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Research on the Key Technique Based on LTE Uplink

Author: XueLiJun
Tutor: ZengZhaoHua
School: Xi'an University of Science and Technology
Course: Communication and Information System
Keywords: LTE Single-Carrier Frequency Division Multiple Access A physical uplink shared channel Channel estimation
CLC: TN929.5
Type: Master's thesis
Year: 2011
Downloads: 173
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Abstract


At the end of 2004 , the 3GPP organization through the 3G Long Term Evolution ( the Long Term Evoloution LTE) , LTE provides high-speed data transfer rate and reduce system latency while increasing the coverage and system capacity , and reduce operating costs . LTE is an important work carried out by the international standards organization , the LTE research is necessary . In this paper, on the basis of the research of key technologies for LTE uplink channel estimation algorithm is carried out in-depth research . LTE uplink departure of key technologies . First introduced the LTE core technology of OFDM and MIMO technologies . Next , for the LTE uplink transmission technology , focusing on the physical shared channel (PUSCH) and the uplink single carrier frequency division multiple access signal generated and transmitted in the terminal when the use of both the MIMO scheme . Introduces the next channel estimation method in the LTE uplink , including uplink pilot the selection of the pattern , the pilot at the position of the channel estimation method and the non-pilot position at the interpolation method . Finally, based on the LTE protocol specification , build the LTE physical uplink shared channel simulation platform , the first three basic channel estimation algorithm for the simulation, analysis and comparison of the performance of the three basic algorithms . Followed by simulation of two improved algorithms , both the LMMSE iterative algorithm with LS windowed filtering to noise algorithm , these two algorithms in the original algorithm on the basis of performance has improved . Finally, for the the LMMSE iterative algorithm complexity is too high this shortcoming proposed to two improved algorithms, both the LS windowed filter denoising LMMSE algorithm with SVD-MMSE algorithm . The simulation results show that the two compared the improved algorithm with the original algorithm can achieve better performance than the original algorithm , in case that does not increase too much the amount of computation .

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