing. Though stitching multiple consecutive channels to expand the effective bandwidth sounds plausible, it may never reach ultra-wideband (UWB) in practice. To this end, we propose UWB-Fi as a novel Wi-Fi sensing framework with ultra-wide bandwidth, leveraging only discrete and irregular channel samples. We first design a fast channel hopping scheme to enable arbitrary channel sampling across 4.7 GHz bandwidth on commodity Wi-Fi hardware without interrupting default communications. As no algorithm exists to exploit such channel samples, we establish a theoretical analysis driven by compressive sensing, so as to enable an explainable deep learning model. This model transforms sparse channel samples into high-dimensional (position) spectra, effectively avoiding the bias-variance dilemma in parameter estimation while encoding sufficient information for general sensing. Our extensive evaluations demonstrate that UWB-Fi successfully achieves centimeter-level fine-granularity multi-person sensing.
{"title":"Enabling Ultra-Wideband Wi-Fi Sensing via Sparse Channel Sampling","authors":"Xin Li;Jingzhi Hu;Hongbo Wang;Zhe Chen;Jun Luo","doi":"10.1109/JSAC.2025.3584510","DOIUrl":"10.1109/JSAC.2025.3584510","url":null,"abstract":"As a technology with ubiquitous presence in unlicensed spectrum, Wi-Fi has demonstrated prominent capabilities in both communication and sensing. However, since the bandwidth requirements for communication and sensing differ significantly, channel bandwidths excessive for communication (e.g., 160 MHz) still fail to achieve multi-person sensing. Though stitching multiple consecutive channels to expand the effective bandwidth sounds plausible, it may never reach <italic>ultra-wideband</i> (UWB) in practice. To this end, we propose UWB-Fi as a novel Wi-Fi sensing framework with ultra-wide bandwidth, leveraging only discrete and irregular channel samples. We first design a fast channel hopping scheme to enable arbitrary channel sampling across 4.7 GHz bandwidth on commodity Wi-Fi hardware without interrupting default communications. As no algorithm exists to exploit such channel samples, we establish a theoretical analysis driven by <italic>compressive sensing</i>, so as to enable an <italic>explainable</i> deep learning model. This model transforms sparse channel samples into high-dimensional (position) spectra, effectively avoiding the <italic>bias-variance dilemma</i> in parameter estimation while encoding sufficient information for general sensing. Our extensive evaluations demonstrate that UWB-Fi successfully achieves centimeter-level fine-granularity multi-person sensing.","PeriodicalId":73294,"journal":{"name":"IEEE journal on selected areas in communications : a publication of the IEEE Communications Society","volume":"43 11","pages":"3782-3795"},"PeriodicalIF":17.2,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144520565","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.2025.3584503
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.
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