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[电气工程与系统科学] 面向超可靠低时延物联网的底层控制信令 通信 [推广有奖]

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能者818 在职认证  发表于 2022-3-4 18:22:00 来自手机 |AI写论文

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摘要翻译:
未来的移动网络不仅要提高移动宽带(MBB)链路的传统链路质量和数据速率,而且要开发新的控制信道来满足时延敏感的使用情况。特别是,对于许多物联网(IoT)用户来说,对超可靠低延迟通信(URLLC)的需求得到了极大的强调。在本文中,我们提出了一种新的扩频波形设计,我们提出了控制信号的传输,以建立URLLC通信。这些控制信号在属于网络中的MBB通信的频谱资源上传输,但以对这些数据信道影响最小的水平传输。所提出的波形虽然是直接序列扩频(DSSS)技术,但其设计是为了利用OFDM宽带通信在网络中可用的符号同步。显然,这允许与网络的其他部分进行简单的同步。所提出的DSSS方法可以在每个OFDM时间帧内传输单个比特和多个比特,并且可以同时服务于多个用户设备(UE)节点。
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英文标题:
《Underlay Control Signaling for Ultra-Reliable Low-Latency IoT
  Communications》
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作者:
Amir Aminjavaheri, Ahmad RezazadehReyhani, Ramon Khalona, Hussein
  Moradi, Behrouz Farhang-Boroujeny
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最新提交年份:
2018
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分类信息:

一级分类:Electrical Engineering and Systems Science        电气工程与系统科学
二级分类:Signal Processing        信号处理
分类描述:Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用,包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、(生物)医学、图像、视频和多模态自然和人为信号,包括通信信号和数据。感兴趣的主题包括:统计信号处理、谱估计和系统辨识;滤波器设计;自适应滤波/随机学习;(压缩)采样、传感和变换域方法,包括快速算法;用于机器学习的信号处理和用于信号处理应用的机器学习;网络与图形信号处理;信号处理中的凸和非凸优化方法;雷达、声纳和传感器阵列波束形成和测向;通信信号处理;低功耗、多核、片上系统信号处理;信息物理系统的传感、通信、分析和优化,如电网和物联网。
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英文摘要:
  Future mobile networks not only envision enhancing the traditional link quality and data rates of mobile broad band (MBB) links, but also development of new control channels to meet the requirements of delay sensitive use cases. In particular, the need for ultra-reliable low-latency communications (URLLC) for many internet of things (IoT) users is greatly emphasized. In this paper, we present a novel spread spectrum waveform design that we propose for transmission of control signals to establish URLLC communications. These control signals are transmitted over the spectral resources that belong to the MBB communications in the network, but at a level that minimally affects these data channels. The proposed waveform, although a direct sequence spread spectrum (DSSS) technique, is designed to take advantage of symbol synchronization available to the OFDM broad band communications in the network. This, clearly, allows simple synchronization with the rest of the network. The proposed DSSS method can transmit single and multiple bits within each OFDM time frame and can serve many user equipment (UE) nodes simultaneously.
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PDF链接:
https://arxiv.org/pdf/1711.02248
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关键词:物联网 Applications Optimization Transmission SIMULTANEOUS data 信道 提出 得到 IoT

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