发帖
雷达卡
摘要翻译：
本文研究了信源采用中继和空间分集的自由空间光通信(FSO)系统的性能分析。分析中还考虑了由不同天气条件和几何损失引起的大气湍流和衰减的影响。给出了多跳多输入单输出(MISO)FSO系统在对数正态衰落信道下M进制正交幅度调制（M-QAM）技术误码率的精确闭式表达式。在此基础上，比较了多跳MISO和多跳单输入单输出(SISO)FSO系统与采用开关键控(OOK)、重复码(RCs)和M进制脉冲幅度调制（M-PAM）技术的不同系统的链路性能。对于M-QAM多跳MISO和多跳SISO FSO系统，在误码率分析和信噪比增益方面都有显著的提高。此外，用Monte-Carlo模拟验证了导出的分析结果的准确性和一致性。数值结果表明，具有中继和空间分集的M-QAM调制多跳MISO和多跳SISO FSO系统在频谱效率相同的情况下性能优于其他系统。
---
英文标题：
《Performance analysis of FSO using relays and spatial diversity under
log-normal fading channel》
---
作者：
Pranav Kumar Jha, Nitin Kachare, K Kalyani and D. Sriram Kumar
---
最新提交年份：
2018
---
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。
--
一级分类：Computer Science 计算机科学
二级分类：Information Theory 信息论
分类描述：Covers theoretical and experimental aspects of information theory and coding. Includes material in ACM Subject Class E.4 and intersects with H.1.1.
涵盖信息论和编码的理论和实验方面。包括ACM学科类E.4中的材料，并与H.1.1有交集。
--
一级分类：Mathematics 数学
二级分类：Information Theory 信息论
分类描述：math.IT is an alias for cs.IT. Covers theoretical and experimental aspects of information theory and coding.
它是cs.it的别名。涵盖信息论和编码的理论和实验方面。
--
---
英文摘要：
The performance analysis of free space optical communication (FSO) system using relays and spatial diversity at the source is studied in this paper. The effect of atmospheric turbulence and attenuation, caused by different weather conditions and geometric losses, has also been considered for analysis. The exact closed-form expressions are presented for bit error rate (BER) of M-ary quadrature amplitude modulation (M-QAM) technique for multi-hop multiple-input single-output (MISO) FSO system under log-normal fading channel. Furthermore, the link performance of multi-hop MISO and multi-hop single-input and single-output (SISO) FSO systems are compared to the different systems using on-off keying (OOK), repetition codes (RCs) and M-ary pulse amplitude modulation (M-PAM) techniques. A significant performance enhancement in terms of BER analysis and SNR gains is shown for multi-hop MISO and multi-hop SISO FSO systems with M-QAM over other existing systems with different modulation schemes. Moreover, Monte-Carlo simulations are used to validate the accuracy and consistency of the derived analytical results. Numerical results show that M-QAM modulated multi-hop MISO and multi-hop SISO FSO system with relays and spatial diversity outperforms other systems while having the same spectral efficiency of each system.
---
PDF链接：
https://arxiv.org/pdf/1710.00484
提升卡
置顶卡
沉默卡
变色卡
抢沙发
千斤顶
显身卡
京公网安备 11010802022788号
