我国新一代无线数字电视系统的构建

doi:10.16183/j.cnki.jsjtu.2018.10.015

摘要/Abstract

摘要： 超高清、网络融合与内容关联已成为全球广播电视技术发展的新趋势.为了主动应对视听媒体消费模式和传播模式变革，构建我国新一代数字电视广播标准体系将有效引导主流文化媒体的创新发展，加快整机制造产业的升级换代.介绍了今年制订完成的美国新一代无线数字电视广播标准(ATSC 3.0)的研制历程和技术特点，以及正在制订之中的全球第五代移动通信技术(5G)标准的进展，并结合我国国情提出新一代无线数字电视广播的发展需求、发展方向以及技术重点建议.

关键词: 无线数字电视, ATSC 3.0, 交互广播, 第五代移动通信技术(5G), 融合

Abstract: Ultra-high definition, network convergence and content association have become new trends in the development of global broadcasting and television technology. In order to actively respond to changes in the consumption patterns of audio-visual media and changes in the mode of communication, the establishment of a new generation digital television broadcasting standard system in China will effectively guide the innovation and development of mainstream cultural media and accelerate the upgrading of the entire machine manufacturing industry. To this end, this article describes the development history and technical characteristics of the US new generation wireless digital television broadcasting standard (ATSC 3.0) that was developed this year, and the current development of global fifth-generation mobile communication technology (5G) standard that is being worked out. Combining China’s national conditions, this article proposed the development needs, development directions, and key technical proposals for the new generation wireless digital TV broadcasting in China.

Key words: wireless digital TV, ATSC 3.0, interactive broadcast, the fifth-generation mobile communication technology (5G), convergence

中图分类号:

TN 949.1

张文军，管云峰，何大治，徐异凌，徐胤. 我国新一代无线数字电视系统的构建[J]. 上海交通大学学报, 2018, 52(10): 1267-1272.

ZHANG Wenjun,GUAN Yunfeng,HE Dazhi,XU Yiling,XU Yin. Construction of a New Generation of Wireless Digital TV System in China[J]. Journal of Shanghai Jiao Tong University, 2018, 52(10): 1267-1272.

参考文献

［1］EN E. 302 755 V1.3.1. Digital Video Broadcasting (DVB)；Frame structure channel coding and modulation for a second generation digital terrestrial television broadcasting system (DVB-T2)［S］. Geneva, August, 2012, 4. ［2］ATSC Physical Layer Protocol Standard［S］. Document A/322, Adv. Television Syst. Committee. Washington, DC, USA, 2017. ［3］何大治, 赵康, 徐异凌, 等. ATSC 3.0关键技术介绍［J］. 电视技术, 2015, 39(16): 105-114. HE Dazhi, ZHAO Kang, XU Yiling, et al. ATSC 3.0 Key Technology Introduction［J］. Vedio Engineering, 2015, 39(16): 105-114. ［4］PANWAR N, SHARMA S, SINGH A K. A survey on 5G: The next generation of mobile communication［J］. Physical Communication, 2016, 18: 64-84. ［5］GB 20600—2006. 数字电视地面广播传输系统帧结构、信道编码和调制［S］. 2006. GB 20600—2006. Framing structure, channel coding and modulation for digital television terrestrial broadcasting system［S］. 2006. ［6］冯景锋, 张文军, 管云峰, 等.我国新一代地面数字电视标准体系建设构想［J］. 广播与电视技术, 2018, 45(3): 32-36. FENG Jingfeng, ZHANG Wenjun, GUAN Yunfeng, et al. China’s new generation of digital TV standard system construction conception［J］. Radio & TV Broadcast Engineering, 2018, 45(3): 32-36. ［7］FAY L. 美国新一代数字电视ATSC 3.0标准技术体系S32物理层介绍［J］. 广播与电视技术, 2015, 42(s2): 20-37. FAY L. Introduction of new generation digital TV ATSC 3.0 standard technology system S32 physical layer［J］. Radio & TV Broadcast Engineering, 2015, 42(s2): 20-37. ［8］赵淼, 张文军, 何大治, 等. 数字电视上行回传信道关键技术介绍［J］. 广播与电视技术, 2015(s2): 70-74. ZHAO Miao, ZHANG Wenjun, HE Dazhi, et al. Introduction of digital TV uplink return channel key technology［J］. Radio & TV Broadcast Engineering, 2015(s2): 70-74. ［9］IMT-2020 (5G) 推进组. 5G 概念白皮书［R］. 2015. IMT-2020 (5G) Promotion Group. White paper on 5G concept［R］. 2015. ［10］BIATEK T, HAMIDOUCHE W, TRAVERS J F, et al. Optimal Bitrate Allocation in the Scalable HEVC Extension for the Deployment of UHD Services［J］. IEEE Transactions on Broadcasting, 2016, 62(4): 826-841. ［11］SU R, WANG L, LIU X. Multimodal learning using 3D audio-visual data for audio-visual speech recognition［C］//International Conference on Asian Language Processing. IEEE, 2018: 40-43.

[1]	范宏, 魏心武, 贾庆山, 罗佳怡. 能源-交通融合下电-气-热多能系统协同优化调度方法[J]. 上海交通大学学报, 2026, 60(2): 211-223.
[2]	丛潇雨, 杨甲一, 单世臣, 左倩. 基于多源信息融合的目标识别方法研究[J]. 空天防御, 2026, 9(1): 12-19.
[3]	. 触觉辅助导航车辆：增强盲区和透明物体场景中的障碍物检测[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(1): 167-175.
[4]	. 机场飞行区域空域入侵物视觉检测[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(1): 176-186.
[5]	. 基于记忆球的混合拓扑地图融合[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(1): 130-142.
[6]	. 用于工业机器人关节跨设备故障检测的混合学习模型[J]. J Shanghai Jiaotong Univ Sci, 2026, 31(1): 82-98.
[7]	张志远, 胡冀苏, 张跃跃, 钱旭升, 周志勇, 戴亚康. 注意力引导多任务学习的前列腺癌盆腔淋巴结转移预测[J]. 上海交通大学学报, 2025, 59(8): 1216-1224.
[8]	. CSC-YOLO：一种铜板带表面缺陷检测的图像识别模型[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(5): 1037-1049.
[9]	. 基于多注意力机制的轻量化人体姿态估计[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(5): 899-910.
[10]	. 基于多尺度融合和自适应标签相关性的多标签图像分类模型[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(5): 889-898.
[11]	. CT-MFENet：基于全局-局部特征融合的用于视网膜血管分割的上下文Transformer和多尺度特征提取网络[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 668-682.
[12]	周添龙, 姚方競, 饶卫雄. 部分已知状态空间模型下的目标状态估计算法[J]. 空天防御, 2025, 8(3): 111-122.
[13]	薛昂, 姜恩宇, 张文涛, 林顺富, 米阳. 基于窗口自注意力网络与YOLOv5融合的输电线路通道异物检测[J]. 上海交通大学学报, 2025, 59(3): 413-423.
[14]	. 基于改进加权融合的胶囊内镜肠道内壁图像拼接方法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 535-544.
[15]	王可, 刘奕阳, 杨杰, 鲁爱国, 李哲, 徐明亮. 基于自适应特征增强和融合的舰载机着舰拉制状态识别[J]. 上海交通大学学报, 2025, 59(2): 274-282.