Channel estimation method based on cell reference signal in LTE-A system

Abstract

The invention relates to a channel estimation method based on a cell reference signal in an LTE-A system, and belongs to the technical field of the mobile communication. The method specifically comprises the following steps: S1, performing pilot frequency extraction on all receiving signals according to a cell reference signal mapping rule to obtain the receiving signal at a CRS, and finishing theLS estimation by using the receiving signal and the local pilot frequency signal; S2, performing interpolation through an obtained pilot frequency channel estimation value to increase the virtual pilot frequency, thereby doubling the pilot frequency; S3, estimating a channel delay parameter and a signal-to-noise ratio by using the channel estimation value at the pilot frequency subcarrier; S4, selecting a corresponding interpolation matrix W from an LMMSE frequency domain interpolation matrix storage unit according to an estimation result; S5, reading a W matrix from the frequency domain interpolation, and estimating an OFDM symbol channel estimation value containing the pilot frequency according to the formula as shown in description by using a frequency domain sliding window; and S6, performing time domain linear interpolation to obtain the channel response estimation value of all sub-carriers. Therefore, the good compromise between the algorithm performance and the complexity is realized.

Description

technical field [0001] The invention belongs to the technical field of mobile communication, and relates to a channel estimation method based on cell reference signals in an LTE-A system. Background technique [0002] The core technologies of the physical layer of the LTE-A system are Orthogonal Frequency Division Multiplexing (OFDM) technology and Multiple-Input Multiple-Output (Multiple-Input Multiple-Output, MIMO) technology. OFDM technology improves spectrum utilization and can effectively resist multipath fading. MIMO technology improves transmission rate without increasing frequency resources, and these technologies require good channel estimation as a support. Therefore, channel estimation is an indispensable part of the entire communication system. Only by fully understanding the channel state information can the overall performance of the wireless communication system be improved. [0003] In the LTE-A system, a channel estimation method based on reference signals ...

AI Technical Summary

Problems solved by technology

Among them, the LMMSE frequency domain interpolation algorithm has excellent performance, but requires channel prior information and has high complexity. However, in the actual application environment, the channel prior knowledge such as autocorrelation matrix and signal-to-noise ratio (SNR) is unknown, which limits the LMMSE estimation algorithm. application

[0004] So far, there have been many LMMSE improved algorithms, but they often only consider performance and algorithm complexity. Algorithms with better performance have too high complexity, while algorithms with low complexity have less than ideal accuracy and cannot achieve better results. Compromise, cannot be applied to the actual LTE-A system

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