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雷达卡
摘要翻译：
随着车载数据传输需求的不断增长，有限的专用蜂窝频谱成为满足所有蜂窝车辆到一切(V2X)用户需求的瓶颈。为了解决这个问题，未经许可的频谱被认为是支持蜂窝V2X用户的补充。本文研究了蜂窝V2X用户和车载ad-hoc网络(VANET)用户在非授权频谱上的共存问题。为了促进这种共存，我们设计了一种基于能量感知的频谱共享方案，使得蜂窝V2X用户能够公平地访问未经许可的信道，同时减少了蜂窝V2X和VANET用户之间的数据传输冲突。为了最大化移动V2X用户数，我们将调度和资源分配问题描述为一个具有对等效应的双边多对多匹配问题。然后提出了一种动态车辆资源匹配算法(DV-RMA)，并给出了算法收敛时间和计算复杂度的分析结果。仿真结果表明，在使用非授权频谱时，该算法在蜂窝V2X系统的性能上优于现有算法。
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英文标题：
《Cellular V2X in Unlicensed Spectrum: Harmonious Coexistence with VANET
in 5G systems》
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作者：
Pengfei Wang, Boya Di, Hongliang Zhang, Kaigui Bian, Lingyang Song
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最新提交年份：
2017
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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：
With the increasing demand for vehicular data transmission, limited dedicated cellular spectrum becomes a bottleneck to satisfy the requirements of all cellular vehicle-to-everything (V2X) users. To address this issue, unlicensed spectrum is considered to serve as the complement to support cellular V2X users. In this paper, we study the coexistence problem of cellular V2X users and vehicular ad-hoc network~(VANET) users over the unlicensed spectrum. To facilitate the coexistence, we design an energy sensing based spectrum sharing scheme, where cellular V2X users are able to access the unlicensed channels fairly while reducing the data transmission collisions between cellular V2X and VANET users. In order to maximize the number of active cellular V2X users, we formulate the scheduling and resource allocation problem as a two-sided many-to-many matching with peer effects. We then propose a dynamic vehicle-resource matching algorithm (DV-RMA) and present the analytical results on the convergence time and computational complexity. Simulation results show that the proposed algorithm outperforms existing approaches in terms of the performance of cellular V2X system when the unlicensed spectrum is utilized.
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PDF链接：
https://arxiv.org/pdf/1712.04639
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