ITR: Design of Novel Receiver Algorithms for OFDM Incorporating Realistic Indoor Channel Modeling

ITR:结合现实室内信道建模的新型 OFDM 接收器算法设计

基本信息

项目摘要

The explosive demand for communication services, fueled by therapid growth in the areas of mobile communications and theInternet, has generated and will continue to generate immenseresearch efforts in the area of wideband wired/wirelesscommunications. To accommodate the demanding future applications,systems must be designed to perform joint equalization, detection,decoding and estimation of the unknown and possibly time varyingchannel parameters, while maintaining reasonable complexity (andlow cost). Motivated by these requirements, and using an OFDMindoor wireless system as a design example, two main directionsare investigated in this project.In the first direction, receiver algorithms are designed foriterative, joint equalization, detection and decoding, thataddress the critical issues mentioned above. The investigationstarts by identifying a powerful model that encompasses all thesalient features of the OFDM transmission system. Data detectionin OFDM is then stated as a problem of two-dimensional (2D) datadetection in the presence of localized, 2D intersymbolinterference, non-linear distortion, and unknown and time varyingparameters. We then identify fast, joint data detection andchannel estimation schemes which are utilized as building blocksfor powerful adaptive iterative detection receivers. Unlike theentire iterative receiver, these sub-blocks are optimal in aprecisely defined sense, and can be implemented withless-than-exponential complexity with respect to the data sequencelength.The second direction is the development of a unified framework forthe analysis of the transient and steady-state behavior ofadaptive iterative algorithms. In the proposed study, the receiveris assumed to have no explicit knowledge about the channelparameters, other than their statistical description. The minimumsignal-to-noise ratio required for convergence to error-freetransmission, and the optimal allocation of power in pilot andcoded symbols, are some of the issues that are investigated for awide variety of adaptive iterative receiver architectures.Regarding propagation modeling for the indoor environment, theapproach followed herein is a direct divergence from the classicalapproaches that include either measurements, or thewell-established ray-tracing techniques. In particular, ultra-fastalgorithms for the numerical solution of the electromagneticproblem are developed. These algorithms result in almost exactsolutions that can be evaluated with complexity comparable to theless accurate ray-tracing techniques.
在移动通信和互联网领域迅猛发展的推动下,对通信服务的爆炸性需求已经并将继续在宽带有线/无线通信领域产生巨大的研究努力。为了适应苛刻的未来应用,系统必须设计为执行联合均衡,检测,解码和估计未知和可能时变的信道参数,同时保持合理的复杂性(和低成本)。在这些需求的推动下,本课题以OFDMindoor无线系统为例,主要从两个方向进行了研究。在第一个方向上,接收机算法设计用于迭代、联合均衡、检测和解码,以解决上述关键问题。本研究首先确定一个包含OFDM传输系统所有显著特征的强大模型。然后将OFDM中的数据检测描述为存在局部、二维符号间干扰、非线性失真以及未知和时变参数的二维(2D)数据检测问题。然后,我们确定了快速,联合数据检测和信道估计方案,这些方案被用作强大的自适应迭代检测接收机的构建块。与整个迭代接收器不同,这些子块在精确定义的意义上是最优的,并且可以在相对于数据序列长度的指数复杂度下实现。第二个方向是建立一个统一的框架来分析自适应迭代算法的瞬态和稳态行为。在提出的研究中,除了信道参数的统计描述外,假设接收方对信道参数没有明确的了解。收敛到无差错传输所需的最小信噪比,以及导频和编码符号的最佳功率分配,是各种自适应迭代接收机架构所研究的一些问题。关于室内环境的传播建模,本文所采用的方法是与经典方法的直接分歧,经典方法包括测量或完善的光线追踪技术。特别地,开发了电磁问题数值解的超快速算法。这些算法产生了几乎精确的解决方案,可以用与不太精确的光线追踪技术相当的复杂性进行评估。

项目成果

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Achilleas Anastasopoulos其他文献

Using Graphics Processing Units in an LTE Base Station

Achilleas Anastasopoulos的其他文献

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{{ truncateString('Achilleas Anastasopoulos', 18)}}的其他基金

Collaborative Research: Distributed Mechanism Design with Learning Guarantees: Resource Allocation among Networked Strategic Agents
协作研究:具有学习保证的分布式机制设计:网络化战略代理之间的资源分配
  • 批准号:
    2015191
  • 财政年份:
    2020
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant
A control-theoretic framework for analysis and design of networked systems with strategic agents via structured strategies
通过结构化策略分析和设计具有策略代理的网络系统的控制理论框架
  • 批准号:
    1608361
  • 财政年份:
    2016
  • 资助金额:
    $ 40万
  • 项目类别:
    Standard Grant
CAREER: Exploring the Complexity Limits of Joint Data Detection and Channel Estimation: Exact, Polynomial-Complexity Solutions and Ultra-Fast Approximations
职业:探索联合数据检测和信道估计的复杂性极限:精确、多项式复杂性解决方案和超快速近似
  • 批准号:
    0346977
  • 财政年份:
    2004
  • 资助金额:
    $ 40万
  • 项目类别:
    Continuing Grant

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