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[电气工程与系统科学] 一种基于SDR的LTE-WiFi聚合系统的设计与实现 [推广有奖]

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nandehutu2022 在职认证  发表于 2022-3-7 14:04:25 来自手机 |AI写论文

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摘要翻译:
随着移动互联网接入的爆炸性增长和无线局域网(WLAN)接入点(APs)的普及,无线保真(WiFi)卸载被认为是减轻蜂窝基础设施负载、提高网络服务质量的重要补充技术。本文设计并实现了符合第三代合作伙伴计划(3GPP)标准的LTEWiFi聚合(LWA)框架。在LWA系统中,数据卸载的过程不同于蜂窝核心网上WiFi互通的过程。无线局域网APs直接连接到eNodeBs(eNB)上,在分组数据汇聚协议层(PDCP)实现卸载。因此,该架构充分利用了现有的无线局域网APs来提高室内蜂窝网络的性能。此外,得益于LTE和WiFi之间的流量控制,eNB调度可以更加灵活和高效。然后,基于开放源码的OpenAirInterface(OAI)软件无线电(SDR)平台对其进行了实现,提出并实现了一种简单实用的重排序方法。实验结果表明,我们的设计具有稳定的WiFi卸载和重排序功能。
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英文标题:
《Design and Implementation of a LTE-WiFi Aggregation System based on SDR》
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作者:
Haitao Liu
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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 explosive growth of the mobile Internet access and the popularization of wireless local area network (WLAN) access points (APs), wireless fidelity (WiFi) offloading is considered as an important supplementary technique to reduce the load of cellular infrastructure and enhance quality of network service. In this paper, we design and implement the framework of LTEWiFi aggregation (LWA) which is in line with the 3rd Generation Partnership Project (3GPP) released standard recently. In the LWA system, the process of data offloading is different from that of WiFi interworking on the cellular core network. WLAN APs directly connect to eNodeBs (eNBs), and the offloading is realized in Packet Data Convergence Protocol layer (PDCP). Thus, this architecture makes full use of existed WLAN APs to improve the performance of indoor cellular network. Besides, benefiting from the flow control between LTE and WiFi, eNB schedule can be more flexible and efficient. Next, it is implemented based on open source OpenAirInterface (OAI) software defined radio (SDR) platform, where a simple and practical reordering method is proposed and carried out. Experimental results demonstrate that our design works stably with the WiFi-offloading and reordering functions.
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PDF链接:
https://arxiv.org/pdf/1711.09386
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关键词:WiFi LTE IFI SDR Applications 网络 design 方法 LTE access

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