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  1. National Taiwan Ocean University Research Hub

Channel Estimation and Spectral Prediction in Nonlinear Multicarrier Systems

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Project title
Channel Estimation and Spectral Prediction in Nonlinear Multicarrier Systems
Code/計畫編號
NSC99-2221-E019-005
Translated Name/計畫中文名
非線性多載波系統之通道估測與頻譜預測
 
Project Coordinator/計畫主持人
Ching-Hsiang Tseng
Funding Organization/主管機關
National Science and Technology Council
 
Department/Unit
Department of Electrical Engineering
Website
https://www.grb.gov.tw/search/planDetail?id=2139070
Year
2010
 
Start date/計畫起
01-08-2010
Expected Completion/計畫迄
31-07-2011
 
Bugetid/研究經費
590千元
 
ResearchField/研究領域
電信工程
 

Description

Abstract
本三年計畫的目標是要開發具有較佳性能及較低計算複雜度的創新方法來估測基頻(baseband)及通頻(passband)正交分頻多工(OFDM)系統中之非線性通道,以及開發 用於預測正交分頻多工訊號受非線性通道影響所造成之頻譜再生(spectral regrowth)的新方法。正交分頻多工是一種特殊形式之多載波調變(multicarrier modulation)。它已經被廣泛地使用於非對稱數位用戶線路(ADSL)和電力線通訊、無線區域網路(LAN)、數位音訊廣播(DAB)、以及數位視訊廣播(DVB)等。由於正交分頻多工訊號可能呈現高峰值對平均功率比(PAR),這導致正交分頻多工系統很容易在通道之非線性特性(如功率放大器之非線性特性)影響下產生失真。因此,瞭解通道之非線性特性如何造成正交分頻多工訊號失真是一個成功的正交分頻多工系統所不可或缺的。在本計畫的第一年裡,我們提出了以具有頻譜凹口(spectral notch)之正交分頻多工訊號來估測正交分頻多工系統中非線性通道之頻域伏特拉核心(Volterra Kernel)的創新方法。在這個方法中,正交分頻多工訊號中的每一個具有完整頻譜的正交分頻多工符元框架(symbol frame)都跟隨多個相同的複製符元框架,但每個複製符元框架都在一個不同的頻率上有個頻譜凹口。藉由使用具有頻譜凹口的正交分頻多工符元框架,我們發現所欲達成之伏特拉核心估測任務可以被解構成具有較小數目核心係數的獨立子任務。由於這些子任務的伏特拉核心係數數目較少,所以其伏特拉核心係數的估測可以用較低之計算複雜度達成較精確的估測結果。我們將證明所提出的方法的計算複雜度為O(M4),而傳統之方法則需要O(M6)的計算複雜度。在第二年裡,我們將藉由考慮正交分頻多工訊號的高階統計(higher-order statistics)特性來進一步簡化第一年所開發出的頻譜凹口法。我們將證明透過使用具有頻譜凹口之正交分頻多工訊號的高階自動差(auto-moment)頻譜特性,一個僅需O(M)計算複雜度的簡易核心估測演算法可以被推導出來。同時,我們也將開發出能保證獲得最佳化最小均方誤差(MMSE)解之假隨機(pseudo random)測試序列的系統化產生方法。在第三年我們將推導正交分頻多工訊號在功率放大器輸出端之頻譜的閉合(closed-form)表示式。這個閉合表示式是以功率放大器參數以及正交分頻多工訊號之高階統計量來呈現。這個表示式可以用來預測正交分頻多工訊號受功率放大器非線性特性影響所造成的頻譜再生。這個問題的重要性在於它可以幫我們預見所選之功率放大器是否能適用於所考慮之應用,而不需要實際進行昂貴的實驗測試。我們將證明所提出的預測方法要比傳統方法更簡單且更精確。在這三年裏我們將持續進行電腦模擬以驗證所提出之多種方法的優點。所提出之方法也將被應用於測試實驗性之基頻及通頻正交分頻多工系統的非線性通道。The goal of this three-year project is to develop novel methods for estimating nonlinear channels in baseband and passband OFDM systems with better performance and less com-putational complexity, and for predicting the spectral regrowth of OFDM signals caused by the nonlinear channels. The OFDM is a special form of multicarrier modulation. It has been widely used in asymmetric digital subscriber line (ADSL) and powerline communications, wireless local area networks (LANs), digital audio broadcasting (DAB), and digital video broadcasting (DVB). However, the OFDM signal may exhibit a high peak-to-average power ratio (PAR), which causes the OFDM to be very vulnerable to nonlinearities in the channel (e.g., power amplifier nonlinearities). Therefore, understanding how the channel nonlineari-ties distort the OFDM signal is essential to the success of an OFDM system. In the first year of this project, we propose a novel method to estimate the frequency-domain Volterra kernels of nonlinear channels in OFDM systems using OFDM signals with spectral notches. In this method, the OFDM signal is arranged in a way that each full-spectral OFDM symbol frame is followed by copies of the same OFDM symbol frame but each has a spectral notch at a distinct frequency. Through the use of OFDM symbol frames with spectral notches, we find that the task of Volterra kernel estimation can be decomposed into independent subtasks with smaller numbers of kernel coefficients. Therefore, the estimation of the Volterra kernels in the subtasks can be accomplished with more accuracy and less computational complexity. We will show that, the proposed method has a computational complexity of O(M4), while the conventional method would require a computational complexity of O(M6). In the second year, we will further simplify the spectral notch method developed in the first year by con-sidering higher-order statistics of the OFDM signal. We will show that, by using higher-order auto-moment spectral properties of OFDM signals with spectral notches, a very simple kernel estimation algorithm with a computational complexity of only O(M) can be derived. Meanwhile, a systematic method for generating pseudo random test sequences which guarantee the attainment of the optimal minimum-mean-square-error (MMSE) solu-tion will also be developed. In the third year, we will derive a closed-form expression for the spectrum of the OFDM signal at the power amplifier output in terms of power amplifier pa-rameters and the higher-order statistics of the OFDM signal. This expression can be used to predict the spectral regrowth of the OFDM signal caused by power-amplifier nonlinearities. This problem is important because it can help to foresee whether the power amplifier is suitable for the application under consideration without actually conducting expensive ex-periments. We will show that the proposed prediction method is simpler yet more accurate compared to the conventional method. Computer simulations will be conducted throughout the three years to justify the goodness of the proposed various methods. The proposed methods will also be applied to test the channel nonlinearities in experimental baseband and passband OFDM systems.
 
Keyword(s)
多載波調變
正交分頻多工
非線性通道
通道估測
伏特拉模型
伏特拉核心
高階頻譜
頻譜再生
頻域分析
Multicarrier modulation
OFDM
nonlinear channel
channel estimation
Volterra model
Volterra kernel
higher-order spectrum
spectral regrowth
frequencydomain analysis
 
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