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Downlink Beamforming And Design Of SRS Receiver In LTE-advanced System

Posted on:2016-06-21Degree:MasterType:Thesis
Country:ChinaCandidate:C S ChenFull Text:PDF
GTID:2348330479453100Subject:Communication and Information System
Abstract/Summary:PDF Full Text Request
In order to meet the requirements of spectral efficiency and the transmission rate in mobile communications, LTE-Advanced is evolving all the time. A lot of new technologies including beamforming, SNR estimation and channel estimation are introduced into the TD-LTE-Advanced system.The core content of this article is to study beamforming, SNR estimation and channel estimation.The second chapter introduces the principles of beamforming as well as various beamforming algorithms. It then introduces implementation of various beamforming algorithms. The traditional method used in the calculation beamforming weight is EBB. While it can not accurately calculate the beamforming weight, when the correlation channel matrix contains the same eigenvalues value. The paper presents an algorithm based on Household transformation and Givens rotation to solve this problem.In LTE-A system,a lot of module need accurate channel state information, especially the uplink channel information. The third chapter firstly summarizes the commonly used algorithm in channel estimation. It then carry out the fixed-point implementation of channel estimation. After this, the paper presents a viable scheme of precoding in LTE uplink system. The idea behind the scheme is to maximize the system capacity. Using Shannon formula, it travers the codebook set of the system to select the codebook which make the system has the largest capacity.The fourth chapter firstly implements the pilot section of receiver. Because the frequency-domain filtering algorithm used in noise estimation is inaccurate, the paper presents a time-domain noise estimation algorithm. The key to the algorithm is to get the maximum multipath delay and the cyclic shift. It proves to be a better solution to calculate the SNR than the frequency-domain filtering algorithm.
Keywords/Search Tags:Beamforming, Channel Estimation Precoding, Noise Estimation, Fixed-point, Implementation
PDF Full Text Request
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