WO2016058476A1 - Procédé et dispositif d'estimation de canal de système de liaison montante lte en cas de brouillage - Google Patents

Procédé et dispositif d'estimation de canal de système de liaison montante lte en cas de brouillage Download PDF

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WO2016058476A1
WO2016058476A1 PCT/CN2015/090735 CN2015090735W WO2016058476A1 WO 2016058476 A1 WO2016058476 A1 WO 2016058476A1 CN 2015090735 W CN2015090735 W CN 2015090735W WO 2016058476 A1 WO2016058476 A1 WO 2016058476A1
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vector
frequency domain
channel estimation
value
estimation
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PCT/CN2015/090735
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English (en)
Chinese (zh)
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熊高才
秦洪峰
林灯生
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中兴通讯股份有限公司
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines

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  • This document relates to, but is not limited to, the field of communications, and in particular, to a method and apparatus for estimating LTE uplink system channels under interference conditions.
  • the LTE (Long Term Evolution) system has adopted the SC-FDMA (Single-Carrier Frequency-Division Multiple Access) technology as the uplink multiple access technology. Since the LTE system uses global frequency reuse, neighbor cell interference. The phenomenon is more serious; in addition, in some frequency bands, LTE uplink may suffer from interference from a variety of different systems, such as:
  • Microwave oven (50% of the busyness in the 2.4 GHz band will generate pulse interference).
  • the channel estimation algorithms commonly used in the LTE uplink mainly include the following three types:
  • LS Least Squares
  • h LS X -1 y m
  • X is the designed steering vector
  • () -1 represents the inverse of the matrix
  • y m is the received steering vector
  • LMMSE Linear Minimum Mean Square Error
  • h LMMSE R h (R h +S H R j S+N 0 I) -1
  • DFT-Based (Fourier Transform) algorithm DFT-Based channel estimation proposed in the article "DFT-Based Channel Estimation and Noise Variance Estimation Techniques for Single-Carrier FDMA" is based on LS channel estimation technology. The characteristics of the domain channel energy concentration achieve noise reduction and suppression of interference.
  • the DFT-Based channel estimation transforms the LS channel estimation value into the time domain through IDFT, and then performs time domain windowing to achieve noise reduction and interference suppression. After the windowing process is completed, the DFT transform is performed to the frequency domain.
  • the LS algorithm has the advantages of simple implementation, but does not have the noise cancellation capability, and has poor performance at low SNR, and the performance will deteriorate further in the presence of interference;
  • the linear optimal LMMSE algorithm has the best noise cancellation effect.
  • LMMSE channel estimation there is a need for more a priori information and high computational complexity.
  • the interference signal is generally unknown in the actual communication environment;
  • the traditional DFT-Based technology uses a fixed window length filter matrix, which causes insufficient noise and interference filtering, or a large signal energy loss under high SNR conditions. Due to the energy diffusion problem in the time domain channel response, The DFT-Based technology suffers from severe degradation in performance when the user occupies fewer subcarriers.
  • Embodiments of the present invention provide a channel estimation method and apparatus for an LTE uplink system under interference conditions, to solve the technical problem of how to simply and sufficiently preserve channel energy and improve channel estimation accuracy while filtering noise and suppressing interference.
  • An embodiment of the present invention provides a channel estimation method for an LTE uplink system under interference conditions, including:
  • Y m is processed in the frequency domain, and part of the interference spectrum is deleted, and the vector y m after frequency domain suppression is obtained;
  • the step of processing Y m in the frequency domain, deleting part of the interference spectrum, and obtaining the frequency domain suppressed vector y m includes:
  • the pilot vector Y m of the frequency domain baseband signal is sorted by the square size, and the half of the spectral value of the minimum modulus value is selected; the mean square value of the selected spectral line is obtained, and then a factor ⁇ is multiplied as a gate Limit, ⁇ is the ratio of noise to useful signal;
  • the step of weighting the LS estimation output vector to obtain the channel estimation value includes:
  • the calculation process of the U, U H, and Q1 is as follows:
  • the DFT-Based channel estimation result of the LS estimated output vector is:
  • T 11 is a square matrix of N SC order, and N SC is a number of subcarriers occupied by the user.
  • T 11 U ⁇ U H
  • U is a eigenvector obtained by eigenvalue decomposition of T 11 ;
  • ⁇ is a diagonal matrix
  • the number of non-zero elements is Q1
  • Q1 ⁇ Q is a rectangular window length
  • the weight matrix is calculated according to the stored U, U H, and Q1 values, and the LS estimation output vector is weighted, and the obtained channel estimation value includes:
  • the least squares estimate is windowed in the feature domain:
  • h U is the channel estimation value obtained by performing the weighting. .
  • An embodiment of the present invention further provides an LTE uplink system channel estimation apparatus under interference conditions, including:
  • Fast Fourier transform module configured to receive steering vector base band signal, obtained through the fast Fourier transform steering vectors Y m of frequency domain baseband signal;
  • the frequency domain processing module is configured to process Y m in the frequency domain, delete part of the interference spectrum line, and obtain a vector y m after frequency domain suppression;
  • the frequency domain processing module includes:
  • a threshold generation submodule configured to sort the pilot vector Y m of the frequency domain baseband signal by a modulus square, select a half of the spectral value with the smallest modulus value; and obtain a norm average of the selected spectral line, and then Multiply a factor ⁇ as the threshold value, and ⁇ is the ratio of the noise to the useful signal;
  • a spectral line deletion submodule configured to compare a modulus value of the pilot vector Y m spectral line of the frequency domain baseband signal with a threshold value, and delete a spectral line greater than the threshold value, less than the gate
  • the spectral line of the limit remains unchanged, and the vector y m after the line deletion is obtained.
  • the channel estimation module includes:
  • Weighted sub-modules including:
  • a storage unit configured to save a previously calculated U, U H matrix and a non-zero element number Q1;
  • the calculating unit is configured to calculate the U, U H matrix and the non-zero element number Q1, calculate a weight matrix according to the stored U, U H and Q1 values and weight the LS estimated output vector to obtain a channel estimation value.
  • the calculation process of the U, U H, and Q1 is as follows:
  • the DFT-Based channel estimation result of the LS estimated output vector is:
  • T 11 is a square matrix of N SC order, and N SC is a number of subcarriers occupied by the user.
  • T 11 U ⁇ U H
  • U is a eigenvector obtained by eigenvalue decomposition of T 11 ;
  • ⁇ is a diagonal matrix
  • the number of non-zero elements is Q1
  • Q1 ⁇ Q is a rectangular window length
  • the calculating unit is configured to calculate a weight matrix according to the stored U, U H, and Q1 values and weight the LS estimated output vector, where the channel estimation value is obtained by:
  • the least squares estimate is windowed in the feature domain:
  • h U is the channel estimation value obtained by performing the weighting.
  • An embodiment of the present invention provides a computer storage medium, where the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the foregoing method.
  • the embodiment of the invention proposes a channel estimation scheme based on frequency domain deletion and EVD decomposition (eigenvalue decomposition), which solves the problem that the traditional DFT-Based channel estimation technology can not suppress strong interference due to energy diffusion and channel estimation accuracy.
  • the problem of deterioration Under the premise of preserving the channel energy as much as possible, the influence of noise and interference is fully eliminated, and the channel estimation accuracy is improved.
  • the power spectrum of the narrowband interference is only distributed in a narrow frequency band, and the frequency domain steering vector is frequency-domain deleted, a part of the interference spectrum is deleted, the influence of the narrowband interference is reduced, and the LS channel estimation is improved.
  • FIG. 1 is a flowchart of a method for estimating an LTE uplink system channel under interference conditions according to an embodiment of the present invention
  • FIG. 2 is a structural diagram of a baseband receiver of a typical LTE uplink system in an embodiment of the present invention
  • FIG. 3 is a structural diagram of an LTE uplink system channel estimation apparatus under interference conditions according to an embodiment of the present invention
  • FIG. 4 is a schematic structural diagram of a weighting submodule according to an embodiment of the present invention.
  • FIG. 5 is a performance comparison diagram of a common channel estimation method according to an embodiment of the present invention in a case where a dry signal ratio is changed and a signal to noise ratio is fixed;
  • FIG. 6 is a performance comparison diagram of a common channel estimation method in a case where the dry signal ratio is fixed and the signal to noise ratio is changed according to an embodiment of the present invention.
  • Embodiment 1 A method for estimating an LTE uplink system channel under interference conditions, including:
  • the S2 includes:
  • S201 Calculate a threshold value of the spectral line deletion according to the guiding vector Y m of the frequency domain baseband signal, and calculate the threshold value as follows:
  • the steering vector Y m is sorted by the square of the modulus, and the half of the spectrum with the smallest modulus value is selected. Since the narrowband signal is distributed in a narrow frequency band, it is considered that the partial line is not contaminated by narrowband interference, only noise and useful. signal. Then find the mean square of the partial line, and then multiply a factor ⁇ as the threshold, ⁇ is the ratio of the noise to the useful signal;
  • the step S4 includes:
  • the time domain tap of the channel does not exceed The first M elements, where M is the length of the CP (cyclic prefix); therefore, the time domain window is selected to filter out most of the interference and noise while saving all channel energy, and then transform the result into the frequency domain to obtain DFT.
  • the -Based channel estimation result is:
  • Diag() is a diagonal matrix
  • T 11 is an N SC order square matrix (N SC is the number of subcarriers occupied by the user)
  • N SC is the number of subcarriers occupied by the user
  • T 11 U ⁇ U H
  • U is a eigenvector obtained by eigenvalue decomposition of T 11 ;
  • ⁇ is a diagonal matrix, the number of non-zero elements is Q1, and Q1 ⁇ Q, Q is a rectangular window window length;
  • the least squares estimate is windowed in the feature domain:
  • the embodiment of the invention further provides a computer storage medium, wherein the computer storage medium stores computer executable instructions, and the computer executable instructions are used to execute the above method.
  • Embodiment 2 An LTE uplink system channel estimation apparatus under interference conditions, including:
  • the fast Fourier transform module 1 is configured to receive a pilot vector of the baseband signal, and obtain a pilot vector Y m of the frequency domain baseband signal through fast Fourier transform;
  • the frequency domain processing module 2 is configured to process Y m in the frequency domain, delete part of the interference spectrum line, and obtain a vector y m after frequency domain suppression;
  • the frequency domain processing module 2 includes:
  • the threshold generation sub-module 21 is configured to sort the guidance vector Y m of the frequency domain baseband signal by a square size, and select a half of the spectral line with the smallest modulus value; and obtain a modulus average of the selected spectral line. Then multiply a factor ⁇ as the threshold value, ⁇ is the ratio of the noise to the useful signal;
  • the spectral line deletion sub-module 22 is configured to compare a modulus value of the pilot vector Y m spectral line of the frequency domain baseband signal with a threshold value, and delete a spectral line greater than the threshold value, less than the The spectral line of the threshold remains unchanged, and the vector y m after the spectral line deletion is obtained.
  • the channel estimation module 3 includes:
  • the weighting sub-module 32 includes:
  • the storage unit 321 is configured to save the U, U H matrix and the non-zero number Q1 calculated in advance;
  • the calculating unit 322 is configured to calculate a U, U H matrix and a non-zero element number Q1, and calculate a weight matrix according to the stored U, U H and Q1 values and weight the LS estimated output vector to obtain a channel estimation value.
  • the calculation process of the U, U H, and Q1 is as follows:
  • the DFT-Based channel estimation result of the LS estimated output vector is:
  • Diag() is a diagonal matrix
  • T 11 is a square matrix of N SC order, and N SC is a number of subcarriers occupied by the user.
  • N SC is a number of subcarriers occupied by the user.
  • T 11 U ⁇ U H
  • U is a eigenvector obtained by eigenvalue decomposition of T 11 ;
  • ⁇ is a diagonal matrix
  • the number of non-zero elements is Q1
  • Q1 ⁇ Q is a rectangular window length
  • the calculating unit calculates the weight matrix according to the stored U, U H, and Q1 values and weights the LS estimation output vector to:
  • the computing unit performs windowing on the feature domain by least squares estimation:
  • a typical LTE uplink system baseband receiver includes: an FFT module, a frequency domain processing module, a channel estimation module, a demodulation module, and a sink module, where:
  • the FFT module performs FFT transformation on a baseband received signal vector
  • the demodulation module performs demodulation processing on the data to obtain bit level data.
  • an LTE uplink system channel estimation apparatus under interference conditions includes a fast Fourier transform module 1, a frequency domain processing module 2, and a channel estimation module 3.
  • the frequency domain processing module 2 includes a threshold.
  • Threshold generation sub-module 21 calculating a threshold value of the spectral line deletion according to the frequency domain receiving pilot signal vector
  • the spectral line deletion sub-module 22 compares the modulus value of the received vector Y m spectral line with the threshold value, and removes the spectral line larger than the threshold value, and the spectral line smaller than the threshold value remains unchanged, and the spectral line deletion is obtained. After the vector y m .
  • the channel estimation module includes a least squares estimation sub-module 31 and a weighting sub-module 32:
  • Weighting sub-module 32 Calculating the weight vector acts on the input vector to obtain a channel estimate.
  • the weighting sub-module 32 includes a storage unit 321 and a computing unit 322 configured to store a first calculated U, U H matrix and a non-zero number Q1; the computing unit 322 is configured to calculate a channel estimate.
  • ISR dry signal ratio
  • SNR signal to noise ratio
  • ISR fixed-signal ratio
  • SNR signal-to-noise ratio
  • all or part of the steps of the above embodiments may also be implemented by using an integrated circuit. These steps may be separately fabricated into individual integrated circuit modules, or multiple modules or steps may be fabricated into a single integrated circuit module. achieve.
  • the devices/function modules/functional units in the above embodiments may be implemented by a general-purpose computing device, which may be centralized on a single computing device or distributed over a network of multiple computing devices.
  • each device/function module/functional unit in the above embodiment When each device/function module/functional unit in the above embodiment is implemented in the form of a software function module and sold or used as a stand-alone product, it can be stored in a computer readable storage medium.
  • the above mentioned computer readable storage medium may be a read only memory, a magnetic disk or an optical disk or the like.
  • the above technical solution reduces the influence of narrowband interference, improves the accuracy of LS channel estimation, and improves the accuracy of channel estimation.

Abstract

La présente invention concerne un procédé et un dispositif permettant d'estimer un canal de système de liaison montante LTE en cas de brouillage. Le procédé consiste à : recevoir un vecteur de guidage d'un signal de bande de base, de sorte à obtenir un vecteur de guidage Ym d'un signal de bande de base du domaine fréquentiel par l'intermédiaire d'une transformée de Fourier rapide ; traiter Ym dans un domaine fréquentiel, et supprimer certaines lignes spectrales de brouillage, de sorte à obtenir un vecteur ym après suppression du domaine fréquentiel ; mettre en œuvre une estimation par les moindres carrés (LS) sur ym, de sorte à obtenir un vecteur de sortie d'estimation LS de hLS = X-1ym, X représentant un signal de référence de démodulation (DMRS) de liaison montante LTE ; et pondérer le vecteur de sortie d'estimation LS, de sorte à obtenir une valeur d'estimation de canal. La solution technique permet de préserver complètement l'énergie de canal tout en filtrant le bruit et en supprimant le brouillage, ce qui permet d'améliorer la précision d'estimation de canal tout en ayant l'avantage de présenter une complexité relativement faible.
PCT/CN2015/090735 2014-10-17 2015-09-25 Procédé et dispositif d'estimation de canal de système de liaison montante lte en cas de brouillage WO2016058476A1 (fr)

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