CN-122027400-A - Iterative channel estimation method based on LDPC assistance

CN122027400ACN 122027400 ACN122027400 ACN 122027400ACN-122027400-A

Abstract

The application belongs to the technical field of wireless multi-carrier communication and signal processing, and particularly discloses an iterative channel estimation method based on LDPC assistance, which comprises the following steps of performing LDPC low-density parity check code coding, offset quadrature amplitude modulation and filter group multi-carrier modulation on information at a transmitting end; the method comprises the steps of calculating initial channel estimation based on pilot frequency symbols at a receiving end, interpolating to obtain initial channel estimation values at all data symbol positions, carrying out hard decision and remodulation reconstruction to obtain a reconstructed symbol after carrying out balanced demodulation on the data symbol by utilizing the initial channel estimation values, further calculating updated channel estimation according to the received symbol and the reconstructed symbol, combining the initial channel frequency response estimation values at the pilot frequency positions and the updated channel estimation values at the data symbol positions, carrying out Gaussian filtering treatment on the combined channel estimation values, and outputting a final full-frequency-domain channel estimation value. The application can effectively improve the channel estimation accuracy of the FBMC-OQAM system.

Inventors

CHEN CHAO
GUO XIN
ZHOU YIFAN
Zhu Mengshuang

Assignees

中国地质大学（武汉）

Dates

Publication Date: 20260512
Application Date: 20260127

Claims (10)

1. The iterative channel estimation method based on the LDPC assistance is characterized by being applied to an FBMC-OQAM system and comprising the following steps of: S10, at a transmitting end, coding the low-density parity check code of information to be transmitted, and performing offset quadrature amplitude modulation and filter group multi-carrier modulation on the coded symbols to generate a transmitting signal and transmitting the transmitting signal through a channel; s20, at a receiving end, receiving signals and demodulating the signals to obtain frequency domain receiving symbols, calculating initial channel frequency response estimated values at pilot positions based on known pilot symbols and corresponding receiving symbols, and obtaining initial channel estimated values at all data symbol positions through interpolation; s30, based on the initial channel estimation values of all the data symbol positions, carrying out equalization and demodulation on the data symbols, and carrying out hard decision remodulation reconstruction on the demodulated data symbols to obtain reconstructed symbols; s40, calculating an updated channel estimation value at the position of the data symbol according to the received symbol corresponding to the data symbol and the corresponding reconstructed symbol; s50, combining the initial channel frequency response estimated value at the pilot frequency position and the updated channel estimated value at the data symbol position, carrying out Gaussian filtering processing on the combined channel estimated value, and outputting a final full frequency domain channel estimated value.
2. The iterative channel estimation method based on LDPC assistance of claim 1, wherein the calculating the initial channel frequency response estimate at the pilot position in step S20 is specifically: According to the formula Calculating an initial channel frequency response estimate at a pilot location; Wherein, the Representing an initial channel frequency response estimate at a pilot location; Representing known pilot symbol values; Representing the received symbols at the pilot.
3. The iterative channel estimation method based on LDPC assistance as claimed in claim 1, wherein in step S20, the interpolation is two-dimensional natural neighbor interpolation.
4. The iterative channel estimation method based on LDPC assistance as claimed in claim 1, wherein in step S30, the equalization is zero forcing equalization.
5. The iterative channel estimation method based on LDPC assistance as claimed in claim 1, wherein in step S40, the updated channel estimation values at the data symbol positions are calculated The method specifically comprises the following steps: Wherein Y is a received symbol at the data symbol, and RS is a reconstructed symbol corresponding to the data symbol.
6. The iterative channel estimation method based on LDPC assistance as claimed in claim 1, wherein in step S50, the gaussian filtering process is used to attenuate the influence of a single error code on the channel estimation values of adjacent symbols.
7. The iterative channel estimation method based on LDPC assistance of claim 1, wherein the pilot symbols adopt a pilot structure based on an interference correction approximation method, and the pilot structure based on an interference correction approximation method sets four symbols of adjacent subcarriers and adjacent symbol positions of the pilot symbols in a time-frequency grid as zero-valued symbols.
8. The iterative channel estimation method based on LDPC assistance of claim 1, wherein the pilot symbols adopt pilot structures based on an auxiliary pilot method, and the pilot structures based on the auxiliary pilot method place auxiliary pilot symbols at positions with maximum interference coefficients in a first-order neighborhood of the pilot symbols for canceling the inherent imaginary interference.
9. Channel estimation device in an FBMC-OQAM system, characterized by the steps for implementing the method according to any of the claims 1 to 8, comprising: The signal transmitting module is used for carrying out low-density parity check code coding on information to be transmitted at a transmitting end, carrying out offset quadrature amplitude modulation and filter group multicarrier modulation on the coded symbols, generating a transmitting signal and transmitting the transmitting signal through a channel; the signal receiving and initial estimating module is used for receiving signals at a receiving end and demodulating the signals to obtain frequency domain receiving symbols, calculating initial channel frequency response estimated values at pilot positions based on known pilot symbols and corresponding receiving symbols, and obtaining initial channel estimated values at all data symbol positions through interpolation; the symbol reconstruction module is used for carrying out equalization and demodulation on the data symbols based on the initial channel estimation values at all the data symbol positions, and carrying out hard decision remodulation reconstruction on the demodulated data symbols to obtain reconstructed symbols; the iterative updating module is used for calculating an updated channel estimation value at the position of the data symbol according to the received symbol corresponding to the data symbol and the corresponding reconstruction symbol; And the filtering output module is used for combining the initial channel frequency response estimated value at the pilot frequency position and the updated channel estimated value at the data symbol position, carrying out Gaussian filtering processing on the combined channel estimated value and outputting a final full-frequency-domain channel estimated value.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 8.

Description

Iterative channel estimation method based on LDPC assistance Technical Field The application belongs to the technical field of wireless multi-carrier communication and signal processing, and particularly relates to an LDPC (low density parity check) auxiliary iterative channel estimation method. Background The rapid development of wireless communication causes the mobile data access service to show explosive growth, and puts higher demands on the spectral efficiency, anti-interference capability and reliability of the communication system. Orthogonal Frequency Division Multiplexing (OFDM) technology is widely used as a typical multi-carrier waveform technology due to its good ability to resist frequency selective fading, but has problems of sensitivity to frequency offset, loss of spectral efficiency due to the need of adding cyclic prefix, spectrum leakage, peak-to-average ratio, and the like. The filter bank multi-carrier (FBMC) technology has great potential for replacing the OFDM technology due to the advantages of ultrahigh frequency spectrum utilization rate, flexible resource allocation capability and the like. FBMC can be classified into a Quadrature Amplitude Modulation (QAM) system and an Offset Quadrature Amplitude Modulation (OQAM) system according to a difference in baseband modulation scheme. The FBMC/OQAM system transmits the real part and the imaginary part of the complex symbol after QAM modulation in a staggered half period mode, and achieves the same data transmission rate as OFDM. The transmission data enters a channel after passing through the comprehensive filter bank at the transmitting end, and is demodulated and output after passing through the analysis filter bank at the receiving end. The prototype filter used cannot ensure that the signal has orthogonality in both the real number domain and the complex number domain, and the signal processed by the filter bank is affected by inherent interference. This interference makes the receiving end face a serious challenge in channel estimation, and the conventional pilot-based channel estimation method (such as a method directly applied to an OFDM system) is difficult to directly apply, because pilot symbols are interfered by imaginary parts introduced by adjacent data symbols, which seriously affects the initial accuracy of channel estimation. To address this challenge, the prior art proposes various channel estimation methods that suppress or cancel the inherent interference by designing a specific pilot structure. However, these methods are not efficient enough in spectrum resource utilization, or ideal in channel condition requirements, or limited in the thoroughness of interference cancellation, so that the channel estimation accuracy and the overall system performance in a complex channel environment still need to be improved. Therefore, how to improve the channel estimation accuracy of the FBMC-OQAM system is a current urgent problem to be solved. Disclosure of Invention Aiming at the defects of the prior art, the application aims to provide an iterative channel estimation method based on LDPC assistance, which can effectively improve the channel estimation accuracy of an FBMC-OQAM system. In order to achieve the above object, in a first aspect, the present application provides an iterative channel estimation method based on LDPC assistance, applied to an FBMC-OQAM system, comprising the steps of: S10, at a transmitting end, coding the low-density parity check code of information to be transmitted, and performing offset quadrature amplitude modulation and filter group multi-carrier modulation on the coded symbols to generate a transmitting signal and transmitting the transmitting signal through a channel; s20, at a receiving end, receiving signals and demodulating the signals to obtain frequency domain receiving symbols, calculating initial channel frequency response estimated values at pilot positions based on known pilot symbols and corresponding receiving symbols, and obtaining initial channel estimated values at all data symbol positions through interpolation; s30, based on the initial channel estimation values of all the data symbol positions, carrying out equalization and demodulation on the data symbols, and carrying out hard decision remodulation reconstruction on the demodulated data symbols to obtain reconstructed symbols; s40, calculating an updated channel estimation value at the position of the data symbol according to the received symbol corresponding to the data symbol and the corresponding reconstructed symbol; s50, combining the initial channel frequency response estimated value at the pilot frequency position and the updated channel estimated value at the data symbol position, carrying out Gaussian filtering processing on the combined channel estimated value, and outputting a final full frequency domain channel estimated value. As a further preferred embodiment, the calculating the initial channel frequency respon