ID	原文	译文
3483	信道建模是设计无线通信系统的基础，传统的信道建模方法无法自动学习特定类型信道的规律，特别是在针对特殊应用场景，如物联网、毫米波通信、车联网等，存在一定的局限性。	Channel characterization is primary to the design of the wireless communication system. The conventionalchannel characterization method cannot learn the law of certain types of channels by itself, which limits its application inseveral special scenarios, such as Internet of things, millimeter wave communication and Internet of vehicles.
3484	此外，机器学习具有有效处理大数据、创建模型的能力，	Machine learning was able to process the big data and establish the model.
3485	基于此，探讨了机器学习如何与信道建模进行有机融合，分别从信道多径分簇、参数估计、模型的构造及信道的场景识别展开了讨论，对当前该领域的重要研究成果进行了阐述，	Based on this, the cooperation between the machinelearning and channel characterization was investigated. The channel multipath clustering, parameter estimation, modelconstruction and wireless channel scene recognition were discussed, and recent significant research results in this field were provided.
3486	并对未来发展提出了展望。	Finally, the future direction of the machine learning in wireless channel modeling was proposed.
3487	移动设备加密流量分析可以用主动或被动的方式获取多种类型的用户信息，为网络安全管理和用户隐私保护提供保障。	Encrypted traffic analysis of mobile devices can obtain multiple types of user information in an active or pas-sive way, which provides protection for network security management and user privacy protection.
3488	重点分析、归纳了用户信息探测所涉及的数据采集、特征选择、模型与方法以及评价体系的基本原理和关键方法。	The basic principlesand key methods of data collection, feature selection, models and methods, and evaluation systems involved in these userinformation detection were analyzed and summarized.
3489	总结了现有方案中存在的问题，以及未来研究方向和面临的挑战	The problems in the existing projects were summarized, as well asthe future research directions and challenges.
3490	面向物联网业务中的低时延需求，将短包通信（SPC）和非正交多址接入（NOMA）技术相结合，针对存在窃听者的情况研究多用户 NOMA 系统中的安全传输问题。	For the low-latency requirements of Internet of things (IoT) business, short packet communication (SPC) andnon-orthogonal multiple access (NOMA) were combined to study the problem of secure transmission in the multi-userNOMA system with eavesdroppers.
3491	以最大化弱用户的安全吞吐量为目标，考虑用户译码错误概率约束、总功率约束和功率分配约束，提出了一种低复杂度的功率分配方案实现系统安全传输。	With the maximizing the secure throughput of weak uses as the objective, consider-ing the user decoding error probability constraint, total power constraint and power allocation constraint, alow-complexity power allocation algorithm was proposed to realize secure transmission.
3492	为解决复杂的目标函数和不可靠的串行干扰消除（SIC）技术带来的问题，首先证明约束条件在取得最优解时的紧约束性，	In order to solve the problem caused by complex objective function formula and unreliable serial interference cancellation (SIC) technology, the proof that the compactness of the constraints was necessary to find the optimal solution.