通信学报 ›› 2022, Vol. 43 ›› Issue (7): 189-202.doi: 10.11959/j.issn.1000-436x.2022140
张海君, 陈安琪, 李亚博, 隆克平
修回日期:
2022-05-30
出版日期:
2022-07-25
发布日期:
2022-06-01
作者简介:
张海君(1985- ),男,辽宁朝阳人,博士,北京科技大学教授、博士生导师,主要研究方向为6G移动通信、人工智能与无线网络、机器学习与大数据等基金资助:
Haijun ZHANG, Anqi CHEN, Yabo LI, Keping LONG
Revised:
2022-05-30
Online:
2022-07-25
Published:
2022-06-01
Supported by:
摘要:
首先,简要介绍了移动通信网络发展历程及社会需求。其次,从通信的频谱、维度、赋能以及范式角度出发,介绍了6G网络中太赫兹通信、空天地海一体化网络、人工智能以及语义通信四项关键技术。围绕四项关键技术分析了近年来的相关研究,对其典型场景模型、覆盖方案、技术原理等进行了总结,并提出了各技术未来发展中要解决的问题。最后,简要讨论了6G网络的其他候选技术,包括通信感知一体化、智能超表面与新材料、区块链、数字孪生以及确定性网络技术等。
中图分类号:
张海君, 陈安琪, 李亚博, 隆克平. 6G移动网络关键技术[J]. 通信学报, 2022, 43(7): 189-202.
Haijun ZHANG, Anqi CHEN, Yabo LI, Keping LONG. Key technologies of 6G mobile network[J]. Journal on Communications, 2022, 43(7): 189-202.
表1
不同太赫兹场景下的典型信道模型"
文献 | 通信场景 | 采用方法 | 考虑特征 | 信道模型 |
文献[ | 纳米通信 | 辐射传输理论 | 分子吸收 | ①分子吸收衰减模型: |
②分子吸收噪声模型: | ||||
其中,f 为电磁波频率;d 为路径长度;Pi和P0分别为入射功率和辐射功率;τ为介质透射率;k(f)为介质吸收系数,其取决于介质的成分,即沿通道发现的特定分子混合物 | ||||
文献[ | 短距通信 | 时域频域分析 | 分子吸收 | 基于文献[ |
文献[ | 纳米通信 | 瑞利散射理论 | 分子吸收粒子散射 | 粒子散射衰减模型: |
其中,f 为电磁波频率,d 为路径长度, | ||||
文献[ | 短距通信、人体通信 | — | 分子吸收 | 分子吸收正态分布衰减模型: |
其中, | ||||
文献[ | 室内通信 | 射线追踪技术 | 分子吸收、散射、衍射 | 综合了LoS、反射、散射和衍射路径的多径信道模型 |
表2
现有的不同维度通信方案总结"
文献 | 通信维度 | 研究内容 | 技术方案 |
文献[ | 天地 | 星地模型 | ①模型X。卫星和地面基站分别与各自的用户通信,共享相同的频谱资源。其中共有2条链路:卫星链路为卫星到卫星终端,地面链路为地面基站到地面移动终端 |
②模型L。卫星通过中继与用户通信,其中,只有一条链路,即卫星到中继再到用户 | |||
③模型V。卫星与地面基站合作为一个公共用户服务。其中共有2条链路:卫星链路和地面链路,都指向公共用户 | |||
文献[ | 空地 | 最小化UAV | ①应用图论技术提出了一种基于飞行-悬停-飞行策略的有效解决方案。 |
任务完成时间 | ②基于连续凸逼近技术提出了一种迭代UAV轨迹设计方案,用于给出UAV和地面基站的关联方案 | ||
文献[ | 天海 | 优化系统容量 | ①考虑海上用户配备多个定向天线,并用中继协作技术将卫星信号重传给其他用户,提出了一种协作接入算法来选择中继用户 |
②提出了一种功率分配算法,分别对卫星和中继节点进行功率分配,并根据天线方向图模型和自动识别系统来估计群间干扰 | |||
文献[ | 空天地 | 中断性能分析 | ①考虑高空平台和地面基站作为中继构建空天地一体化框架,对协作信道进行建模,包括空天链路、空地链路和天地链路 |
②从链路角度分析了系统中断性能。考虑 5 种链路:卫星-空中平台、卫星-基站、空中平台-基站、空中平台-用户和基站-用户,近似了以上链路的中断概率和渐近中断概率的表达式 | |||
文献[ | 空天地海 | 海上通信增强 | ①提出了一种基于移动边缘计算的空天地一体化网络辅助海洋通信网络架构 |
②分析了如何利用移动边缘计算和区块链等技术来增强海洋网络通信 |
表3
基于AI技术的资源管理方案"
文献 | 类别 | 学习算法/模型 | 面向问题 | 函数模型 |
文献[ | 深度强化学习 | DQN+RC | 动态频谱接入 | 总折扣奖励函数为 |
其中,γ∈[0,1]为折扣率,t为时隙,rl(t+1)为第l个次要用户的奖励函数, | ||||
文献[ | 深度强化学习 | LSTM DQN | 多路接入控制 | 总折扣奖励函数为 |
其中,γ∈(0,1) 为折扣率,F 为带宽,P为用户的传输功率,Hi(k+1) 为信道状态信息, | ||||
RC | 能量收集预测 | 总折扣预测损失函数为 | ||
其中,Sk+1为系统状态, | ||||
文献[ | 半监督学习 | 协同训练 | 子信道分配 | 子信道分配损失函数为 |
其中, | ||||
深度强化学习 | DNN | 功率分配 | 功率分配损失函数为 | |
其中,R为系统总速率,U 为总传输功率, |
表4
现有的典型语义通信研究方案对比"
文献 | 通信信源 | 研究内容 | 学习方法 | 技术方案 |
文献[ | 文本 | 编解码方案 | 深度学习 | ①提出一种用于文本的联合信源和信道编码的神经网络架构 |
②基于该架构训练一个联合的信源和信道编码器和解码器,其中解码器可以输出一个不同的句子来保留其语义信息内容 | ||||
文献[ | 图像 | 编解码方案 | 卷积神经网络 | ①提出一种用于无线图像传输的联合信源和信道编码技术,将输入图像像素映射到信道输入符号 |
②编码器和解码器功能被建模为互补的卷积神经网络,并在数据集上联合训练以最小化重建图像的均方误差 | ||||
文献[ | 图像 | 编解码方案 | 深度神经网络 | 提出一种针对图像检索任务的基于DNN的联合信源和信道编码技术,提高端到端的准确性,简化和加速编码操作 |
文献[ | 图像 | 编解码方案 | 卷积神经网络 | ①将无噪声或有噪声的信道输出反馈纳入传输系统,以提高接收器的重构质量 |
②提出了一种基于自动编码器的联合信源和信道编码方案,其利用了信道输出反馈,在固定长度传输的端到端重构质量方面,或在可变长度传输的平均时延方面,提供了较大改进 | ||||
文献[ | 视频 | 编解码方案 | 卷积神经网络 | ①编码器定位文本信息,每个字符的语义通过卷积神经网络提取并进行预测编码,用标准的编解码器压缩背景视频,并与文字语义一起传送给接收方 |
②在解码器端,使用解码后的语义合成文本,叠加在解码后的剩余视频上,恢复原始帧 | ||||
文献[ | 文本 | 系统设计 | 深度迁移学习 | ①提出一种新的支持DL的语义通信系统DeepSC,考虑了联合信源和信道编码,以从文本中提取语义信息 |
②利用深度迁移学习来加速模型的重新训练,以保证 DeepSC 适用于不同的通信环境 | ||||
文献[ | 文本 | 系统设计 | 深度学习 | ①针对物联网通信场景提出了一个基于 DL 的精简分布式语义通信系统L-DeepSC,用于低复杂度的文本传输 |
②通过分析信道状态信息在衰落信道上对 DL 模型训练的影响,提出了一种信道状态信息辅助训练处理方法,以减少衰落信道对传输的影响 | ||||
文献[ | 语音 | 系统设计 | 深度学习 | ①提出一种语音信号语义通信系统DeepSC-S,考虑联合信源和信道编码 |
②利用SE网络学习并提取基本语音语义信息,提高信号恢复的准确性 |
[1] | 张平, 牛凯, 田辉 ,等. 6G 移动通信技术展望[J]. 通信学报, 2019,40(1): 141-148. |
ZHANG P , NIU K , TIAN H ,et al. Technology prospect of 6G mobile communications[J]. Journal on Communications, 2019,40(1): 141-148. | |
[2] | ITU-R. IMT traffic estimates for the years 2020 to 2030:M.2370-0[S]. 2015. |
[3] | 尤肖虎, 尹浩, 邬贺铨 . 6G 与广域物联网[J]. 物联网学报, 2020,4(1): 3-11. |
YOU X H , YIN H , WU H Q . On 6G and wide-area IoT[J]. Chinese Journal on Internet of Things, 2020,4(1): 3-11. | |
[4] | ZHANG H J , ZHANG H S , LIU W ,et al. Energy efficient user clustering,hybrid precoding and power optimization in terahertz MIMO-NOMA systems[J]. IEEE Journal on Selected Areas in Communications, 2020,38(9): 2074-2085. |
[5] | IMT-2030 (6G) 推进组. 太赫兹通信技术研究报告[R]. 2021. |
IMT-2030 (6G) Promotion Group. Research report of terahertz com-munication technology[R]. 2021. | |
[6] | ITU-R. Attenuation by atmospheric gases and related effects:P.676-12[S]. 2019. |
[7] | ITU-R. Specific attenuation model for rain for use in prediction methods:P.838[S]. 2005. |
[8] | JORNET J M , AKYILDIZ I F . Channel modeling and capacity analysis for electromagnetic wireless nanonetworks in the terahertz band[J]. IEEE Transactions on Wireless Communications, 2011,10(10): 3211-3221. |
[9] | 谢莎, 李浩然, 李玲香 ,等. 太赫兹通信技术综述[J]. 通信学报, 2020,41(5): 168-186. |
XIE S , LI H R , LI L X ,et al. Survey of terahertz communication technology[J]. Journal on Communications, 2020,41(5): 168-186. | |
[10] | NIE S , AKYILDIZ I F . Channel modeling and analysis of inter-small-satellite links in terahertz band space networks[J]. IEEE Transactions on Communications, 2021,69(12): 8585-8599. |
[11] | FRICKE A , REY S , PENG B ,et al. TG3d channel modelling document (CMD):IEEE P802.15[S]. 2016. |
[12] | 张平, 陶运铮, 张治 . 5G 若干关键技术评述[J]. 通信学报, 2016,37(7): 15-29. |
ZHANG P , TAO Y Z , ZHANG Z . Survey of several key technologies for 5G[J]. Journal on Communications, 2016,37(7): 15-29. | |
[13] | SHEIKH F , ZANTAH Y , BEN M I ,et al. Scattering and roughness analysis of indoor materials at frequencies from 750 GHz to 1.1 THz[J]. IEEE Transactions on Antennas and Propagation, 2021,69(11): 7820-7829. |
[14] | JANSEN C , PIESIEWICZ R , MITTLEMAN D ,et al. The impact of reflections from stratified building materials on the wave propagation in future indoor terahertz communication systems[J]. IEEE Transactions on Antennas and Propagation, 2008,56(5): 1413-1419. |
[15] | PIESIEWICZ R , JANSEN C , MITTLEMAN D ,et al. Scattering analysis for the modeling of THz communication systems[J]. IEEE Transactions on Antennas and Propagation, 2007,55(11): 3002-3009. |
[16] | MA J J , SHRESTHA R , ZHANG W ,et al. Terahertz wireless links using diffuse scattering from rough surfaces[J]. IEEE Transactions on Terahertz Science and Technology, 2019,9(5): 463-470. |
[17] | JANSEN C , PRIEBE S , MOLLER C ,et al. Diffuse scattering from rough surfaces in THz communication channels[J]. IEEE Transactions on Terahertz Science and Technology, 2011,1(2): 462-472. |
[18] | SHEIKH F , GAO Y , KAISER T . A study of diffuse scattering in massive MIMO channels at terahertz frequencies[J]. IEEE Transactions on Antennas and Propagation, 2020,68(2): 997-1008. |
[19] | ZHANG H J , DUAN Y N , LONG K P ,et al. Energy efficient resource allocation in terahertz downlink NOMA systems[J]. IEEE Transactions on Communications, 2021,69(2): 1375-1384. |
[20] | LEMIC F , ABADAL S , TAVERNIER W ,et al. Survey on terahertz nanocommunication and networking:a top-down perspective[J]. IEEE Journal on Selected Areas in Communications, 2021,39(6): 1506-1543. |
[21] | LLATSER I , MESTRES A , ABADAL S ,et al. Time and frequency-domain analysis of molecular absorption in short-range terahertz communications[J]. IEEE Antennas and Wireless Propagation Letters, 2015,14: 350-353. |
[22] | KOKKONIEMI J , LEHTOM?KI J , UMEBAYASHI K ,et al. Frequency and time domain channel models for nanonetworks in terahertz band[J]. IEEE Transactions on Antennas and Propagation, 2015,63(2): 678-691. |
[23] | JAVED I T , NAQVI I H . Frequency band selection and channel modeling for WNSN applications using simplenano[C]// Proceedings of 2013 IEEE International Conference on Communications. Piscataway:IEEE Press, 2013: 5732-5736. |
[24] | CHEN Y , LI Y B , HAN C ,et al. Channel measurement and ray-tracing-statistical hybrid modeling for low-terahertz indoor communications[J]. IEEE Transactions on Wireless Communications, 2021,20(12): 8163-8176. |
[25] | PRIEBE S , JASTROW C , JACOB M ,et al. Channel and propagation measurements at 300 GHz[J]. IEEE Transactions on Antennas and Propagation, 2011,59(5): 1688-1698. |
[26] | KHALID N , AKAN O B . Wideband THz communication channel measurements for 5G indoor wireless networks[C]// Proceedings of 2016 IEEE International Conference on Communications. Piscataway:IEEE Press, 2016: 1-6. |
[27] | HAN C , BICEN A , AKYILDIZ I F . Multi-ray channel modeling and wideband characterization for wireless communications in the terahertz band[J]. IEEE Transactions on Wireless Communications, 2015,14(5): 2402-2412. |
[28] | PRIEBE S , KURNER T . Stochastic modeling of THz indoor radio channels[J]. IEEE Transactions on Wireless Communications, 2013,12(9): 4445-4455. |
[29] | WANG J , WANG C X , HUANG J ,et al. A general 3D space-time-frequency non-stationary THz channel model for 6G ultra-massive MIMO wireless communication systems[J]. IEEE Journal on Selected Areas in Communications, 2021,39(6): 1576-1589. |
[30] | 段瑞洋, 王景璟, 杜军 ,等. 面向“三全”信息覆盖的新型海洋信息网络[J]. 通信学报, 2019,40(4): 10-20. |
DUAN R Y , WANG J J , DU J ,et al. New marine information network for realizing all-coverage over sea[J]. Journal on Communications, 2019,40(4): 10-20. | |
[31] | 黄韬, 刘江, 汪硕 ,等. 未来网络技术与发展趋势综述[J]. 通信学报, 2021,42(1): 130-150. |
HUANG T , LIU J , WANG S ,et al. Survey of the future network tech-nology and trend[J]. Journal on Communications, 2021,42(1): 130-150. | |
[32] | FANG X R , FENG W , WEI T ,et al. 5G embraces satellites for 6G ubiquitous IoT:basic models for integrated satellite terrestrial networks[J]. IEEE Internet of Things Journal, 2021,8(18): 14399-14417. |
[33] | AN K , LIN M , JIAN O Y ,et al. Symbol error analysis of hybrid satellite-terrestrial cooperative networks with cochannel interference[J]. IEEE Communications Letters, 2014,18(11): 1947-1950. |
[34] | AN K , LIN M , LIANG T ,et al. Performance analysis of multi-antenna hybrid satellite-terrestrial relay networks in the presence of interference[J]. IEEE Transactions on Communications, 2015,63(11): 4390-4404. |
[35] | 李凤华, 殷丽华, 吴巍 ,等. 天地一体化信息网络安全保障技术研究进展及发展趋势[J]. 通信学报, 2016,37(11): 156-168. |
LI F H , YIN L H , WU W ,et al. Research status and development trends of security assurance for space-ground integration information network[J]. Journal on Communications, 2016,37(11): 156-168. | |
[36] | SU Y T , LIU Y Q , ZHOU Y Q ,et al. Broadband LEO satellite communications:architectures and key technologies[J]. IEEE Wireless Communications, 2019,26(2): 55-61. |
[37] | LAGUNAS E , SHARMA S K , MALEKI S ,et al. Resource allocation for cognitive satellite communications with incumbent terrestrial networks[J]. IEEE Transactions on Cognitive Communications and Networking, 2015,1(3): 305-317. |
[38] | ZHU X M , JIANG C X , KUANG L L ,et al. Energy efficient resource allocation in cloud based integrated terrestrial-satellite networks[C]// Proceedings of 2018 IEEE International Conference on Communications. Piscataway:IEEE Press, 2018: 1-6. |
[39] | ZHU X M , JIANG C X , KUANG L L ,et al. Non-orthogonal multiple access based integrated terrestrial-satellite networks[J]. IEEE Journal on Selected Areas in Communications, 2017,35(10): 2253-2267. |
[40] | CHRISTOPOULOS D , CHATZINOTAS S , OTTERSTEN B . Multicast multigroup precoding and user scheduling for frame-based satellite communications[J]. IEEE Transactions on Wireless Communications, 2015,14(9): 4695-4707. |
[41] | WANG L N , WU Y N , ZHANG H J ,et al. Resource allocation for NOMA based space-terrestrial satellite networks[J]. IEEE Transactions on Wireless Communications, 2021,20(2): 1065-1075. |
[42] | CAO H , SU Y T , ZHOU Y Q ,et al. QoS guaranteed load balancing in broadband multi-beam satellite networks[C]// Proceedings of IEEE International Conference on Communications. Piscataway:IEEE Press, 2019: 1-6. |
[43] | ZHANG H J , ZHANG J M , LONG K P . Energy efficiency optimization for NOMA UAV network with imperfect CSI[J]. IEEE Journal on Selected Areas in Communications, 2020,38(12): 2798-2809. |
[44] | MU X D , LIU Y W , GUO L ,et al. Non-orthogonal multiple access for air-to-ground communication[J]. IEEE Transactions on Communications, 2020,68(5): 2934-2949. |
[45] | HUA M , YANG L X , WU Q Q ,et al. 3D UAV trajectory and communication design for simultaneous uplink and downlink transmission[J]. IEEE Transactions on Communications, 2020,68(9): 5908-5923. |
[46] | JIANG X , WU Z L , YIN Z D ,et al. Power consumption minimization of UAV relay in NOMA networks[J]. IEEE Wireless Communications Letters, 2020,9(5): 666-670. |
[47] | LI Y B , ZHANG H J , LONG K P . Joint resource,trajectory,and artificial noise optimization in secure driven 3-D UAVs with NOMA and imperfect CSI[J]. IEEE Journal on Selected Areas in Communications, 2021,39(11): 3363-3377. |
[48] | LI Y B , ZHANG H J , LONG K P ,et al. Joint resource allocation and trajectory optimization with QoS in UAV-based NOMA wireless net works[J]. IEEE Transactions on Wireless Communications, 2021,20(10): 6343-6355. |
[49] | WANG H M , ZHANG X . UAV secure downlink NOMA transmissions:a secure users oriented perspective[J]. IEEE Transactions on Communications, 2020,68(9): 5732-5746. |
[50] | YE J , DANG S P , SHIHADA B ,et al. Space-air-ground integrated networks:outage performance analysis[J]. IEEE Transactions on Wireless Communications, 2020,19(12): 7897-7912. |
[51] | FU Y Z , JIANG C N , YIN L G . Satellite multicast transmission scheme in integrated satellite-maritime networks[C]// Proceedings of 2020 International Wireless Communications and Mobile Computing (IWCMC). Piscataway:IEEE Press, 2020: 988-993. |
[52] | PANG Y , WANG D S , WANG D D ,et al. A space-air-ground integrated network assisted maritime communication network based on mobile edge computing[C]// Proceedings of 2020 IEEE World Congress on Services (SERVICES). Piscataway:IEEE Press,Piscataway:IEEE Press, 2020: 269-274. |
[53] | QU Z P , WANG X H , LIU D C ,et al. Inactivation of Cipc alters the expression of Per1 but not circadian rhythms in mice[J]. Science China (Life Sciences), 2015,58(4): 368-372. |
[54] | CHANG H-H , SONG H , YI Y ,et al. Distributive dynamic spectrum access through deep reinforcement learning:a reservoir computing-based approach[J]. IEEE Internet of Things Journal, 2019,6(2): 1938-1948. |
[55] | CHU M , LI H , LIAO X W ,et al. Reinforcement learning-based multiaccess control and battery prediction with energy harvesting in IoT systems[J]. IEEE Internet of Things Journal, 2019,6(2): 2009-2020. |
[56] | ZHANG H J , ZHANG H S , LONG K P ,et al. Deep learning based radio resource management in NOMA networks:user association,subchannel and power allocation[J]. arXiv Preprint,arXiv:2006.11513, 2020. |
[57] | YE H , LI G Y , JUANG B H . Power of deep learning for channel estimation and signal detection in OFDM systems[J]. IEEE Wireless Communications Letters, 2018,7(1): 114-117. |
[58] | ZHANG Z M , HUA M , LI C G ,et al. Placement delivery array design via attention-based sequence-to-sequence model with deep neural network[J]. IEEE Wireless Communications Letters, 2019,8(2): 372-375. |
[59] | HE Y , ZHAO N , YIN H X . Integrated networking,caching,and computing for connected vehicles:a deep reinforcement learning approach[J]. IEEE Transactions on Vehicular Technology, 2018,67(1): 44-55. |
[60] | SUN H R , CHEN X Y , SHI Q J ,et al. Learning to optimize:training deep neural networks for interference management[J]. IEEE Transactions on Signal Processing, 2018,66(20): 5438-5453. |
[61] | ZHANG H J , YANG N , HUANGFU W ,et al. Power control based on deep reinforcement learning for spectrum sharing[J]. IEEE Transactions on Wireless Communications, 2020,19(6): 4209-4219. |
[62] | WEI X H , HU C , DAI L L . Deep learning for beamspace channel estimation in millimeter-wave massive MIMO systems[J]. IEEE Transactions on Communications, 2021,69(1): 182-193. |
[63] | HE H T , WEN C K , JIN S ,et al. Deep learning-based channel estimation for beamspace mmWave massive MIMO systems[J]. IEEE Wireless Communications Letters, 2018,7(5): 852-855. |
[64] | ZHANG Y H , MU Y F , LIU Y ,et al. Deep learning-based beamspace channel estimation in mmWave massive MIMO systems[J]. IEEE Wireless Communications Letters, 2020,9(12): 2212-2215. |
[65] | WEI Y , ZHAO M M , ZHAO M J ,et al. An AMP-based network with deep residual learning for mmWave beamspace channel estimation[J]. IEEE Wireless Communications Letters, 2019,8(4): 1289-1292. |
[66] | SHABARA Y , EKICI E , KOKSAL C E . Source coding based millimeter-wave channel estimation with deep learning based decoding[J]. IEEE Transactions on Communications, 2021,69(7): 4751-4766. |
[67] | O’SHEA T , HOYDIS J . An introduction to deep learning for the physical layer[J]. IEEE Transactions on Cognitive Communications and Networking, 2017,3(4): 563-575. |
[68] | D?RNER S , CAMMERER S , HOYDIS J ,et al. Deep learning based communication over the air[J]. IEEE Journal of Selected Topics in Signal Processing, 2018,12(1): 132-143. |
[69] | NGUYEN D C , PATHIRANA P N , DING M ,et al. Privacy-preserved task offloading in mobile blockchain with deep reinforcement learning[J]. IEEE Transactions on Network and Service Management, 2020,17(4): 2536-2549. |
[70] | GAO M J , SHEN R J , SHI L ,et al. Task partitioning and offloading in DNN-task enabled mobile edge computing networks[C]// 2019 IEEE Global Communications Conference. Piscataway:IEEE Press, 2019: 1-6. |
[71] | QU G J , WU H M , LI R D ,et al. DMRO:a deep meta reinforcement learning-based task offloading framework for edge-cloud computing[J]. IEEE Transactions on Network and Service Management, 2021,18(3): 3448-3459. |
[72] | HE S W , HUANG W , WANG J H ,et al. Cache-enabled coordinated mobile edge network:opportunities and challenges[J]. IEEE Wireless Communications, 2020,27(2): 204-211. |
[73] | ZHANG Z M , YANG Y Q , HUA M ,et al. Proactive caching for vehicular multi-view 3D video streaming via deep reinforcement learning[J]. IEEE Transactions on Wireless Communications, 2019,18(5): 2693-2706. |
[74] | ZHANG Z M , CHEN H Y , HUA M ,et al. Double coded caching in ultra dense networks:caching and multicast scheduling via deep reinforcement learning[J]. IEEE Transactions on Communications, 2020,68(2): 1071-1086. |
[75] | AWAN D A , CAVALCANTE R L G , STANCZAK S . Robust cell-load learning with a small sample set[J]. IEEE Transactions on Signal Processing, 2020,68: 270-283. |
[76] | 石光明, 肖泳, 李莹玉 ,等. 面向万物智联的语义通信网络[J]. 物联网学报, 2021,5(2): 26-36. |
SHI G M , XIAO Y , LI Y Y ,et al. Semantic communication networking for the intelligence of everything[J]. Chinese Journal on Internet of Things, 2021,5(2): 26-36. | |
[77] | CARNAP R , BAR-HILLEL Y , . An outline of a theory of semantic information:RLE (research laboratory of electronics) technical reports 247[R]. 1952. |
[78] | BAO J , BASU P , DEAN M K ,et al. Towards a theory of semantic communication[C]// Proceedings of 2011 IEEE Network Science Workshop. Piscataway:IEEE Press, 2011: 110-117. |
[79] | FLORIDI L . Outline of a theory of strongly semantic information[J]. Minds and Machines, 2004,14(2): 197-221. |
[80] | 刘传宏, 郭彩丽, 杨洋 ,等. 人工智能物联网中面向智能任务的语义通信方法[J]. 通信学报, 2021,42(11): 97-108. |
LIU C H , GUO C L , YANG Y ,et al. Intelligent task-oriented semantic communication method in artificial intelligence of things[J]. Journal on Communications, 2021,42(11): 97-108. | |
[81] | 涂勇峰, 陈文 . 基于深度学习的语义通信系统[J]. 移动通信, 2021,45(4): 91-94,119. |
TU Y F , CHEN W . A deep learning-based semantic communication system[J]. Mobile Communications, 2021,45(4): 91-94,119. | |
[82] | FARSAD N , RAO M , GOLDSMITH A . Deep learning for joint source-channel coding of text[C]// Proceedings of 2018 IEEE International Conference on Acoustics,Speech and Signal Processing. Piscataway:IEEE Press, 2018: 2326-2330. |
[83] | BOURTSOULATZE E , BURTH KURKA D , GüNDüZ D , . Deep joint source-channel coding for wireless image transmission[J]. IEEE Transactions on Cognitive Communications and Networking, 2019,5(3): 567-579. |
[84] | JANKOWSKI M , GüNDüZ D , MIKOLAJCZYK K . Deep joint source-channel coding for wireless image retrieval[C]// Proceedings of ICASSP 2020 - 2020 IEEE International Conference on Acoustics,Speech and Signal Processing. Piscataway:IEEE Press, 2020: 5070-5074. |
[85] | KURKA D B , GüNDüZ D , . DeepJSCC-f:deep joint source-channel coding of images with feedback[J]. IEEE Journal on Selected Areas in Information Theory, 2020,1(1): 178-193. |
[86] | WEI C C , ZHAO J , ZHOU W G ,et al. Semantic boundary detection with reinforcement learning for continuous sign language recognition[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2021,31(3): 1138-1149. |
[87] | HUANG C L , SHIH H C , CHAO C Y . Semantic analysis of soccer video using dynamic Bayesian network[J]. IEEE Transactions on Multimedia, 2006,8(4): 749-760. |
[88] | CHEN Y T , WANG J , BAI Y N ,et al. Probabilistic semantic retrieval for surveillance videos with activity graphs[J]. IEEE Transactions on Multimedia, 2019,21(3): 704-716. |
[89] | MITRICA I , MERCIER E , RUELLAN C ,et al. Very low bitrate semantic compression of airplane cockpit screen content[J]. IEEE Transactions on Multimedia, 2019,21(9): 2157-2170. |
[90] | XIE H Q , QIN Z J , LI G Y ,et al. Deep learning enabled semantic communication systems[J]. IEEE Transactions on Signal Processing, 2021,69: 2663-2675. |
[91] | XIE H Q , QIN Z J . A lite distributed semantic communication system for Internet of things[J]. IEEE Journal on Selected Areas in Communications, 2021,39(1): 142-153. |
[92] | WENG Z Z , QIN Z J , LI G Y . Semantic communications for speech signals[C]// Proceedings of ICC 2021 - IEEE International Conference on Communications. Piscataway:IEEE Press, 2021: 1-6. |
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