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[电气工程与系统科学] 基于最大最小公平性的多色约束部分群译码 多用户可见光通信 [推广有奖]

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何人来此 在职认证  发表于 2022-3-15 12:05:00 来自手机 |只看作者 |坛友微信交流群|倒序 |AI写论文

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摘要翻译:
一种可见光通信(VLC)系统可以采用多色发光二极管(LED)阵列来支持多个用户。本文提出了一种多层编码和约束部分群译码(CPGD)方法,以解决强彩色干扰,提高系统吞吐量。在建立信道模型后,通过贪婪算法解决最大最小公平性问题,分配用户信息速率,得到所有接收数据层的解码顺序。在截断高斯输入分布下导出了一个可实现的速率。为了降低译码复杂度,在接收平面上为所有感兴趣的位置构造一个关于译码顺序和码率分配的映射,并通过基于分类的算法减小其大小。同时,利用了LED阵列的对称几何特性。最后,提出了发射机-用户关联问题,并用遗传算法进行了求解。观察到,由于减小的干扰电平,当接收机与相应的LED阵列稍微不对准时,系统吞吐量增加,但随后由于减弱的链路增益,系统吞吐量减小。
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英文标题:
《Constrained Partial Group Decoding with Max-Min Fairness for Multi-color
  Multi-user Visible Light Communication》
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作者:
Guangtao Zheng, Chen Gong and Zhengyuan Xu
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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:
  A visible light communication (VLC) system can adopt multi-color light emitting diode (LED) arrays to support multiple users. In this paper, a multi-layer coding and constrained partial group decoding (CPGD) method is proposed to tackle strong color interference and increase the system throughput. After channel model formulation, user information rates are allocated and decoding order for all the received data layers is obtained by solving a max-min fairness problem using a greedy algorithm. An achievable rate is derived under the truncated Gaussian input distribution. To reduce the decoding complexity, a map on the decoding order and rate allocation is constructed for all positions of interest on the receiver plane and its size is reduced by a classification-based algorithm. Meanwhile, the symmetrical geometry of LED arrays is exploited. Finally, the transmitter-user association problem is formulated and solved by a genetic algorithm. It is observed that the system throughput increases as the receivers are slightly misaligned with corresponding LED arrays due to the reduced interference level, but decreases afterwards due to the weakened link gain.
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PDF链接:
https://arxiv.org/pdf/1805.07766
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关键词:公平性 可见光 光通信 Applications Optimization 译码 interference 阵列 干扰 color

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