Pub Date : 2025-08-21DOI: 10.1109/TBC.2025.3597154
Zhisen Tang;Xiaokai Yi;Hanli Wang
Deep neural network (DNN)-based image compression methods have demonstrated superior rate-distortion performance compared to traditional codecs in recent years. However, most existing DNN-based compression methods only optimize signal fidelity at certain bitrate for human perception, neglecting to preserve the richness of semantics in compressed bitstream. This limitation renders the images compressed by existing deep codecs unsuitable for machine vision applications. To bridge the gap between image compression and multiple semantic analysis tasks, an integration of self-supervised learning (SSL) with deep image compression is proposed in this work to learn generic compressed representations, allowing multiple computer vision tasks to perform semantic analysis from the compressed domain. Specifically, the semantic-guided SSL under bitrate constraint is designed to preserve the semantics of generic visual features and remove the redundancy irrelevant to semantic analysis. Meanwhile, a compression network with high-order spatial interactions is proposed to capture long-range dependencies with low complexity to remove global redundancy. Without incurring decoding cost of pixel-level reconstruction, the features compressed by the proposed method can serve multiple semantic analysis tasks in a compact manner. The experimental results from multiple semantic analysis tasks confirm that the proposed method significantly outperforms traditional codecs and recent deep image compression methods in terms of various analysis performances at similar bitrates. The source code of this work can be found in https://mic.tongji.edu.cn.
{"title":"Toward Learned Image Compression for Multiple Semantic Analysis Tasks","authors":"Zhisen Tang;Xiaokai Yi;Hanli Wang","doi":"10.1109/TBC.2025.3597154","DOIUrl":"https://doi.org/10.1109/TBC.2025.3597154","url":null,"abstract":"Deep neural network (DNN)-based image compression methods have demonstrated superior rate-distortion performance compared to traditional codecs in recent years. However, most existing DNN-based compression methods only optimize signal fidelity at certain bitrate for human perception, neglecting to preserve the richness of semantics in compressed bitstream. This limitation renders the images compressed by existing deep codecs unsuitable for machine vision applications. To bridge the gap between image compression and multiple semantic analysis tasks, an integration of self-supervised learning (SSL) with deep image compression is proposed in this work to learn generic compressed representations, allowing multiple computer vision tasks to perform semantic analysis from the compressed domain. Specifically, the semantic-guided SSL under bitrate constraint is designed to preserve the semantics of generic visual features and remove the redundancy irrelevant to semantic analysis. Meanwhile, a compression network with high-order spatial interactions is proposed to capture long-range dependencies with low complexity to remove global redundancy. Without incurring decoding cost of pixel-level reconstruction, the features compressed by the proposed method can serve multiple semantic analysis tasks in a compact manner. The experimental results from multiple semantic analysis tasks confirm that the proposed method significantly outperforms traditional codecs and recent deep image compression methods in terms of various analysis performances at similar bitrates. The source code of this work can be found in <uri>https://mic.tongji.edu.cn</uri>.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"1022-1033"},"PeriodicalIF":4.8,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-08-20DOI: 10.1109/TBC.2025.3597096
Linxia Zhu;Jun Cheng;Xu Wang;Honglei Su;Hui Yuan;Jiarun Song;Jari Korhonen
As 3D vision applications relying on point clouds rapidly develop, point cloud quality assessment (PCQA) has emerged as a significant research area. When observing a point cloud, people typically rotate it to different viewpoints to examine local details from various angles, ultimately synthesizing the overall quality score of the point cloud. In this process, different parts of the point cloud have varying impacts on the overall quality. However, existing PCQA methods often overlook the influence of local quality variations across different regions of the point cloud. To address the imbalance in quality distribution, we introduce COPP-Net, a no-reference point cloud quality assessment (NR-PCQA) method equipped with the capability for local area correlation analysis. Specifically, we segment the point cloud into multiple patches and enhance PointNet++ to generate accurate texture and structure features for each patch. These features are then combined to predict the quality of each patch. Subsequently, we conduct aggregation analysis on the features of all patches using the correlation analysis (CORA) network based on Transformer to determine correlation weights. Finally, we calculate the overall quality score by combining the predicted quality and correlation weights of all patches. Through comparisons with the latest state-of-the-art NR-PCQA models, as well as a series of tests on different distortion types, cross-dataset validation, and time complexity analysis, the high performance of COPP-Net is verified. The available source code for the proposed COPP-Net can be found at https://github.com/philox12358/COPP-Net.
{"title":"COPP-Net: No-Reference Point Cloud Quality Assessment via Weighted Patch Quality Prediction","authors":"Linxia Zhu;Jun Cheng;Xu Wang;Honglei Su;Hui Yuan;Jiarun Song;Jari Korhonen","doi":"10.1109/TBC.2025.3597096","DOIUrl":"https://doi.org/10.1109/TBC.2025.3597096","url":null,"abstract":"As 3D vision applications relying on point clouds rapidly develop, point cloud quality assessment (PCQA) has emerged as a significant research area. When observing a point cloud, people typically rotate it to different viewpoints to examine local details from various angles, ultimately synthesizing the overall quality score of the point cloud. In this process, different parts of the point cloud have varying impacts on the overall quality. However, existing PCQA methods often overlook the influence of local quality variations across different regions of the point cloud. To address the imbalance in quality distribution, we introduce COPP-Net, a no-reference point cloud quality assessment (NR-PCQA) method equipped with the capability for local area correlation analysis. Specifically, we segment the point cloud into multiple patches and enhance PointNet++ to generate accurate texture and structure features for each patch. These features are then combined to predict the quality of each patch. Subsequently, we conduct aggregation analysis on the features of all patches using the correlation analysis (CORA) network based on Transformer to determine correlation weights. Finally, we calculate the overall quality score by combining the predicted quality and correlation weights of all patches. Through comparisons with the latest state-of-the-art NR-PCQA models, as well as a series of tests on different distortion types, cross-dataset validation, and time complexity analysis, the high performance of COPP-Net is verified. The available source code for the proposed COPP-Net can be found at <uri>https://github.com/philox12358/COPP-Net</uri>.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"1079-1091"},"PeriodicalIF":4.8,"publicationDate":"2025-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-08-12DOI: 10.1109/TBC.2025.3590570
Yasutaka Matsuo;Shuichi Aoki
To simultaneously produce 4K broadcast video with 8K broadcasts, 4K resolution videos can be captured using an 8K resolution video camera with an image downscaling process. A blocking artifact for the video coding of this 4K broadcast is likely to form in a pixel region with high coding difficulty. We developed the encoder-side preprocessing method of video coding for image downscaling to prevent the formation of blocking artifacts. Our proposed method adaptively controls the band limitation of the spatial frequency in an iteration using the spectrum power information of the original image and the quantization parameter (QP) and the motion vector (MV) in the video coding of its downscaled image. In addition, when iteration is not allowed, for example, for live broadcasts and low latency transmission, the spectrum power information of the original image and the estimated values of the QP and MV in the video coding of its downscaled image are used. These estimated QP and MV values were calculated previously using the video codec. We experimentally showed that coding in the proposed method is simpler than the conventional bicubic, Lanczos3, and wavelet methods to prevent the blocking of artifact formation. These experimental results using both methods are also discussed.
{"title":"Encoder-Aware Video Downscaling Using Encoding Parameters","authors":"Yasutaka Matsuo;Shuichi Aoki","doi":"10.1109/TBC.2025.3590570","DOIUrl":"https://doi.org/10.1109/TBC.2025.3590570","url":null,"abstract":"To simultaneously produce 4K broadcast video with 8K broadcasts, 4K resolution videos can be captured using an 8K resolution video camera with an image downscaling process. A blocking artifact for the video coding of this 4K broadcast is likely to form in a pixel region with high coding difficulty. We developed the encoder-side preprocessing method of video coding for image downscaling to prevent the formation of blocking artifacts. Our proposed method adaptively controls the band limitation of the spatial frequency in an iteration using the spectrum power information of the original image and the quantization parameter (QP) and the motion vector (MV) in the video coding of its downscaled image. In addition, when iteration is not allowed, for example, for live broadcasts and low latency transmission, the spectrum power information of the original image and the estimated values of the QP and MV in the video coding of its downscaled image are used. These estimated QP and MV values were calculated previously using the video codec. We experimentally showed that coding in the proposed method is simpler than the conventional bicubic, Lanczos3, and wavelet methods to prevent the blocking of artifact formation. These experimental results using both methods are also discussed.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"1011-1021"},"PeriodicalIF":4.8,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Medium-frequency (MF) is widely used in medium and long-range broadcasting and other scenarios such as navigation, and emergency communication, especially when other radio transmission methods are unavailable, predicting MF skywave propagation is crucial. Therefore, to improve the prediction accuracy of MF skywave propagation, we proposed an improved method based on the ITU-R P.1147 method, addressing the following aspects: (1) By redefining the solar flux factor and analyzing MF skywave field strength of 7 circuits in Europe and 9 circuits in North America, an accuracy improvement of 34.69% is achieved compared to the ITU-R P.1147 method; (2) By replacing the dipole geomagnetic latitude with the corrected dipole geomagnetic latitude and combining the basic loss coefficient with an improved ionospheric absorption factor and other relevant loss factors, an accuracy improvement of 42.78% is further achieved. Taken together, these improvements enable the proposed method to achieve a prediction accuracy improvement of 60.78% over the ITU-R P.1147 method, facilitating enhanced accuracy in MF skywave propagation predictions.
{"title":"An Improved Prediction Method of MF Skywave Propagation for Medium and Long-Range Broadcasting Services","authors":"Jianhua Yao;Yafei Shi;Jian Wang;Chengsong Duan;Qidong Chen;Fanyi Meng","doi":"10.1109/TBC.2025.3590589","DOIUrl":"https://doi.org/10.1109/TBC.2025.3590589","url":null,"abstract":"Medium-frequency (MF) is widely used in medium and long-range broadcasting and other scenarios such as navigation, and emergency communication, especially when other radio transmission methods are unavailable, predicting MF skywave propagation is crucial. Therefore, to improve the prediction accuracy of MF skywave propagation, we proposed an improved method based on the ITU-R P.1147 method, addressing the following aspects: (1) By redefining the solar flux factor and analyzing MF skywave field strength of 7 circuits in Europe and 9 circuits in North America, an accuracy improvement of 34.69% is achieved compared to the ITU-R P.1147 method; (2) By replacing the dipole geomagnetic latitude with the corrected dipole geomagnetic latitude and combining the basic loss coefficient with an improved ionospheric absorption factor and other relevant loss factors, an accuracy improvement of 42.78% is further achieved. Taken together, these improvements enable the proposed method to achieve a prediction accuracy improvement of 60.78% over the ITU-R P.1147 method, facilitating enhanced accuracy in MF skywave propagation predictions.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"965-976"},"PeriodicalIF":4.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-07-23DOI: 10.1109/TBC.2025.3587532
Feng Yuan;Zhaoqing Pan;Jianjun Lei;Bo Peng;Fu Lee Wang;Sam Kwong
The Conditional Coding-based Learned Video Compression (CC-LVC) has become an important paradigm in learned video compression, because it can effectively explore spatial-temporal redundancies within a huge context space. However, existing CC-LVC methods cannot accurately model motion information and efficiently mine contextual correlations for complex regions with non-rigid motions and non-linear deformations. To address these problems, an efficient CC-LVC method is proposed in this paper, which mines spatial-temporal dependencies across multiple motion domains and receptive domains for improving the video coding efficiency. To accurately model complex motions and generate precise temporal contexts, a Multi-domain Motion modeling Network (MMNet) is proposed to capture robust motion information from both spatial and frequency domains. Moreover, a multi-domain context refinement module is developed to discriminatively highlight frequency-domain temporal contexts and adaptively fuse multi-domain temporal contexts, which can effectively mitigate inaccuracies in temporal contexts caused by motion errors. In order to efficiently compress video signals, a Multi-scale Long Short-range Decorrelation Module (MLSDM)-based context codec is proposed, in which an MLSDM is designed to learn long short-range spatial-temporal dependencies and channel-wise correlations across varying receptive domains. Extensive experimental results show that the proposed method significantly outperforms VTM 17.0 and other state-of-the-art learned video compression methods in terms of both PSNR and MS-SSIM.
{"title":"Multi-Domain Spatial-Temporal Redundancy Mining for Efficient Learned Video Compression","authors":"Feng Yuan;Zhaoqing Pan;Jianjun Lei;Bo Peng;Fu Lee Wang;Sam Kwong","doi":"10.1109/TBC.2025.3587532","DOIUrl":"https://doi.org/10.1109/TBC.2025.3587532","url":null,"abstract":"The Conditional Coding-based Learned Video Compression (CC-LVC) has become an important paradigm in learned video compression, because it can effectively explore spatial-temporal redundancies within a huge context space. However, existing CC-LVC methods cannot accurately model motion information and efficiently mine contextual correlations for complex regions with non-rigid motions and non-linear deformations. To address these problems, an efficient CC-LVC method is proposed in this paper, which mines spatial-temporal dependencies across multiple motion domains and receptive domains for improving the video coding efficiency. To accurately model complex motions and generate precise temporal contexts, a Multi-domain Motion modeling Network (MMNet) is proposed to capture robust motion information from both spatial and frequency domains. Moreover, a multi-domain context refinement module is developed to discriminatively highlight frequency-domain temporal contexts and adaptively fuse multi-domain temporal contexts, which can effectively mitigate inaccuracies in temporal contexts caused by motion errors. In order to efficiently compress video signals, a Multi-scale Long Short-range Decorrelation Module (MLSDM)-based context codec is proposed, in which an MLSDM is designed to learn long short-range spatial-temporal dependencies and channel-wise correlations across varying receptive domains. Extensive experimental results show that the proposed method significantly outperforms VTM 17.0 and other state-of-the-art learned video compression methods in terms of both PSNR and MS-SSIM.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"808-820"},"PeriodicalIF":4.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-07-23DOI: 10.1109/TBC.2025.3587530
Aye Yadanar Win;Merhawit Berhane Teklu;Yeon Ho Chung
Orbital angular momentum (OAM) communication has emerged as a promising technology for significantly enhancing data transmission efficiency and overall system performance in free-space optical (FSO) communication systems. However, its performance is severely affected by atmospheric turbulence (AT), which leads to signal attenuation, crosstalk, and degradation in system capacity and bit error rate (BER). To address these challenges, this paper proposes a novel approach that integrates OAM multiplexing with orthogonal frequency division multiplexing using index modulation (OFDM-IM) under varying AT conditions. Additionally, a low-complexity log-likelihood ratio detector is employed for efficient signal detection. Simulation results demonstrate that the proposed system outperforms conventional OAM-MIMO in terms of BER and capacity across various turbulence regimes and OAM modes. The proposed system is evaluated using different parameters, including propagation distance, active indices, and the number of users. The results suggest that our proposed system effectively balances resilience to turbulence and spatial multiplexing, ensuring sustained capacity in challenging FSO environments.
{"title":"Performance Enhancement of OAM With OFDM-IM for FSO Communications Using LLR Detection","authors":"Aye Yadanar Win;Merhawit Berhane Teklu;Yeon Ho Chung","doi":"10.1109/TBC.2025.3587530","DOIUrl":"https://doi.org/10.1109/TBC.2025.3587530","url":null,"abstract":"Orbital angular momentum (OAM) communication has emerged as a promising technology for significantly enhancing data transmission efficiency and overall system performance in free-space optical (FSO) communication systems. However, its performance is severely affected by atmospheric turbulence (AT), which leads to signal attenuation, crosstalk, and degradation in system capacity and bit error rate (BER). To address these challenges, this paper proposes a novel approach that integrates OAM multiplexing with orthogonal frequency division multiplexing using index modulation (OFDM-IM) under varying AT conditions. Additionally, a low-complexity log-likelihood ratio detector is employed for efficient signal detection. Simulation results demonstrate that the proposed system outperforms conventional OAM-MIMO in terms of BER and capacity across various turbulence regimes and OAM modes. The proposed system is evaluated using different parameters, including propagation distance, active indices, and the number of users. The results suggest that our proposed system effectively balances resilience to turbulence and spatial multiplexing, ensuring sustained capacity in challenging FSO environments.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"784-792"},"PeriodicalIF":4.8,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-07-11DOI: 10.1109/TBC.2025.3582107
Jingbo Tan;Jintao Wang;Jian Song
Sub-terahertz (sub-THz) communications is considered one of the critical techniques in 6G network. To enlarge the antenna effective aperture and guarantee the received power, the employment of an extremely large-scale antenna array to generate high-gain beams is essential in sub-THz communications. Obtaining accurate channel path directions of users is necessary for achieving high-gain beamforming and efficient user scheduling in both unicast and multicast scenarios. However, the existing beam training schemes for acquiring channel path directions suffer from a large beam training overhead in either time-domain or frequency-domain. To solve this problem, we propose an angle-domain partition beam pattern (APBP) based beam training scheme by considering the delay-phase precoding architecture. Specifically, a wideband beam pattern called APBP is defined which covers the entire angle-domain and is realized by generating beams that cover different angle-domain partitions through different radio-frequency chains. Then, the property of the APBP is revealed that the channel path direction can be uniquely determined by using the targeted direction difference of beams satisfying two different APBPs with coprime partition numbers. Based on this property, we propose a fast beam training scheme with two stages. In the coarse estimation stage, the channel path directions are coarsely estimated by utilizing beams satisfying two different APBPs with coprime partition numbers. After that, a fine-tuning stage is operated to accurately decide the channel path directions. The proposed scheme is able to achieve accurate beam training by utilizing pilots occupying only three time slots and a small part of subcarriers. Theoretical analyses and extensive simulations have shown that the proposed scheme can realize a 75% reduction in beam training overhead with the near-optimal achievable sum-rate.
{"title":"Angle-Domain Partition Beam Pattern-Based Beam Training in Sub-THz Extremely Large-Scale Antenna Array Communication Systems","authors":"Jingbo Tan;Jintao Wang;Jian Song","doi":"10.1109/TBC.2025.3582107","DOIUrl":"https://doi.org/10.1109/TBC.2025.3582107","url":null,"abstract":"Sub-terahertz (sub-THz) communications is considered one of the critical techniques in 6G network. To enlarge the antenna effective aperture and guarantee the received power, the employment of an extremely large-scale antenna array to generate high-gain beams is essential in sub-THz communications. Obtaining accurate channel path directions of users is necessary for achieving high-gain beamforming and efficient user scheduling in both unicast and multicast scenarios. However, the existing beam training schemes for acquiring channel path directions suffer from a large beam training overhead in either time-domain or frequency-domain. To solve this problem, we propose an angle-domain partition beam pattern (APBP) based beam training scheme by considering the delay-phase precoding architecture. Specifically, a wideband beam pattern called APBP is defined which covers the entire angle-domain and is realized by generating beams that cover different angle-domain partitions through different radio-frequency chains. Then, the property of the APBP is revealed that the channel path direction can be uniquely determined by using the targeted direction difference of beams satisfying two different APBPs with coprime partition numbers. Based on this property, we propose a fast beam training scheme with two stages. In the coarse estimation stage, the channel path directions are coarsely estimated by utilizing beams satisfying two different APBPs with coprime partition numbers. After that, a fine-tuning stage is operated to accurately decide the channel path directions. The proposed scheme is able to achieve accurate beam training by utilizing pilots occupying only three time slots and a small part of subcarriers. Theoretical analyses and extensive simulations have shown that the proposed scheme can realize a 75% reduction in beam training overhead with the near-optimal achievable sum-rate.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"741-755"},"PeriodicalIF":4.8,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2025-07-10DOI: 10.1109/TBC.2025.3583873
Zhongle Wu;Yulong Hao;Jian Wang;Qingzhi Hao;Cheng Yang;Hongmin Yang
The continuous evolution of current and future wireless networks across land, sea, air, and space places increasing demands on broadcasting coverage capabilities. Existing models are difficult to fully adapt to radio propagation scenarios in China. They are generally less effective than machine learning models in capturing the complex characteristics of radio channel propagation. To support the industrial upgrading of Frequency Modulation (FM) broadcasting and enhance its quality, this study presents the construction of a high-quality FM Broadcasting Map (FM-BM) using a semi-supervised clustering method. The core construction idea is to determine the spatial distribution pattern of the optimal model, model adaption map, by clustering based on the typical model predicted path loss of the Irregular Terrain Model, ITU-R P.1546, and ITU-R P.2001 and combining them with measured path loss in the Beijing area, and to accurately map the FM-BM accordingly. This study fully considers the influence of channel propagation characteristics and terrain features in constructing FM-BM to achieve dual improvements in classification refinement and prediction accuracy. Especially in the prediction of path loss of broadcasting signal propagation, compared with the three classical models, the method proposed shows significant superiority, with the prediction accuracy improved by 48.96%. This study not only provides a novel and efficient solution for the construction of FM-BM but also lays down the technical support and reference for upgrading FM broadcasting technology and improving coverage efficiency.
{"title":"Constructing Frequency Modulation-Broadcasting Map Based on Semi-Supervised Clustering","authors":"Zhongle Wu;Yulong Hao;Jian Wang;Qingzhi Hao;Cheng Yang;Hongmin Yang","doi":"10.1109/TBC.2025.3583873","DOIUrl":"https://doi.org/10.1109/TBC.2025.3583873","url":null,"abstract":"The continuous evolution of current and future wireless networks across land, sea, air, and space places increasing demands on broadcasting coverage capabilities. Existing models are difficult to fully adapt to radio propagation scenarios in China. They are generally less effective than machine learning models in capturing the complex characteristics of radio channel propagation. To support the industrial upgrading of Frequency Modulation (FM) broadcasting and enhance its quality, this study presents the construction of a high-quality FM Broadcasting Map (FM-BM) using a semi-supervised clustering method. The core construction idea is to determine the spatial distribution pattern of the optimal model, model adaption map, by clustering based on the typical model predicted path loss of the Irregular Terrain Model, ITU-R P.1546, and ITU-R P.2001 and combining them with measured path loss in the Beijing area, and to accurately map the FM-BM accordingly. This study fully considers the influence of channel propagation characteristics and terrain features in constructing FM-BM to achieve dual improvements in classification refinement and prediction accuracy. Especially in the prediction of path loss of broadcasting signal propagation, compared with the three classical models, the method proposed shows significant superiority, with the prediction accuracy improved by 48.96%. This study not only provides a novel and efficient solution for the construction of FM-BM but also lays down the technical support and reference for upgrading FM broadcasting technology and improving coverage efficiency.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"954-964"},"PeriodicalIF":4.8,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of 5G Multicast Broadcast Services (5MBS) within 3rd Generation Partnership Project (3GPP)-based Non-Terrestrial Networks (NTN) represents a major advancement in bridging the digital divide and improving network efficiency for multicast and broadcast communication. This paper presents a comprehensive study on the integration of 5MBS over NTN, focusing on a simulation-based performance evaluation. NTN, including Geosynchronous Earth Orbit (GEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO) satellite systems, offer extensive coverage capabilities, particularly benefiting rural and underserved areas. A key highlight is the incorporation of Hybrid automatic repeat request (HARQ)-based Time Interleaving (TIL) mechanisms, which enhance broadcast resilience in NTN environments. NTN channels are characterized by high user mobility and dynamic channel conditions. By leveraging time diversity and spreading coded bits across non-consecutive slots, the proposed approach mitigates the effects of fast-fading and Doppler shift scenarios, achieving performance gains from 1 dB at lower speeds to 2.8 dB at 500 km/h, ensuring robust communication under Line of Sight (LoS) and Non Line of Sight (NLoS) conditions. This study proposes a 5MBS solution tailored for NTN deployment using a Link Level Simulator (LLS), considering channel modeling, environmental factors, and high mobility scenarios. The results show that while existing NTN setups struggle to maintain performance in high-speed environments (e.g., airplanes), the proposed HARQ-based TIL significantly improves performance under these challenging conditions. These findings validate the feasibility of integrating 5MBS with NTN and highlight its potential to deliver scalable and reliable broadcast and multicast services. The study provides valuable insights for future enhancements in 5G-Advanced systems and lays the foundation for novel Terrestrial Networks (TN)-NTN convergent deployments, contributing to the evolution of satellite-based communication networks and the International Mobile Telecommunications (IMT)-2030 evaluation process.
{"title":"5G Multicast Broadcast Services Over Non Terrestrial Networks: An In-Depth Performance Analysis","authors":"Álvaro Ibanez;Carlos Barjau;David Gomez-Barquero;Manuel Fuentes;Sung-Ik Park;Seok-Ki Ahn","doi":"10.1109/TBC.2025.3582111","DOIUrl":"https://doi.org/10.1109/TBC.2025.3582111","url":null,"abstract":"The integration of 5G Multicast Broadcast Services (5MBS) within 3rd Generation Partnership Project (3GPP)-based Non-Terrestrial Networks (NTN) represents a major advancement in bridging the digital divide and improving network efficiency for multicast and broadcast communication. This paper presents a comprehensive study on the integration of 5MBS over NTN, focusing on a simulation-based performance evaluation. NTN, including Geosynchronous Earth Orbit (GEO), Medium Earth Orbit (MEO), and Low Earth Orbit (LEO) satellite systems, offer extensive coverage capabilities, particularly benefiting rural and underserved areas. A key highlight is the incorporation of Hybrid automatic repeat request (HARQ)-based Time Interleaving (TIL) mechanisms, which enhance broadcast resilience in NTN environments. NTN channels are characterized by high user mobility and dynamic channel conditions. By leveraging time diversity and spreading coded bits across non-consecutive slots, the proposed approach mitigates the effects of fast-fading and Doppler shift scenarios, achieving performance gains from 1 dB at lower speeds to 2.8 dB at 500 km/h, ensuring robust communication under Line of Sight (LoS) and Non Line of Sight (NLoS) conditions. This study proposes a 5MBS solution tailored for NTN deployment using a Link Level Simulator (LLS), considering channel modeling, environmental factors, and high mobility scenarios. The results show that while existing NTN setups struggle to maintain performance in high-speed environments (e.g., airplanes), the proposed HARQ-based TIL significantly improves performance under these challenging conditions. These findings validate the feasibility of integrating 5MBS with NTN and highlight its potential to deliver scalable and reliable broadcast and multicast services. The study provides valuable insights for future enhancements in 5G-Advanced systems and lays the foundation for novel Terrestrial Networks (TN)-NTN convergent deployments, contributing to the evolution of satellite-based communication networks and the International Mobile Telecommunications (IMT)-2030 evaluation process.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"681-695"},"PeriodicalIF":4.8,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Current orthogonal frequency-division multiplexing (OFDM)-based integrated navigation-communication (INC) designs suffer from critical limitations, particularly high peak-to-average power ratio (PAPR), which ultimately compromises the performance of both communication throughput and positioning accuracy. This paper proposes an acquisition-assisted low PAPR INC signal design scheme. Specifically, the transmitter utilizes the selectivity of the pseudorandom sequence designed for the navigation function in the frame header to indicate the index of the phase sequence that minimizes the PAPR of the OFDM signal, thereby avoiding the transmission of side information (SI) and achieving a reduction in PAPR. The receiver leverages the correlation properties of the designed synchronization sequence to jointly recover SI and estimate Doppler shift and time delay during the acquisition phase. The computational complexity of the proposed scheme is analyzed for both signal generation and SI recovery processes. The simulation results demonstrate that the proposed INC scheme achieves significant PAPR reduction without causing a degradation in the bit error rate (BER), maintains robust detection probability in low signal-to-noise ratio (SNR) environments, and attains high acquisition accuracy.
{"title":"A Novel Low-PAPR Integrated Navigation-Communication Waveform Design for LEO Satellite Systems","authors":"Zhaoxian Yang;Miaoran Peng;Yu Zhang;Xinkun Zheng;Jiaxi Zhou;Tao Jiang","doi":"10.1109/TBC.2025.3582114","DOIUrl":"https://doi.org/10.1109/TBC.2025.3582114","url":null,"abstract":"Current orthogonal frequency-division multiplexing (OFDM)-based integrated navigation-communication (INC) designs suffer from critical limitations, particularly high peak-to-average power ratio (PAPR), which ultimately compromises the performance of both communication throughput and positioning accuracy. This paper proposes an acquisition-assisted low PAPR INC signal design scheme. Specifically, the transmitter utilizes the selectivity of the pseudorandom sequence designed for the navigation function in the frame header to indicate the index of the phase sequence that minimizes the PAPR of the OFDM signal, thereby avoiding the transmission of side information (SI) and achieving a reduction in PAPR. The receiver leverages the correlation properties of the designed synchronization sequence to jointly recover SI and estimate Doppler shift and time delay during the acquisition phase. The computational complexity of the proposed scheme is analyzed for both signal generation and SI recovery processes. The simulation results demonstrate that the proposed INC scheme achieves significant PAPR reduction without causing a degradation in the bit error rate (BER), maintains robust detection probability in low signal-to-noise ratio (SNR) environments, and attains high acquisition accuracy.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"930-940"},"PeriodicalIF":4.8,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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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