IEEE Transactions on Broadcasting最新文献_第2页

Protograph-Based Raptor-Like LDPC Codes With an Add-On Structure for Reliable Communications 基于原型的猛禽类LDPC代码，具有可靠通信的附加结构

IF 4.8 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-12 DOI: 10.1109/TBC.2025.3575341

Hyejin Ro;Junghyun Kim;Hosung Park;Sang-Hyo Kim;Seok-Ki Ahn;Sung-Ik Park

{"title":"Protograph-Based Raptor-Like LDPC Codes With an Add-On Structure for Reliable Communications","authors":"Hyejin Ro;Junghyun Kim;Hosung Park;Sang-Hyo Kim;Seok-Ki Ahn;Sung-Ik Park","doi":"10.1109/TBC.2025.3575341","DOIUrl":"https://doi.org/10.1109/TBC.2025.3575341","url":null,"abstract":"The 5G multicast and broadcast service (MBS) has been discussed since 3GPP Release 17, emphasizing resource-efficient transmission for multiple users. A primary focus of 5G MBS is enhancing reliability, even for the broadcast mode without retransmissions. In discussing 6G, the hyper reliable communication is also an important use case. In this context, the design of channel codes with low error floors is crucial to ensure robust communication for such demanding scenarios. Protograph-based raptor-like (PBRL) low-density parity-check (LDPC) codes have good error-correcting performance and rate-compatibility but the construction has focused on waterfall rather than error floor. In this paper, we propose an add-on structure for PBRL LDPC codes to have low error floors, which consists of edges added on the protographs of original PBRL LDPC codes. The added edges play a role of boosting up the reliability of weak variable nodes in the original PBRL LDPC codes. We propose two construction algorithms, one for use at a fixed rate and the other for rate-compatible use. It is shown via simulations that the proposed codes have lower error floors than the original PBRL LDPC codes for various rates. Since the edge addition does not change the existing edge connections in the protograph, an adaptive use with/without the add-on structure has an effect of implementing two PBRL LDPC codes for high-speed and reliable communications in an efficient way while keeping the system backward-compatible with the original PBRL LDPC code.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"717-731"},"PeriodicalIF":4.8,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998094","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}

引用次数: 0

MAIP: A Multi-Attribute Informativeness Proxy for Image Semantic Broadcasting Communication MAIP：图像语义广播通信的多属性信息代理

IF 4.8 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-11 DOI: 10.1109/TBC.2025.3573144

Zhuo Zhang;Shuai Xiao;Guipeng Lan;Meng Xi;Jiabao Wen;Jiachen Yang

引用次数: 0

IEEE Transactions on Broadcasting Information for Authors IEEE作者广播信息汇刊

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-09 DOI: 10.1109/TBC.2025.3569995

引用次数: 0

IEEE Transactions on Broadcasting Publication Information IEEE广播出版信息汇刊

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-09 DOI: 10.1109/TBC.2025.3569993

引用次数: 0

Fusion Prediction Model of Broadcast Radio Signal Propagation Based on the Coefficient of Variation Method 基于变异系数法的广播无线电信号传播融合预测模型

IF 4.8 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-04 DOI: 10.1109/TBC.2025.3570860

Yulong Hao;Jiaxuan Weng;Jian Wang;Zhongle Wu;Cheng Yang

引用次数: 0

Social VR With Holographic Comms: Enablers for New Engaging Experiences Within the TV / Video Consumption Landscape 带有全息通信的社交VR：电视/视频消费领域中新的引人入胜的体验的推动者

IF 4.8 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-06-02 DOI: 10.1109/TBC.2025.3570869

Mario Montagud Climent;Marc Martos;Álvaro Egea;Sergi Fernández Langa

{"title":"Social VR With Holographic Comms: Enablers for New Engaging Experiences Within the TV / Video Consumption Landscape","authors":"Mario Montagud Climent;Marc Martos;Álvaro Egea;Sergi Fernández Langa","doi":"10.1109/TBC.2025.3570869","DOIUrl":"https://doi.org/10.1109/TBC.2025.3570869","url":null,"abstract":"Social Virtual Reality (VR) enables shared media experiences between remote people inside immersive and realistic 3D spaces, providing richer and more natural interactions than in classical 2D social conferencing tools. Likewise, the benefits and engagement can even be magnified by integrating realistic and volumetric user representations (i.e., 3D holograms) in these virtual environments rather than synthetic avatars. This paper presents the design and evaluation of an interactive Social VR scenario for a joint and collaborative exploration of a catalogue of professional video clips by a broadcaster. On the one hand, the scenario includes a control panel to select the desired year and clip. After the year selection, a time travel through a lift effect is enforced to teleport users through a multi-level semi-open building in which each level / floor represents one year, and its look-and-feel is customized to resemble that year. On the other hand, the scenario allows the integration of up to four users represented as 3D holograms (full-body and full volume Point Clouds), each one with his/her own screen for video consumption, and arranged in a cross 360° shape to allow for a natural visual interaction among themselves. The evaluation results with N=48 professionals of the broadcast sector not only provide relevant insights about the technical requirements and obtained performance, but confirm the satisfactory user experience (in terms of presence, togetherness, quality of interaction) provided by the presented technology and VR scenario and, most importantly, reveal and contribute to identifying the potential and opportunities of Social VR in the broadcast / video consumption landscape.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"793-807"},"PeriodicalIF":4.8,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998182","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}

引用次数: 0

STFF: Spatio-Temporal and Frequency Fusion for Video Compression Artifact Removal 用于视频压缩伪影去除的时空和频率融合

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-04-28 DOI: 10.1109/TBC.2025.3550018

Mingxing Wang;Yipeng Liao;Weiling Chen;Liqun Lin;Tiesong Zhao

{"title":"STFF: Spatio-Temporal and Frequency Fusion for Video Compression Artifact Removal","authors":"Mingxing Wang;Yipeng Liao;Weiling Chen;Liqun Lin;Tiesong Zhao","doi":"10.1109/TBC.2025.3550018","DOIUrl":"https://doi.org/10.1109/TBC.2025.3550018","url":null,"abstract":"Video compression artifact removal focuses on enhancing the visual quality of compressed videos by mitigating visual distortions. However, existing methods often struggle to effectively capture spatio-temporal features and recover high-frequency details, due to their suboptimal adaptation to the characteristics of compression artifacts. To overcome these limitations, we propose a novel Spatio-Temporal and Frequency Fusion (STFF) framework. STFF incorporates three key components: Feature Extraction and Alignment (FEA), which employs SRU for effective spatiotemporal feature extraction; Bidirectional High-Frequency Enhanced Propagation (BHFEP), which integrates HCAB to restore high-frequency details through bidirectional propagation; and Residual High-Frequency Refinement (RHFR), which further enhances high-frequency information. Extensive experiments demonstrate that STFF achieves superior performance compared to state-of-the-art methods in both objective metrics and subjective visual quality, effectively addressing the challenges posed by video compression artifacts. Trained model available: <uri>https://github.com/Stars-WMX/STFF</uri>.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"542-554"},"PeriodicalIF":3.2,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243633","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}

引用次数: 0

An End-to-End Spatially Scalable Light Field Image Compression Method 一种端到端空间可伸缩的光场图像压缩方法

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-04-18 DOI: 10.1109/TBC.2025.3553295

Jianjun Lei;Hao Li;Bo Peng;Bo Zhao;Nam Ling

{"title":"An End-to-End Spatially Scalable Light Field Image Compression Method","authors":"Jianjun Lei;Hao Li;Bo Peng;Bo Zhao;Nam Ling","doi":"10.1109/TBC.2025.3553295","DOIUrl":"https://doi.org/10.1109/TBC.2025.3553295","url":null,"abstract":"Recently, learning-based light field (LF) image compression methods have achieved impressive progress, while end-to-end spatially scalable LF image compression (SS-LFIC) has not been explored. To tackle this problem, this paper proposes an end-to-end spatially scalable LF compression network (SSLFC-Net). In the SSLFC-Net, a spatial-angular domain-specific enhancement layer coding strategy is designed to boost the coding performance of the enhancement layers (ELs). Specifically, by referencing domain-specific features, the ELs compress spatial features by predictive coding in the spatial domain to effectively remove inter-layer spatial redundancy, and reconstruct angular features by decoder-side generative method in the angular domain to strategically avoid angular compression. Particularly, to produce accurate spatial predictions and reconstruct high-quality LF images, an inter-layer spatial prediction module and a spatial-angular context-aware reconstruction module are presented to collaboratively promote EL compression. Experiments show that the proposed SSLFC-Net effectively supports spatial scalability and achieves state-of-the-art rate-distortion performance.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"570-580"},"PeriodicalIF":3.2,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243678","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}

引用次数: 0

Environment Information Enhanced Neural Adaptive Bitrate Video Streaming for Intercity Railway 城际铁路环境信息增强神经自适应比特率视频流

IF 4.8 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-04-15 DOI: 10.1109/TBC.2025.3559002

Liuchang Yang;Guanghua Liu;Shuo Li;Jintang Zhao;Tao Jiang

{"title":"Environment Information Enhanced Neural Adaptive Bitrate Video Streaming for Intercity Railway","authors":"Liuchang Yang;Guanghua Liu;Shuo Li;Jintang Zhao;Tao Jiang","doi":"10.1109/TBC.2025.3559002","DOIUrl":"https://doi.org/10.1109/TBC.2025.3559002","url":null,"abstract":"Intercity railways are vital to modern transportation systems, providing high-speed and efficient connections between cities. With the increasing demand for onboard entertainment and real-time monitoring systems, ensuring high Quality of Experience (QoE) video transmission has become a critical challenge. The unique characteristics of intercity railways, such as predictable railway schedules, spatial routes, and passenger-induced tidal effects, offer significant opportunities for optimizing video transmission performance. However, existing video streaming solutions must fully leverage these characteristics, resulting in inefficient bandwidth utilization, unstable video quality, and frequent interruptions caused by rapid train velocity, frequent handovers, and fluctuating network loads. This paper proposes an Environmental Information Enhanced adaptive video streaming (EIE-ABR) scheme that integrates environmental information with advanced techniques to address these challenges. Firstly, the scheme employs Deep Reinforcement Learning (DRL) to model the dynamic relationship between train speed and base station distance, enabling proactive bitrate adjustments in response to fluctuating network conditions. Secondly, EIE-ABR uses seasonal trend decomposition (STL) to capture throughput variations driven by periodic patterns, such as railway schedules and tidal effects, as well as abrupt disruptions from handovers or link failures. By combining DRL with STL, EIE-ABR achieves accurate throughput prediction and adapts effectively to the highly dynamic intercity railway environment. Simulation results show that EIE-ABR outperforms existing ABR algorithms, achieving an 11.22% improvement in average QoE reward.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 3","pages":"849-861"},"PeriodicalIF":4.8,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998288","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}

引用次数: 0

Gray-Mapped NOM-Enhanced SFN: A Broadcast and Broadband Converged Transmission Solution in LTE-Based 5G Broadcast 灰度映射nomo增强SFN：基于lte的5G广播中广播与宽带融合传输的解决方案

IF 3.2 1区计算机科学

IEEE Transactions on Broadcasting Pub Date : 2025-04-14 DOI: 10.1109/TBC.2025.3553318

Haoyang Li;Dazhi He;Yin Xu;Kewu Peng;Yunfeng Guan;Wenjun Zhang

{"title":"Gray-Mapped NOM-Enhanced SFN: A Broadcast and Broadband Converged Transmission Solution in LTE-Based 5G Broadcast","authors":"Haoyang Li;Dazhi He;Yin Xu;Kewu Peng;Yunfeng Guan;Wenjun Zhang","doi":"10.1109/TBC.2025.3553318","DOIUrl":"https://doi.org/10.1109/TBC.2025.3553318","url":null,"abstract":"Broadcast and broadband converged transmission has emerged as a prominent research focus within broadcast technology. Abundant corresponding studies have been conducted in traditional terrestrial broadcast and 3GPP unicast systems. However, due to issues like system compatibility, traditional terrestrial broadcasts usually reveal insufficient flexibility in transmitting broadband services, and conventional unicast systems always perform inefficiently in delivering broadcast services in scenarios of converged transmission. In addition, as the current Non-Orthogonal Multiplexing (NOM) scheme employed in converged transmission usually does not comply with the Gray-mapping rule, the required codeword-level Successive Interference Cancellation (SIC) algorithm makes the Enhanced Layer (EL) data share the same processing delay as the Core Layer (CL) one, which restricts the variety of EL services. This paper focuses on the physical layer technologies of converged transmission in the 3GPP LTE-based 5G Broadcast system. Due to the inherent good compatibility with both broadcast and broadband systems, LTE-based 5G Broadcast has great potential in realizing the converged transmission of broadcast and broadband. In addition, a novel converged transmission scheme enhanced by Gray-mapped NOM is proposed in this paper, and the corresponding networking architecture, frame structure, transmitting processing, and receiving algorithms are put forward. By significantly improving the performance of the non-SIC receiving algorithm, the proposed Gray-mapped NOM-enhanced SFN (GNeSFN) scheme enables the EL customized services and the CL broadcast services to have processing delays independent from each other, bringing more flexibility to converged transmission. Link-level simulations are carried out with different system configurations and multiple channel scenarios, verifying the effectiveness and feasibility of the proposed scheme.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 2","pages":"426-438"},"PeriodicalIF":3.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144243675","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}

引用次数: 0