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Frequency Offset Estimation Algorithm for OFDM Systems

Author: LanTianYi
Tutor: ShuFeng
School: Nanjing University of Technology and Engineering
Course: Communication and Information System
Keywords: Orthogonal Frequency Division Multiplexing Carrier frequency offset Maximum Likelihood Multiple signal classification Rotation invariant subspace Zero Carrier
CLC: TN919.3
Type: Master's thesis
Year: 2010
Downloads: 161
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Abstract


With the development of communication technology , people on communication quality , communication speed, bandwidth put forward higher requirements. Orthogonal frequency division multiplexing (OFDM, Orthogonal Frequency Division Multiplexing) technology is a key to meet future communication technologies. This technique can be effective against multipath fading and improve bandwidth utilization. However, due to the frequency offset for OFDM systems (CFO, Carrier Frequency Offset) is very sensitive , it will seriously affect the system performance. This paper studies the more popular now offset estimation algorithm , and its theoretical analysis and simulation performance, and on this basis propose a carrier based on distributed zero minimum power and algorithms. Main tasks are as follows: a ) for blind CFO estimation methods , focusing on the maximum likelihood (ML, Maximum Likelihood) algorithm, multiple signal classification (MUSIC, Multiple Signal Classification,) algorithm and rotation invariant subspace (ESPRIT, Estimation of Signal Parameters via Rotational Invariance Techniques) algorithm three classical algorithms. Through the complexity analysis as well as simulation and compared with those obtained following conclusions: As a whole , the band Blind Estimation of efficiency is good, high complexity , the estimated range limited ; ML estimation algorithm although better accuracy , less complex , but can only be estimated fractional frequency offset ; MUSIC algorithm to estimate the range, accuracy is good, but its high complexity ; ESPRIT algorithm and MUSIC algorithm similar to the estimated range , complexity, and MUSIC algorithm is similar , but at higher SNR in the end the case of high precision low. 2 ) can not be achieved for ML integer CFO estimation , focus on the zero-based carrier Sameer-Kumar (SK) algorithm, and X.MA algorithm and analyze its computational complexity and simulation performance. Since SK poor performance , X.MA higher computational complexity , fully tap the wireless channel on the basis of frequency selective characteristics , we propose a new distributed zero carrier minimum power and methods. Simulation results show that our proposed algorithm has the same complexity SK similar , but to achieve a lower error than the probability of detection . And this method is better than X.MA much lower computational complexity .

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