IEEE Transactions on Broadcasting最新文献

{"title":"Architectural Challenges and Solutions in Multimedia IoT Over 5G Networks","authors":"Claudia Rinaldi;Alex Piccioni;Carlo Centofanti;Andrea Marotta;Piergiuseppe Di Marco;Fabio Graziosi","doi":"10.1109/TBC.2025.3639764","DOIUrl":"https://doi.org/10.1109/TBC.2025.3639764","url":null,"abstract":"Multimedia Internet of Things (M-IoT) refers to the convergence of the Internet of Things (IoT) with multimedia services, describing networks of interconnected smart devices capable of capturing, processing, and transmitting rich data streams, including video, audio, and immersive content. The evolution of M-IoT applications is driving the need for multilayer architectures in which dedicated functional layers cooperate to manage data processing, content delivery, and device coordination. This paper provides a comprehensive analysis of the critical challenges associated with M-IoT deployments, such as bandwidth management, reliability, interoperability, security, and energy efficiency. It also presents a systematic description of a multilayer architecture for organizing M-IoT services, mapping functional requirements to enabling technologies. Finally, a qualitative and quantitative comparative evaluation of alternative network solutions is conducted. Non-public networking emerges as particularly effective for mission-critical applications, whereas 5G Multicast/Broadcast Service demonstrates significant advantages for large-scale multimedia content distribution scenarios.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"46-61"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11301895","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148512476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discrete Reflection Coefficients RIS for Interference Suppression in Multicast Transmissions","authors":"Linsong Du;Qingpeng Liang;Pingzhi Fan;Zheng Ma","doi":"10.1109/TBC.2025.3609082","DOIUrl":"https://doi.org/10.1109/TBC.2025.3609082","url":null,"abstract":"Reconfigurable Intelligent Surface (RIS) introduces a novel strategy for mitigating channel interference. However, the assumption of continuous reflection coefficients (CRC) in most existing studies on interference neutralization utilizing RIS is unrealistic due to hardware constraints. This work centers on interference neutralization in RIS-supported multicast transmission with the more common discrete reflection coefficients (DRC). Here, an RIS comprised of reflectors is utilized to improve the multicast channel and diminish the interference channel by designing DRC. In this context, a problem that maximizes the signal-to-interference-plus-noise ratio is defined as the attainable rate maximization by choosing the feasible DRC and a beamforming vector. First, an alternating optimization approach iteratively updates the DRC and beamforming vector. It combines Gaussian randomization with bisection search to solve feasibility problems, neutralizing interference by adjusting the interference channel without cooperator involvement. Then, for RIS-assisted multicast under millimeter-wave interference, the asymptotic behaviors of achievable rate is analyzed via the Toeplitz structure of channel covariance matrices. Last, this demonstrates that the RIS can greatly enhance the multicast rate in the presence of interference.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"130-143"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148515270","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}

{"title":"Macropixel-Constrained Collocated Positions and Neighbors Motion Search for Plenoptic 2.0 Video Coding","authors":"Vinh Van Duong;Thuc Nguyen Huu;Jonghoon Yim;Byeungwoo Jeon","doi":"10.1109/TBC.2026.3651185","DOIUrl":"https://doi.org/10.1109/TBC.2026.3651185","url":null,"abstract":"Plenoptic 2.0 cameras enable high-resolution light field acquisition by incorporating focused optical designs that differ fundamentally from traditional plenoptic 1.0 systems. These structural differences introduce unique motion characteristics that challenge existing motion estimation (ME) algorithms. In this paper, we present comprehensive statistical analysis on real-world captured datasets to examine the primary differences in motion vector distributions among conventional, plenoptic 1.0, and plenoptic 2.0 videos. Based on the analysis, a novel fast ME algorithm is designed for efficient plenoptic 2.0 video coding. It performs a joint search over macropixel collocated positions (MCPs) and their neighboring regions to effectively accommodate the large motion deviation characteristic of plenoptic 2.0 video. To further improve computational efficiency, a macropixel-level diamond search pattern (MLDSP) is introduced to benefit from the center-biased motion-vector distribution at the macropixel resolution. Additionally, a fast MCP neighbor search is employed to restrict the search only to the top <inline-formula> <tex-math>$K$ </tex-math></inline-formula> number of MCPs with the lowest distortion costs. Experimental results demonstrate that the proposed method achieves better bitrate savings and reduced computational complexity compared to existing ME techniques.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"182-192"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148509543","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}

{"title":"IRS-Assisted Joint Broadcast/Multicast Resource Allocation and Cooperative Perception Optimization for 6G V2X Networks","authors":"Fei Qi;Qian Huang;Yinan Wang;Pingping Lin;Chunxia Hu;Xuan Shi","doi":"10.1109/TBC.2025.3611640","DOIUrl":"https://doi.org/10.1109/TBC.2025.3611640","url":null,"abstract":"Aiming at the coexistence challenges of highly reliable broadcast/multicast communication and high-precision cooperative sensing in 6G vehicular networking, this paper proposes an IRS-enhanced joint optimization framework. First, an IRS-assisted millimeter-wave-terahertz heterogeneous network architecture is constructed to reconfigure multi-vehicle communication links through dynamically programmable reflective units to solve the signal occlusion and interference problems in traditional multicast scenarios; second, a cooperative sensing task modeling method based on GAT is designed to fuse LiDAR point-cloud data and camera information into spatio-temporal sensing features to drive dynamic resource allocation demand; finally, the HFRL algorithm is proposed to jointly optimize the IRS phase matrix, broadcast spectrum allocation, computational offloading strategy and perception task priority. The simulation results show that the sensing accuracy has increased from 68.5% of the baseline to 90.5%, the URLLC reliability is 99.999%, and the spectral efficiency is 5.2 bps/Hz.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"106-116"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148514734","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}

{"title":"Quality and Energy-Aware Cooperative Distributed Solution for Mobile Rich Media Delivery in Wireless Heterogeneous Environments","authors":"John Monks;Anderson Augusto Simiscuka;Gabriel-Miro Muntean","doi":"10.1109/TBC.2025.3609056","DOIUrl":"https://doi.org/10.1109/TBC.2025.3609056","url":null,"abstract":"Mobile video traffic is rapidly growing, putting significant pressure on current heterogeneous wireless networks. Common data is traditionally requested by multiple users from server or cache devices. This results in the same data being sent across the network multiple times causing unnecessary congestion. This paper proposes a cooperative solution which allows neighboring devices to share locally content that was previously received by interested peers. In this paper, the Mobile-aware Quality-oriented Cooperative Multimedia Delivery Solution (MENCO) is described, which enables peer devices to identify neighboring host devices which could act as content providers, while considering their own mobility. Simulated testing shows that MENCO is capable of identifying the most suitable hosts while travelling at different speeds and maintaining a suitable quality level by adapting the content to the existing network conditions. MENCO outperforms state-of-the-art alternative solutions by maintaining good quality levels of service with increasing speeds in a mobile environment.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"87-95"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11185237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148513585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Frequency-Domain Feature-Based Self-Interference Cancellation Method for In-Band Full-Duplex Communications in Inter-Tower Communication Networks","authors":"Ning Yang;Haoyang Li;Hao Ju;Yin Xu;Dazhi He;Zhiyong Chen;Yiyan Wu","doi":"10.1109/TBC.2026.3651191","DOIUrl":"https://doi.org/10.1109/TBC.2026.3651191","url":null,"abstract":"As a hot research topic for next-generation broadcasting systems, enhancements to In-band Distribution Links (IDL) and the Inter-Tower Communications Network (ITCN) have attracted significant attention. With its significant advantages in spectrum efficiency and inter-tower wireless connectivity, the In-Band Full-Duplex (IBFD) technique has become a much-needed solution for Single-Frequency Network (SFN) signal backhaul, network synchronization and control, and emergency alert information distribution. However, the self-interference resulting from the local transmitter signal loop-back is the primary bottleneck impacting the performance of the IBFD technique, and the non-linear distortion caused by the high-power amplifier further complicates the cancellation of the self-interference. This paper proposes a full-duplex self-interference cancellation (SIC) method. Based on radio frequency (RF) reference signals and short-term learning via phase search and tracking, combined with prior knowledge of Advanced Television Standards Committee (ATSC) 3.0 signals, this method achieves good SIC performance with low complexity. Simulation results show that the proposed method achieves a good SIC gain of up to 46 dB in digital domain cancellation. With analog pre-cancellation and other co-channel interference mitigation techniques, 60+ dB total SIC cancellation can be achieved for ITCN applications. Meanwhile, the simulation results also show that this method can effectively address phase jitter and signal distortion caused by the distributed parameters of hardware devices and environmental variations.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"96-105"},"PeriodicalIF":5.9,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148514270","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}

{"title":"Light Field Referring Segmentation: A Benchmark and an LLM-Based Approach","authors":"Shishun Tian;Qian Xu;He Gui;Ting Su;Yan Li;Qiong Wang","doi":"10.1109/TBC.2026.3659013","DOIUrl":"https://doi.org/10.1109/TBC.2026.3659013","url":null,"abstract":"Referring image segmentation (RIS) is a challenging task that requires models to segment objects based on natural language descriptions. Existing RIS models have limited leverage of geometric information, resulting in multimodal mismatch between language and vision. In contrast to conventional 2D images, light field imaging gathers rays emitted from light sources in all directions. This unique characteristic enriches the comprehensive understanding of scenes, which provides us with a new way to optimize RIS. In this paper, we propose the first light field referring segmentation dataset, which contains rich occluded objects and depth-referring descriptions. Afterward, we benchmark the performance of existing 2D referring image segmentation methods on the proposed dataset. The results revealed that these methods show limited efficacy in occluded scenes and depth-based descriptions of scenes. To address this issue, we propose a novel framework, termed LFLLM, for light field referring segmentation. Specifically, we propose a Center Angular Aggregation Module that warps the views adjacent to the central view to prevent feature occlusion caused by viewpoints misalignment, and a Depth Convergence Module that adds a depth token into the LLMs to leverage the depth information in the light field. Extensive experiments demonstrate that our approach outperforms the current state-of-the-art methods. The dataset and code are available at <uri>https://github.com/ShishunTian/LFLLM-TBC2026</uri>","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"361-372"},"PeriodicalIF":4.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362447","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}

{"title":"Compression Efficiency and Picture Quality Assessment of Broadcast HDR Videos With and Without Film-Grain","authors":"Gosala Kulupana;Jayasingam Adhuran;Andrew Cotton","doi":"10.1109/TBC.2026.3651199","DOIUrl":"https://doi.org/10.1109/TBC.2026.3651199","url":null,"abstract":"Along with the ever-growing popularity of information rich video formats such as High Dynamic Range (HDR), Wide Colour Gamut (WCG) and Ultra High Definition (UHD), the need for efficient distribution of such video content has become crucially important. To this end, video compression plays an important role in reducing the bitrate requirements by, for example, up to two orders of magnitude. This work first investigates the performance of state-of-the-art video compression standards with the help of a large-scale subjective study. The study for the first time provides some useful insight into the types of artifacts that are introduced by the video codecs on HDR content with film-grain. The evaluation of the pictures generated by the video codecs is also a crucial aspect in the video distribution pipeline. For this purpose, this paper further provides an HDR picture quality metric which is based on an existing Standard Dynamic Range (SDR) picture quality metric called Detail Loss Metric (DLM). The proposed metric includes several novel features to make it suitable for assessing compression artifacts of HDR content with and without film-grain. They are 1) A Just Noticeable Difference (JND) based perceptual weighting function that captures the non-linearity in the HDR signal. 2) An entropy masking module to capture the impact of film-grain characteristics. 3) A contrast masking operation based on previous work, to better represent the impact of local visual masking. Performance of the proposed method and several state-of-the-art HDR and SDR quality metrics is evaluated on two large-scale datasets using three commonly used accuracy measures: Pearson Linear Correlation Coefficient (PLCC), Spearman’s Rank Correlation Coefficient (SRCC) and Root Mean Square Error (RMSE). A further measure of how reliably a given metric can represent the user perception is also introduced. The experimental results indicate superior performance of the proposed method, demonstrating a PLCC score of more than 94% and similar good performance scores for other accuracy measures.","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"72 1","pages":"317-328"},"PeriodicalIF":4.8,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147362477","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}

{"title":"IEEE Transactions on Broadcasting Publication Information","authors":"","doi":"10.1109/TBC.2025.3640759","DOIUrl":"https://doi.org/10.1109/TBC.2025.3640759","url":null,"abstract":"","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"C2-C2"},"PeriodicalIF":4.8,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11302006","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2025 Scott Helt Memorial Award for the Best Paper Published in IEEE Transactions on Broadcasting","authors":"","doi":"10.1109/TBC.2025.3640887","DOIUrl":"https://doi.org/10.1109/TBC.2025.3640887","url":null,"abstract":"","PeriodicalId":13159,"journal":{"name":"IEEE Transactions on Broadcasting","volume":"71 4","pages":"1108-1110"},"PeriodicalIF":4.8,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11302029","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145766204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}