OFDM synchronization method of using training circulated prefix

Abstract

The method comprises: inserting the training sequence after the OFDM symbol to generate the cyclic prefix; fixing the training sequence segment in order to search a fitted timing offset; according to the timing offset, calculating the fractional frequency offset to get the integer frequency offset. The integer frequency offset is calculated using the training sequence section; by fixing the training sequence part in OFDM symbol, the value of timing bias is constantly changed to get a section of possible cyclic prefix of OFDM symbol, by which the integer frequency offset estimation, can be made so as to improve the estimation accuracy.

Description

technical field [0001] The present invention relates to wireless communication technology, in particular to OFDM system in wireless communication. technical background [0002] Orthogonal frequency division multiplexing OFDM is a high-speed transmission technology in a wireless environment. Its characteristic is that each subcarrier is orthogonal to each other, so that the spectrum after spread spectrum modulation can overlap with each other, thereby reducing the mutual interference between subcarriers. . However, OFDM systems are very sensitive to timing and frequency offsets compared to single-carrier systems. In order to eliminate inter-symbol interference (ISI) and inter-carrier interference (ICI), synchronization estimation is very important. [0003] The synchronization estimation of the OFDM system in the prior art all adopts data-aided estimation algorithms and non-data-aided estimation algorithms. Data-aided estimation uses multiple OFDM blocks to conduct frequen...

AI Technical Summary

Problems solved by technology

Data-aided estimation uses multiple OFDM blocks to conduct frequency symbols or training sequences, resulting in waste of resources and loss of information rate; although non-data-aided estimation does not waste resources, the performance of estimation in multipath fading channels is not good. Good, not high accuracy

[0004] The classic ML (Maximum Likelihood) algorithm using data correlation properties is proposed based on the Gaussian channel. However, due to the influence of the channel under the multipath fading channel, the repetition property of the cyclic prefix deteriorates so that the timing point d and its two sides The ML function values ​​at the sampling points are very close, resulting in a serious degradation in timing estimation performance

Due to the poor performance of timing estimation, the performance of frequency offset estimation is also degraded

For example, Van de Beek J J et al [Van de Beek J J, Sandell M, Boriesson P O. ML estimation of time and frequency offset in OFDM systems. IEEE Transaction on Signal Processing, 1997, 45(7): 1800-1805] according to the OFDM symbol backend The principle of correlation between data and cyclic prefix data uses ML algorithm to estimate timing and frequency offset at the same time, but the effect is not good in fading channels, and integer multiple frequency offset estimation cannot be performed, so that the synchronization effect is not good

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