WO2020000613A1 - 信噪比确定方法及装置、信道均衡方法及装置 - Google Patents

信噪比确定方法及装置、信道均衡方法及装置 Download PDF

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Publication number
WO2020000613A1
WO2020000613A1 PCT/CN2018/101903 CN2018101903W WO2020000613A1 WO 2020000613 A1 WO2020000613 A1 WO 2020000613A1 CN 2018101903 W CN2018101903 W CN 2018101903W WO 2020000613 A1 WO2020000613 A1 WO 2020000613A1
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signal
noise ratio
noise
determining
autocorrelation function
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PCT/CN2018/101903
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English (en)
French (fr)
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魏急波
辜方林
黄圣春
熊俊
唐麒
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国防科技大学
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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
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03006—Arrangements for removing intersymbol interference
    • H04L25/03159—Arrangements for removing intersymbol interference operating in the frequency domain
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
    • G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B1/00—Details of transmission systems, not covered by a single one of groups H04B3/00 - H04B13/00; Details of transmission systems not characterised by the medium used for transmission
    • H04B1/69—Spread spectrum techniques
    • H04B1/707—Spread spectrum techniques using direct sequence modulation
    • H04B1/7097—Interference-related aspects
    • H04B1/7103—Interference-related aspects the interference being multiple access interference
    • H04B1/7105—Joint detection techniques, e.g. linear detectors
    • H04B1/71055—Joint detection techniques, e.g. linear detectors using minimum mean squared error [MMSE] detector
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0002—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0014—Carrier regulation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2662—Symbol synchronisation
    • H04L27/2663—Coarse synchronisation, e.g. by correlation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2668—Details of algorithms
    • H04L27/2673—Details of algorithms characterised by synchronisation parameters
    • H04L27/2675—Pilot or known symbols
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/0001—Arrangements for dividing the transmission path
    • H04L5/0003—Two-dimensional division
    • H04L5/0005—Time-frequency
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L5/00—Arrangements affording multiple use of the transmission path
    • H04L5/003—Arrangements for allocating sub-channels of the transmission path
    • H04L5/0058—Allocation criteria
    • H04L5/006—Quality of the received signal, e.g. BER, SNR, water filling
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/0014—Carrier regulation
    • H04L2027/0024—Carrier regulation at the receiver end
    • H04L2027/0026—Correction of carrier offset

Definitions

  • the technical field of the mobile communication system of the present invention more specifically, relates to a method and device for determining a signal-to-noise ratio at a receiving end of an information transmission system, and a method and device for channel equalization based on an MMSE equalizer.
  • multi-carrier transmission technologies In high-rate information transmission systems, basic transmission technologies can be divided into multi-carrier transmission technologies and single-carrier transmission technologies.
  • the most representative of multi-carrier transmission technology is OFDM (Orthogonal Frequency Division Multiplexing), and the single-carrier transmission technology is SCFDE (Single carrier frequency domain equalization).
  • OFDM Orthogonal Frequency Division Multiplexing
  • SCFDE Single carrier frequency domain equalization
  • the main process in this figure is as follows: channel coding of a binary bit stream, and after inserting constellation mapping, insert a guard interval (GI),
  • GI guard interval
  • the SCFDE system usually uses cyclic prefix (CP) or unique word (UW) as GI, and the signal enters the channel after shaping filtering, up conversion (DUC), and digital-to-analog conversion (D / A).
  • CP cyclic prefix
  • UW unique word
  • the receiving end is the reverse process of the sending end.
  • the receiving end signal is first subjected to analog-to-digital conversion (A / D), down-conversion (DDC), and matched filtering, and then the system performs timing synchronization and frequency synchronization.
  • a / D analog-to-digital conversion
  • DDC down-conversion
  • the signal After removing the guard interval, the signal is divided into two parts, one part is the pilot part, which is mainly used for channel estimation, and the other part is the data part, which is converted into the frequency domain by FFT and combined with the channel estimated by the pilot part.
  • the response and signal-to-noise ratio are equalized in the MMSE frequency domain, and then converted to the time domain by FFT, and then judged and decoded to obtain the original binary bit stream.
  • the channel equalization method used is minimum mean square error (MMSE) equalization.
  • MMSE equalizer takes into account both noise and channel effects, so it will not be amplified when there is deep fading in the transmission channel The effect of noise on the system.
  • the basic idea of the MMSE equalizer is to solve the equalizer coefficients to minimize the mean square value of the difference between the equalizer output and the desired signal.
  • the MMSE equalizer coefficient needs to accurately estimate the signal-to-noise ratio.
  • the current estimation of the signal-to-noise ratio is mainly divided into two categories, one is a data-assisted estimation method, and the other is a blind estimation method.
  • An object of the present invention is to provide a method and device for determining a signal-to-noise ratio at a receiving end of an information transmission system, and a method and device for channel equalization based on an MMSE equalizer, so as to reduce the calculation amount of the signal-to-noise ratio and achieve stable and reliable signal-to-noise ratio. estimate.
  • a method for determining a signal-to-noise ratio at a receiving end of an information transmission system is based on an information transmission system that realizes timing synchronization by using a repeated training sequence structure.
  • the method for determining the signal-to-noise ratio includes:
  • the peak value represents the sum of the average signal power and the noise average power
  • the valley value represents the average noise power
  • a signal-to-noise ratio is determined using the peak value and the valley value.
  • the peaks and valleys of the obtained autocorrelation function include:
  • k represents a time-related subscript
  • N is the length of the repeated training sequence
  • r (k + m) represents a signal delayed by m sampling periods from time k
  • m represents a delayed sampling period
  • s preamble (k) is the training sequence
  • w (k) is the noise
  • P signal is the average power of the signal
  • P noise is the average power of the noise
  • k ⁇ is the time index corresponding to the peak
  • k ⁇ is the corresponding to the valley value Time index.
  • the determining the signal-to-noise ratio by using the peak value and the valley value includes:
  • a channel equalization method based on an MMSE equalizer includes:
  • the received frequency domain signal is equalized by the MMSE equalizer coefficient and the scale correction factor to obtain a frequency domain signal after size correction.
  • the use of the average value of the channel frequency domain response, the average power of the signal, and the average power of the noise to determine the scale correction factor includes:
  • the rule for determining the scale correction factor is:
  • the signal-to-noise ratio determining device is based on an information transmission system that realizes timing synchronization by using a repeated training sequence structure.
  • the signal-to-noise ratio determining device includes:
  • a first obtaining module configured to obtain a peak value and a valley value of an autocorrelation function; the peak value represents a sum of an average signal power and a noise average power; and the valley value represents a noise average power;
  • the signal-to-noise ratio determination module is configured to determine the signal-to-noise ratio by using the peak value and the valley value.
  • the first acquisition module includes:
  • An autocorrelation function determining unit configured to determine an autocorrelation function R auto (k + N); the autocorrelation function Among them, k represents a time-related subscript, N is the length of the repeated training sequence, and r (k + m) is a signal delayed by m sampling periods at time k; m is a delayed sampling period; (.) * Indicates Conjugate operation
  • a first peak determination unit configured to determine a peak value of an autocorrelation function according to the autocorrelation function R auto (k + N) If the information transmission system does not have a frequency offset, the peak value for:
  • a valley value determining unit configured to determine a valley value of an autocorrelation function according to the autocorrelation function R auto (k + N)
  • s preamble (k) is the training sequence
  • w (k) is the noise
  • P signal is the average power of the signal
  • P noise is the average power of the noise
  • k ⁇ is the time index corresponding to the peak
  • k ⁇ is the corresponding to the valley value Time index.
  • the signal-to-noise ratio determination module is specifically configured to: use the peak value With the trough And the signal-to-noise ratio determination rule determines the signal-to-noise ratio SNR; wherein the signal-to-noise ratio determination rule is
  • a channel equalization device based on an MMSE equalizer includes:
  • a second obtaining module configured to obtain a signal-to-noise ratio obtained by the above-mentioned signal-to-noise ratio determining device and a frequency domain channel impulse response;
  • An equalizer coefficient determining module configured to determine an MMSE equalizer coefficient by using the signal-to-noise ratio and the frequency domain channel impulse response;
  • a scale correction factor determining module is used to determine the scale correction factor by using the average value of the channel frequency domain response, the average power of the signal, and the average power of the noise;
  • a signal equalization module is configured to perform equalization processing on the received frequency domain signal by using the MMSE equalizer coefficient and the scale correction factor to obtain a size-corrected frequency domain signal.
  • the scale correction factor determining module is specifically configured to determine a rule by using the scale correction factor and an average value of a channel frequency domain response.
  • the average power P signal of the signal and the average power P noise of the noise determine the scale correction factor ⁇ ;
  • the rule for determining the scale correction factor is:
  • the information transmission system based on this scheme implements time-frequency synchronization using a repeated training sequence structure.
  • Timing synchronization and carrier frequency offset estimation therefore, a method and device for determining the signal-to-noise ratio at the receiving end of an information transmission system provided by this solution, using the characteristics of signal and noise being independent of each other, without adding additional computational complexity,
  • the peak and valley values of the autocorrelation function achieve a stable and reliable estimation of the signal-to-noise ratio and reduce the amount of calculation of the signal-to-noise ratio.
  • this solution provides a channel equalization method based on the MMSE equalizer. This method obtains a stable and reliable The signal-to-noise ratio is used to determine the MMSE equalizer coefficient, and then the scale correction factor is determined by the average value of the channel frequency domain response and the average power of the signal and noise, so as to maintain the good equalization performance of the MMSE equalizer while passing the constellation of the output signal
  • the scale correction achieves scale stability, which facilitates the normal work of the subsequent soft solution module.
  • FIG. 1 is a schematic diagram of a transmission process of an SCFDE system in the prior art
  • FIG. 2 is a schematic flowchart of a method for determining a signal-to-noise ratio at a receiving end of an information transmission system according to an embodiment of the present invention
  • FIG. 3 is a schematic diagram of a signal-to-noise ratio estimation based on a structure of a repetitive training sequence disclosed in an embodiment of the present invention
  • FIG. 4 is a schematic diagram showing a relationship between a real value and an estimated value of an SNR disclosed in an embodiment of the present invention
  • 5a is a constellation diagram of an output signal of an MMSE equalizer with a signal-to-noise ratio of 4 dB according to an embodiment of the present invention
  • 5b is a constellation diagram of an output signal of an MMSE equalizer with a signal-to-noise ratio of 12B disclosed in an embodiment of the present invention
  • FIG. 6 is a schematic flowchart of a MMSE equalizer-based channel equalization method disclosed in an embodiment of the present invention
  • FIG. 7 is a block diagram of a MMSE channel equalization method disclosed by an embodiment of the present invention.
  • FIG. 8a is a constellation diagram after a scale change under the condition that the signal-to-noise ratio is 4 dB according to an embodiment of the present invention
  • FIG. 8b is an expected constellation diagram under a condition that a signal-to-noise ratio is 4 dB disclosed in an embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of an apparatus for determining a signal-to-noise ratio at a receiving end of an information transmission system according to an embodiment of the present invention.
  • FIG. 10 is a schematic structural diagram of a channel equalization device based on an MMSE equalizer disclosed in an embodiment of the present invention.
  • the embodiment of the invention discloses a method and a device for determining a signal-to-noise ratio at a receiving end of an information transmission system, and a method and a device for channel equalization based on an MMSE equalizer, so as to reduce the calculation amount of the signal-to-noise ratio and realize stable and reliable signal-to-noise ratio estimate.
  • the transmitted signal is s (k)
  • its average power is 1
  • the sampling frequency is 1 / T
  • the channel impulse response of s (k) is h (l)
  • l 0, 1, ... L-1
  • L is the number of taps of the channel impulse response
  • w (k) is additive white Gaussian noise
  • P noise is P noise .
  • the time-domain receiving signal r (k) can be expressed as:
  • * represents linear convolution. Due to the introduction of a cyclic prefix, a linear convolution of the signal s (k) and the channel impulse response h (k) can be converted into a cyclic convolution. That is, when the cyclic prefix duration T G satisfies T G ⁇ max , ⁇ max is the maximum delay extension, and the sending and receiving parts in the system are strictly synchronized. After removing the cyclic prefix, we get:
  • N F the number of FFT points.
  • R (k) H (k) S (k) + W (k), 0 ⁇ k ⁇ N F -1 ... briefly.. (3)
  • Equation (3) is the basic starting point for channel estimation and frequency domain equalization in the SCFDE system.
  • the equalized MSE is derived as
  • the minimum mean square error MMSE equalizer is obtained as
  • P signal represents the average power of the signal
  • P noise represents the average power of the noise
  • SNR represents the signal-to-noise ratio
  • a method for determining a signal-to-noise ratio at a receiving end of an information transmission system is provided.
  • the method for determining the signal-to-noise ratio is based on an information transmission system that implements timing synchronization by using a repeated training sequence structure.
  • Methods for determining the noise ratio include:
  • information transmission systems SCFDE, OFDM, etc. often use repeated pilot structures to solve the problem of time-frequency synchronization, and in the implementation of the time-frequency synchronization algorithm based on the repeated training sequence structure, the correlation of the autocorrelation function is needed.
  • the parameters are determined. Specifically, the position and phase of the maximum value of the autocorrelation function are used to complete symbol timing synchronization and carrier frequency offset estimation, respectively. Therefore, this solution can determine the signal-to-noise ratio based on the peaks and valleys of the autocorrelation function without adding additional calculation complexity while the system completes time-frequency synchronization, thereby solving the problem of estimating the signal-to-noise ratio and facilitating hardware implementation.
  • the peak and valley of the autocorrelation function can determine the signal-to-noise ratio because the peak of the autocorrelation function represents the sum of the average power of the signal and the average power of the noise, and the valley of the autocorrelation function represents the average of the noise Power, so, as defined by the signal-to-noise ratio, With trough And the SNR determination rule to determine the SNR;
  • obtaining the peak and valley values of the autocorrelation function includes:
  • k represents a time-related subscript
  • N is the length of a repeated training sequence
  • r (k + m) is a signal delayed by m sampling periods at time k
  • m represents a delayed sampling period
  • s preamble (m) is the training sequence
  • w (m) is the noise
  • P signal is the average power of the signal
  • P noise is the average power of the noise
  • k ⁇ is the time index corresponding to the peak
  • k ⁇ is the corresponding to the valley value Time index.
  • FIG. 3 a schematic diagram of the SNR estimation based on the structure of the repeated training sequence is provided for this embodiment.
  • the actual system may have multiple repeated training sequences, but the multiple repeated sequences will not estimate the signal to noise ratio.
  • the method brings qualitative changes, and the valley value and peak value can be obtained from the results of the first two repeated sequences.
  • only two repeated training sequences are used as an example for description. Assuming that the length of the repeated training sequence is N, the autocorrelation function of the N sampling time instants of the received signal delay can be obtained:
  • s preamble (m) represents the training sequence
  • P signal represents the average power of the signal
  • P noise represents the average power of the noise
  • k ⁇ is the time index corresponding to the peak
  • the frequency offset does not affect the algorithm for calculating the signal-to-noise ratio.
  • the frequency offset only causes the peak of the autocorrelation function to carry a phase related to the frequency offset value, and this phase value can be used to implement the frequency offset estimation.
  • the noise in the channel is white Gaussian noise and is independent of the transmitted signal.
  • the value R auto (k + N) of the bottom of the autocorrelation function can be obtained as:
  • this scheme realizes frequency offset estimation and signal-to-noise ratio estimation by finding the peak value of the delayed autocorrelation function value of the received signal.
  • the absolute value of the peak value is used to estimate the signal-to-noise ratio, and the phase value of the peak value can be used to Achieve frequency offset estimation.
  • FIG. 4 a schematic diagram of the relationship between the true value and the estimated value of the SNR is disclosed in this embodiment.
  • the straight line is the estimated value and the broken line is the true value. It can be seen that the estimated value and the true value show a substantially linear relationship. Therefore, the present invention can realize a stable and reliable estimation of the system signal-to-noise ratio.
  • the MMSE equalization algorithm shown in formula (6) will cause the signal constellation scale after the equalization to change with factors such as the signal-to-noise ratio. See Figure 5a for the constellation diagram of the output signal of the MMSE equalizer at a signal-to-noise ratio of 4dB. See Figure 5b for the constellation diagram of the output signal of the MMSE equalizer at a signal-to-noise ratio of 12B. It can be seen that As the ratio increases, the constellation scale of the equalizer output signal becomes smaller. The smaller scale of the constellation chart will cause subsequent soft solution modules to not work properly. In addition, in the actual implementation process, it is necessary to introduce automatic gain control (AGC) to ensure the received signal level of the system.
  • AGC automatic gain control
  • AGC does not guarantee that the average power of the received signal is a fixed value. It can only ensure that the average power of the received signal is within a certain range. This will also cause the size of the channel estimation value to change. This change will also cause the constellation of the output signal of the MMSE equalizer to change.
  • this solution also provides a channel equalization method based on the MMSE equalizer.
  • the signal-to-noise ratio is obtained by using the method for determining a signal-to-noise ratio described in any one of the foregoing embodiments.
  • a specific method for obtaining the signal-to-noise ratio refer to the description of the method for determining a signal-to-noise ratio, which is not described herein.
  • the MMSE equalizer coefficient in this solution is calculated in the same manner as in the above formula (6), that is, the MMSE equalizer coefficient C MMSE (k) is:
  • S203 Determine the scale correction factor by using the average value of the channel frequency domain response, the average power of the signal, and the average power of the noise;
  • the use of the average value of the channel frequency domain response, the average power of the signal, and the average power of the noise to determine the scale correction factor includes:
  • the rule for determining the scale correction factor is:
  • the constellation scale of the output signal of the LS equalizer does not change with factors such as the signal-to-noise ratio.
  • the MMSE equalizer shown in equation (6) is transformed into the equalizer shown in equation (13). It can be seen that the MMSE equalizer shown in equation (13) is compared with the LS equalizer shown in equation (15). , While retaining the MMSE equalizer to obtain better performance by considering the influence of the signal-to-noise ratio, and by introducing a scale correction factor ⁇ , the nature of the LS equalizer output signal constellation scale does not change with the signal-to-noise ratio can be eliminated. The scale change of the constellation of the output signal of the equalizer caused by the noise ratio and channel estimation.
  • MMSE channel equalization method disclosed in this embodiment is shown. It consists of 3 parts, namely MMSE equalization unit, scale correction factor calculation unit and scale correction unit.
  • the MMSE equalization unit uses the frequency-domain received signal Y, frequency-domain channel response estimate H, signal power P, and noise power N to perform processing according to the algorithm shown in Equation (12) to obtain an equalized signal constellation diagram.
  • the scale correction factor calculation unit uses the frequency domain channel response estimation value H, the signal power P, and the noise power N to process according to the algorithm shown in Equation (13) to obtain a scale correction factor ⁇ .
  • the scale correction unit uses the scale correction factor ⁇ and the equalized signal constellation Get scaled constellation
  • FIG. 8a is a constellation diagram after the scale change under the condition that the signal-to-noise ratio is 4dB.
  • FIG. 8b which is the expected constellation diagram that the signal-to-noise ratio is 4dB.
  • the scale of the constellation of the output signal of the transmitter does not change with changes in factors such as signal-to-noise ratio and AGC signal adjustment, and the difference is small compared with the expected constellation.
  • the device for determining the signal-to-noise ratio provided in the embodiment of the present invention is described below.
  • the device for determining the signal-to-noise ratio described below and the method for determining the signal-to-noise ratio described above may refer to each other.
  • an apparatus for determining a signal-to-noise ratio at a receiving end of an information transmission system is based on an information transmission system that realizes timing synchronization by using a repeated training sequence structure, and the signal-to-noise ratio is determined.
  • the device includes:
  • a first obtaining module 110 is configured to obtain a peak value and a valley value of an autocorrelation function; the peak value represents a sum of an average signal power and a noise average power; and the valley value represents a noise average power;
  • the signal-to-noise ratio determining module 120 is configured to determine a signal-to-noise ratio by using the peak value and the valley value.
  • the first obtaining module 110 includes:
  • An autocorrelation function determining unit configured to determine an autocorrelation function R auto (k + N); the autocorrelation function Among them, k represents a time-related subscript, N is the length of the repeated training sequence, and r (k + m) is a signal delayed by m sampling periods at time k; m is a delayed sampling period; (.) * Indicates Conjugate operation
  • a first peak determination unit configured to determine a peak value of an autocorrelation function according to the autocorrelation function R auto (k + N) If the information transmission system does not have a frequency offset, the peak value for:
  • a valley value determining unit configured to determine a valley value of an autocorrelation function according to the autocorrelation function R auto (k + N)
  • s preamble (k) is the training sequence
  • w (m) is the noise
  • P signal is the average power of the signal
  • P noise is the average power of the noise
  • k ⁇ is the time index corresponding to the peak
  • k ⁇ is the corresponding to the valley value Time index.
  • the signal-to-noise ratio determination module is specifically configured to: use the peak value With the trough And a signal-to-noise ratio determination rule to determine a signal-to-noise ratio SNR, where the signal-to-noise ratio determination rule is:
  • This embodiment also discloses a signal-to-noise ratio determination device, including: a memory for storing a computer program; and a processor for implementing the steps of the above-mentioned method for determining the signal-to-noise ratio when the computer program is executed.
  • This embodiment also discloses a computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the foregoing method for determining a signal-to-noise ratio are implemented.
  • the storage medium may include: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc. medium.
  • the channel equalization device provided by the embodiment of the present invention is described below.
  • the channel equalization device described below and the channel equalization method described above may refer to each other.
  • an MMSE equalizer-based channel equalization device includes:
  • a second acquiring module 210 configured to acquire a signal-to-noise ratio obtained by the signal-to-noise ratio determining device and a frequency domain channel impulse response;
  • An equalizer coefficient determining module 220 configured to determine an MMSE equalizer coefficient by using the signal-to-noise ratio and the frequency domain channel impulse response;
  • a scale correction factor determining module 230 is configured to determine a scale correction factor by using the average value of the channel frequency domain response, the average power of the signal, and the average power of the noise;
  • the signal equalization module 240 is configured to perform equalization processing on the received frequency domain signal by using the MMSE equalizer coefficient and the scale correction factor to obtain a size-corrected frequency domain signal.
  • the scale correction factor determining module is specifically configured to determine a rule by using the scale correction factor and an average value of a channel frequency domain response.
  • the average power P signal of the signal and the average power P noise of the noise determine the scale correction factor ⁇ , where the rule for determining the scale correction factor is:
  • the scale correction factor determination module 230 in this embodiment can be understood as the scale correction factor calculation unit in the above-mentioned channel equalization method to realize the determination of the scale correction factor;
  • the signal equalization module 240 in this embodiment includes the above-mentioned channels.
  • the MMSE equalization unit and scale correction unit in the equalization method realize the determination of the signal constellation and the correction of the signal constellation.
  • This embodiment also discloses a MMSE equalizer-based channel equalization device, including: a memory for storing a computer program; and a processor for implementing the steps of the above-mentioned channel equalization method when the computer program is executed.
  • This embodiment also discloses a computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium.
  • the computer program is executed by a processor, the steps of the foregoing channel equalization method are implemented.
  • the storage medium may include: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc. medium.

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Abstract

一种信息传输系统接收端的信噪比确定方法及装置，基于采用重复训练序列结构实现时频同步的信息传输系统，利用信号与噪声相互独立的特性，在不增加额外计算复杂度的条件下，通过自相关函数的峰值和谷值实现对信噪比的稳定可靠估计，减少了信噪比的计算量。进一步，本发明还公开了一种基于MMSE均衡器的信道均衡方法及装置，通过上述信噪比确定方式获取稳定可靠的信噪比来确定MMSE均衡器系数，再通过信道频域响应的平均值、信号与噪声的平均功率确定尺度校正因子，以便在保留MMSE均衡器良好的均衡性能同时，使输出信号的星座图通过尺度校正达到尺度稳定，便于后续软解模块的正常工作。

Description

信噪比确定方法及装置、信道均衡方法及装置
本申请要求于2018年06月26日提交中国专利局、申请号为201810670194.4、发明名称为“信噪比确定方法及装置、信道均衡方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本发明移动通信系统技术领域，更具体地说，涉及一种信息传输系统接收端的信噪比确定方法及装置、基于MMSE均衡器的信道均衡方法及装置。
背景技术
在高速率信息传输系统中，基本的传输技术可以分为多载波传输技术及单载波传输技术。多载波传输技术中最具代表性的是OFDM(Orthogonal Frequency Division Multiplexing，正交频分复用技术)，单载波传输技术则为SCFDE(Single carrier frequency domain equalization，单载波频域均衡系统)。以SCFDE系统为例，参见图1，为现有技术中的SCFDE系统传输过程示意图，在该图中主要过程如下：对二进制比特流进行信道编码，经过星座映射之后，插入保护间隔(GI)，SCFDE系统通常用循环前缀(CP)或者独特字(UW)为GI，信号通过成型滤波、上变频(DUC)、数模转换(D/A)之后进入信道。相反的，接收端是发送端的逆过程。接收端信号首先经过模数转换(A/D)、下变频(DDC)、匹配滤波后，对系统进行定时同步和频率同步。在去除保护间隔之后，将信号分为两部分，一部分是导频部分，该部分主要用于信道估计，另一部分是数据部分，该部分通过FFT转换成频域，结合导频部分估计得到的信道响应和信噪比进行MMSE频域均衡，之后经过FFT转换到时域再经过判决和解码得到原始二进制比特流。
在SCFDE系统中，使用的信道均衡方法为最小均方误差(minimum  mean square error,MMSE)均衡，采用MMSE均衡器同时考虑了噪声和信道的影响，因此当传输信道存在深衰落时也不会放大噪声对系统的影响。MMSE均衡器的基本思想是求解均衡器系数使均衡器输出与期望信号之差的均方值达到最小，MMSE均衡器系数需要准确的估计信噪比。现有关于信噪比的估计主要分为两大类，一类是基于数据辅助的估计方法，一类是盲估计方法。现有实际系统中大都采用基于数据辅助的方法，其中以Boumard算法最为典型。它的基本思想是利用两个前导符号估计出噪声功率，但是该方法的计算复杂度比较大，且它直接估计的是噪声功率，信噪比还需要进一步估计实现。
因此，如何减低信噪比的计算量，实现对信噪比的稳定可靠估计是本领域技术人员需要解决的问题。
发明内容
本发明的目的在于提供一种信息传输系统接收端的信噪比确定方法及装置、基于MMSE均衡器的信道均衡方法及装置，以实现减低信噪比的计算量，实现对信噪比的稳定可靠估计。
为实现上述目的，本发明实施例提供了如下技术方案：
一种信息传输系统接收端的信噪比确定方法，所述信噪比确定方法基于采用重复训练序列结构实现时序同步的信息传输系统，所述信噪比确定方法包括：
获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
利用所述峰值与所述谷值确定信噪比。
其中，所述获取自相关函数的峰值和谷值包括：
确定自相关函数R auto(k+N)；所述自相关函数
Figure PCTCN2018101903-appb-000001
其中，k表示与时间有关的下 标，N为重复训练序列的长度，r(k+m)表示与k时刻延后m个采样周期的信号；m表示延迟的采样周期；(.) *表示共轭运算；
根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000002
若所述信息传输系统不存在频偏，则峰值
Figure PCTCN2018101903-appb-000003
为：
Figure PCTCN2018101903-appb-000004
若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
Figure PCTCN2018101903-appb-000005
为：
Figure PCTCN2018101903-appb-000006
根据所述自相关函数R auto(k+N)确定自相关函数的谷值
Figure PCTCN2018101903-appb-000007
Figure PCTCN2018101903-appb-000008
其中，s preamble(k)为训练序列，w(k)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；k ▽为与谷值对应的时间下标。
其中，利用所述峰值与所述谷值确定信噪比，包括：
利用所述峰值
Figure PCTCN2018101903-appb-000009
与所述谷值
Figure PCTCN2018101903-appb-000010
以及信噪比确定规则确定信噪比SNR；其中，所述信噪比确定规则为：
Figure PCTCN2018101903-appb-000011
其中，|·|表示绝对值运算。
一种基于MMSE均衡器的信道均衡方法，包括：
获取通过上述的信噪比确定方法得到的信噪比，以及频域信道冲激响应；
利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
其中，所述利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子，包括：
利用尺度校正因子确定规则，以及信道频域响应的平均值
Figure PCTCN2018101903-appb-000012
信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；
其中，所述尺度校正因子确定规则为：
Figure PCTCN2018101903-appb-000013
其中，所述信噪比确定装置基于采用重复训练序列结构实现时序同步的信息传输系统，所述信噪比确定装置包括：
第一获取模块，用于获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
信噪比确定模块，用于利用所述峰值与所述谷值确定信噪比。
其中，所述第一获取模块包括：
自相关函数确定单元，用于确定自相关函数R auto(k+N)；所述自相关函数
Figure PCTCN2018101903-appb-000014
其中，k表示与时间有关的下标，N为重复训练序列的长度，r(k+m)为与k时刻延后m个采样周期的信号；m为延迟的采样周期；(.) *表示共轭运算；
第一峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000015
若所述信息传输系统不存在频偏，则峰值
Figure PCTCN2018101903-appb-000016
为：
Figure PCTCN2018101903-appb-000017
第二峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000018
若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
Figure PCTCN2018101903-appb-000019
为：
Figure PCTCN2018101903-appb-000020
谷值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的谷值
Figure PCTCN2018101903-appb-000021
Figure PCTCN2018101903-appb-000022
其中，s preamble(k)为训练序列，w(k)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；k ▽为与谷值对应的时间下标。
其中，所述信噪比确定模块具体用于：利用所述峰值
Figure PCTCN2018101903-appb-000023
与所述谷值
Figure PCTCN2018101903-appb-000024
以及信噪比确定规则确定信噪比SNR；其中，所述信噪比确定规则为：
Figure PCTCN2018101903-appb-000025
其中，|·|表示绝对值运算。
一种基于MMSE均衡器的信道均衡装置，包括：
第二获取模块，用于获取通过上述的信噪比确定装置得到的信噪比，以及频域信道冲激响应；
均衡器系数确定模块，用于利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
尺度校正因子确定模块，用于利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
信号均衡模块，用于通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
其中，所述尺度校正因子确定模块具体用于利用尺度校正因子确定规则，以及信道频域响应的平均值
Figure PCTCN2018101903-appb-000026
信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；
其中，所述尺度校正因子确定规则为：
Figure PCTCN2018101903-appb-000027
通过以上方案可知，本方案基于的信息传输系统是采用重复训练序列结构实现时频同步的，在该过程中本身便需要寻找自相关函数的最大值，然后利用最大值的位置和相位分别完成符号定时同步与载波频偏估计；因此，本方案提供的一种信息传输系统接收端的信噪比确定方法及装置，利用信号与噪声相互独立的特性，在不增加额外计算复杂度的条件下，通过自相关函数的峰值和谷值实现对信噪比的稳定可靠估计，减少了信噪比的计算量。
进一步，本方案为了解决MMSE均衡器输出的信号星座图尺度随信噪比等因素发生变化，提供了一种基于MMSE均衡器的信道均衡方式，该方式通过上述信噪比确定方式获取稳定可靠的信噪比来确定MMSE均衡器系数，再通过信道频域响应的平均值、信号与噪声的平均功率确定尺度校正因子，以便在保留MMSE均衡器良好的均衡性能同时，使输出信号的星座图通过尺度校正达到尺度稳定，便于后续软解模块的正常工作。
附图说明
为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为现有技术中的SCFDE系统传输过程示意图；
图2为本发明实施例公开的一种信息传输系统接收端的信噪比确定方法流程示意图；
图3为本发明实施例公开的一种基于重复训练序列结构的信噪比估计原理图；
图4为本发明实施例公开的SNR的真实值与估计值的关系示意图；
图5a为本发明实施例公开的信噪比为4dB条件下MMSE均衡器输出信号的星座图；
图5b为本发明实施例公开的信噪比为12B条件下MMSE均衡器输出信号的星座图；
图6为本发明实施例公开的一种基于MMSE均衡器的信道均衡方法流程示意图；
图7为本发明实施例公开的一种MMSE信道均衡方法框图；
图8a为本发明实施例公开的信噪比为4dB的条件下尺度变化后的星座图；
图8b为本发明实施例公开的信噪比为4dB的条件的期望星座图；
图9为本发明实施例公开的一种信息传输系统接收端的信噪比确定装置结构示意图；
图10为本发明实施例公开的一种基于MMSE均衡器的信道均衡装置结构示意图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
本发明实施例公开了一种信息传输系统接收端的信噪比确定方法及装置、基于MMSE均衡器的信道均衡方法及装置，以实现减低信噪比的计算量，实现对信噪比的稳定可靠估计。
可以理解的是，假设发送信号为s(k)，其平均功率为1，采样频率为1/T，s(k)的信道冲激响应为h(l)，l＝0,1,…,L-1，其中L为信道冲激响应的抽头数目。w(k)为加性高斯白噪声，它的平均功率为P noise。时域接收端接收信号r(k)可以表示为：
Figure PCTCN2018101903-appb-000028
其中，*表示线性卷积。由于循环前缀的引入，信号s(k)与信道冲激响应h(k)的线性卷积可以转化为循环卷积。即当循环前缀持续时间T G满足T G≥τ max，τ max为最大时延扩展，并且系统中的收发部分严格同步，除去循环前缀之后得到：
Figure PCTCN2018101903-appb-000029
其中，
Figure PCTCN2018101903-appb-000030
表示循环卷积，N F表示FFT点数。对式(2)进行FFT变换，可得接收信号r(k)的频域表达式：
R(k)＝H(k)S(k)+W(k),0≤k≤N F-1…………………(3)
其中，R(k)、H(k)、S(k)和W(k)分别表示r(k)、h(k)、s(k)和w(k)的频域表示。式(3)是SCFDE系统进行信道估计和频域均衡的基本出发点。
假设均衡器系数为C(k)，则均衡后的频域输出为：
Figure PCTCN2018101903-appb-000031
根据均方误差MSE的定义，推导出均衡后的MSE为
Figure PCTCN2018101903-appb-000032
当均方误差MSE取得最小值时，得到最小均方误差MMSE均衡器为
Figure PCTCN2018101903-appb-000033
其中，P signal表示信号的平均功率，P noise表示噪声的平均功率，SNR表示信噪比。根据式(6)所示MMSE均衡器得知，实现MMSE均衡器需要 解决以下两个问题：一是信噪比的准确估计，它是实现MMSE均衡的关键之一；二是系统的自动增益控制(AGC)并不能保证接收信号的平均功率处于某一特定值，而是只能保证位于某一区间，因此会使信号平均功率、噪声平均功率、信道估计值等参数的相对值会发生变化，从而会导致均衡后输出星座图尺度发生变化，这种尺度变化会导致软解模块不能正常工作，因此需要克服这种尺度变化。
目前，现有的基于数据辅助的信噪比估计方法大都单独针对信噪比估计问题，没有从整个系统考虑的情形，往往需要单独设计帧结构和比较大的计算复杂度。因此，参见图2，为本发明实施例提供的一种信息传输系统接收端的信噪比确定方法，所述信噪比确定方法基于采用重复训练序列结构实现时序同步的信息传输系统，所述信噪比确定方法包括：
S101、获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
需要说明的是，信息传输系统SCFDE、OFDM等往往采用重复导频结构用于解决时频同步问题，并且系统在基于重复训练序列结构的时频同步算法实现过程中，需要对自相关函数的相关参数进行确定，具体来说是利用自相关函数最大值的位置和相位分别完成符号定时同步与载波频偏估计。因此，本方案在系统完成时频同步的同时，不用增加额外的计算复杂度就可以根据自相关函数的峰值和谷值确定信噪比，从而解决信噪比的估计问题，便于硬件实现。
S102、利用所述峰值与所述谷值确定信噪比。
可以理解的是，之所以自相关函数的峰值与谷值能确定信噪比，是因为在自相关函数的峰值代表信号平均功率与噪声平均功率之和，而自相关函数的谷值代表噪声平均功率，因此，根据信噪比的定义，利用峰值
Figure PCTCN2018101903-appb-000034
与谷值
Figure PCTCN2018101903-appb-000035
以及信噪比确定规则确定信噪比SNR；
其中，所述信噪比确定规则为：
Figure PCTCN2018101903-appb-000036
可以看出，本方案通过对自相关函数峰值和谷值的简单运算，便能实现对信噪比的准确估计。
基于上述实施例，在本实施例中，获取自相关函数的峰值和谷值包括：
确定自相关函数R auto(k+N)；所述自相关函数
Figure PCTCN2018101903-appb-000037
其中，k表示与时间有关的下标，N为重复训练序列的长度，r(k+m)为与k时刻延后m个采样周期的信号；m表示延迟的采样周期；(.) *表示共轭运算；
根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000038
若所述信息传输系统不存在频偏，则峰值
Figure PCTCN2018101903-appb-000039
为：
Figure PCTCN2018101903-appb-000040
若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
Figure PCTCN2018101903-appb-000041
为：
Figure PCTCN2018101903-appb-000042
根据所述自相关函数R auto(k+N)确定自相关函数的谷值
Figure PCTCN2018101903-appb-000043
Figure PCTCN2018101903-appb-000044
其中，s preamble(m)为训练序列，w(m)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；k ▽为与谷值对应的时间下标。
参见图3，为本实施例提供一种基于重复训练序列结构的信噪比估计原理图，需要说明的是，实际系统可能会存在多段重复训练序列，但是多段重复序列不会给信噪比估计方法带来质的变化，其谷值与峰值分别取前两段重复序列的结果即可。在本实施例中仅以两段重复训练序列为例进行描述；假设重复训练序列的长度为N，则计算接收信号的延时N个采样时刻的自相关函数可得：
Figure PCTCN2018101903-appb-000045
其中，(.) *表示共轭运算。在计算自相关函数的峰值时，存在信息传输系统收、发端不存在频偏以及存在频偏这两种情况；如若信息传输系统收、发端不存在频偏，则自相关峰值
Figure PCTCN2018101903-appb-000046
可以表示为：
Figure PCTCN2018101903-appb-000047
其中，s preamble(m)表示训练序列，P signal表示信号平均功率，P noise表示噪声平均功率；k Δ为与峰值对应的时间下标；。并且可以发现，峰值出现过程呈现山坡状，且由山底到山顶需要N个采样周期。
如若信息传输系统收、发端存在频偏，假设收、发端之间存在归一化频偏ε＝f offset/Δf，其中f offset表示载波偏移，Δf表示子载波频率间隔。在此情况下，自相关峰值
Figure PCTCN2018101903-appb-000048
可以表示为
Figure PCTCN2018101903-appb-000049
可以发现，频偏并不会对计算信噪比的算法产生影响，频偏只会导致自相关函数的峰值携带一个与频偏值相关的相位，该相位值可用于实现频偏估计。
另一方面，假设信道中噪声为高斯白噪声，且与发送信号相互独立。在此基础上，可以得到自相关函数山底的值R auto(k+N)可以表示为：
Figure PCTCN2018101903-appb-000050
进一步，根据信噪比的定义，利用峰值
Figure PCTCN2018101903-appb-000051
与谷值
Figure PCTCN2018101903-appb-000052
得到信噪比SNR；
Figure PCTCN2018101903-appb-000053
其中，|·|表示绝对值运算。
综上可以看出，本方案通过寻找接收信号延时自相关函数值的峰值实现频偏估计与信噪比估计，其中峰值的绝对值用于实现信噪比估计，而峰值的相位值可用于实现频偏估计。参见图4，为本实施例公开了SNR的真实值与估计值的关系示意图，其中，直线为估计值，折线为真实值，可以看出，估计值与真实值之间基本呈现出线性关系，因此本发明能够实现对系统信噪比的稳定可靠估计。
需要说明的是，公式(6)所示的MMSE均衡算法会导致均衡后的信号星座图尺度随信噪比等因素发生变化。参见图5a，为信噪比为4dB条件下MMSE均衡器输出信号的星座图，参见图5b，为信噪比为12B条件下 MMSE均衡器输出信号的星座图；可以看出，随着信噪比的增加，均衡器输出信号的星座图尺度会变小。星座图尺度变小会导致后续的软解模块不能正常工作。此外，在实际实现过程中，需要引入自动增益控制(AGC)来保证系统的接收信号电平，然而AGC并能保证接收信号的平均功率为定值，只能保证接收信号平均功率位于某一区间，这还会导致信道估计值的大小也会发生变化，这种变化也会导致MMSE均衡器输出信号星座图发生变化。
因此，参见图6，为了解决均衡后的信号星座图尺度随信噪比等因素发生变化，导致后续软解模块不能正常工作的问题，本方案还提供了一种基于MMSE均衡器的信道均衡方法，包括：
S201、获取通过信噪比以及频域信道冲激响应；
具体的，该信噪比为通过上述任意一项实施例所述的信噪比确定方法求得的，具体求取方法详见信噪比确定方法实施例所述，在此并不赘述。
S202、利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
具体的，本方案中的MMSE均衡器系数与上述公式(6)中的计算方式相同，即MMSE均衡器系数C MMSE(k)为：
Figure PCTCN2018101903-appb-000054
只不过在公式(12)中的信噪比SNR，为通过本实施例所述的信噪比确定方法求得的。
S203、利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
其中，所述利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子，包括：
利用尺度校正因子确定规则，以及信道频域响应的平均值
Figure PCTCN2018101903-appb-000055
信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；
其中，所述尺度校正因子确定规则为：
Figure PCTCN2018101903-appb-000056
具体的，在本实施例中，对公式(6)所示的计算MMSE均衡器系数的方法进行变换，具体过程如下：
Figure PCTCN2018101903-appb-000057
其中，
Figure PCTCN2018101903-appb-000058
S204、通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
为了进一步更好理解所述MMSE均衡器为何能够实现尺度校正，这里借鉴式(15)所示LS均衡算法来说明
Figure PCTCN2018101903-appb-000059
可以证明LS均衡器输出信号星座图尺度不会随信噪比等因素变化。基于上述考虑，将式(6)所示的MMSE均衡器变换为式(13)所示均衡器，可以看出式(13)所示MMSE均衡器相较于式(15)所示LS均衡器，在保留了MMSE均衡器通过考虑信噪比的影响获得更优性能的同时，通过引入尺度校正因子Θ，获得了LS均衡器输出信号星座图尺度不随信噪比变化的性质，从而可以消除信噪比、信道估计值等引起的均衡器输出信号星座图的尺度变化。
参见图7，为本实施例公开的一种MMSE信道均衡方法框图。包括3个部分组成，分别是MMSE均衡单元、尺度校正因子计算单元和尺度校正单元。MMSE均衡单元利用频域接收信号Y、频域信道响应估计值H、信号功率P和噪声功率N按照式(12)所示算法进行处理，获得均衡后的信号星座图
Figure PCTCN2018101903-appb-000060
尺度校正因子计算单元利用频域信道响应估计值H、信号功率P和噪声功率N按照式(13)所示算法进行处理，获得尺度校正因子Θ。尺度校正单元利用尺度校正因子Θ和均衡后的信号星座图
Figure PCTCN2018101903-appb-000061
获得尺度校正后的星座图
Figure PCTCN2018101903-appb-000062
参见图8a，为信噪比为4dB的条件下尺度变化后的星座图，参见图8b，为信噪比为4dB的条件的期望星座图；可以看出，本发明通过尺度校正的方式使均衡器输出信号的星座图尺度不会随着信噪比、AGC信号调整等因素的变化而变化，与期望星座图相比差异较小。
下面对本发明实施例提供的信噪比确定装置进行介绍，下文描述的信噪比确定装置与上文描述的信噪比确定方法可以相互参照。
参见图9，本发明实施例提供的一种信息传输系统接收端的信噪比确定装置，所述信噪比确定装置基于采用重复训练序列结构实现时序同步的信息传输系统，所述信噪比确定装置包括：
第一获取模块110，用于获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
信噪比确定模块120，用于利用所述峰值与所述谷值确定信噪比。
其中，所述第一获取模块110包括：
自相关函数确定单元，用于确定自相关函数R auto(k+N)；所述自相关函数
Figure PCTCN2018101903-appb-000063
其中，k表示与时间有关的下标，N为重复训练序列的长度，r(k+m)为与k时刻延后m个采样周期的信号；m为延迟的采样周期；(.) *表示共轭运算；
第一峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000064
若所述信息传输系统不存在频偏，则峰值
Figure PCTCN2018101903-appb-000065
为：
Figure PCTCN2018101903-appb-000066
第二峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
Figure PCTCN2018101903-appb-000067
若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
Figure PCTCN2018101903-appb-000068
为：
Figure PCTCN2018101903-appb-000069
谷值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的谷值
Figure PCTCN2018101903-appb-000070
Figure PCTCN2018101903-appb-000071
其中，s preamble(k)为训练序列，w(m)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；k ▽为与谷值对应的时间下标。
其中，所述信噪比确定模块具体用于：利用所述峰值
Figure PCTCN2018101903-appb-000072
与所述谷值
Figure PCTCN2018101903-appb-000073
以及信噪比确定规则确定信噪比SNR；其中，所述信噪比确定规则为：
Figure PCTCN2018101903-appb-000074
其中，|·|表示绝对值运算。
本实施例还公开了一种信噪比确定设备，包括：存储器，用于存储计算机程序；处理器，用于执行计算机程序时实现上述信噪比确定方法的步骤。
本实施例还公开了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现上述信噪比确定方法的步骤。
其中，该存储介质可以包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
下面对本发明实施例提供的信道均衡装置进行介绍，下文描述的信道均衡装置与上文描述的信道均衡方法可以相互参照。
参见图10，本发明实施例提供的一种基于MMSE均衡器的信道均衡装置，包括：
第二获取模块210，用于获取上述信噪比确定装置得到的信噪比，以及频域信道冲激响应；
均衡器系数确定模块220，用于利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
尺度校正因子确定模块230，用于利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
信号均衡模块240，用于通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
其中，所述尺度校正因子确定模块具体用于利用尺度校正因子确定规则，以及信道频域响应的平均值
Figure PCTCN2018101903-appb-000075
信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；其中，所述尺度校正因子确定规则为：
Figure PCTCN2018101903-appb-000076
需要说明的是，本实施例中的尺度校正因子确定模块230可以理解为上述信道均衡方法中的尺度校正因子计算单元，实现尺度校正因子的确定；本实施例中的信号均衡模块240包括上述信道均衡方法中的MMSE均衡单元、和尺度校正单元，实现了信号星座图确定以及信号星座图的校正。
本实施例还公开了一种基于MMSE均衡器的信道均衡设备，包括：存储器，用于存储计算机程序；处理器，用于执行所述计算机程序时实现上述信道均衡方法的步骤。
本实施例还公开了一种计算机可读存储介质，所述计算机可读存储介质上存储有计算机程序，所述计算机程序被处理器执行时实现上述信道均衡方法的步骤。
其中，该存储介质可以包括：U盘、移动硬盘、只读存储器(Read-Only Memory，ROM)、随机存取存储器(Random Access Memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
本说明书中各个实施例采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似部分互相参见即可。
对所公开的实施例的上述说明，使本领域专业技术人员能够实现或使用本发明。对这些实施例的多种修改对本领域的专业技术人员来说将是显而易见的，本文中所定义的一般原理可以在不脱离本发明的精神或范围的情况下，在其它实施例中实现。因此，本发明将不会被限制于本文所示的这些实施例，而是要符合与本文所公开的原理和新颖特点相一致的最宽的范围。

Claims (10)

  1. 一种信息传输系统接收端的信噪比确定方法，所述信噪比确定方法基于采用重复训练序列结构实现时序同步的信息传输系统，其特征在于，所述信噪比确定方法包括：
    获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
    利用所述峰值与所述谷值确定信噪比。
  2. 根据权利要求1所述的信噪比确定方法，其特征在于，所述获取自相关函数的峰值和谷值包括：
    确定自相关函数R auto(k+N)；所述自相关函数
    Figure PCTCN2018101903-appb-100001
    其中，k表示与时间有关的下标，N为重复训练序列的长度，r(k+m)表示与k时刻延后m个采样周期的信号；m表示延迟的采样周期；(.) *表示共轭运算；
    根据所述自相关函数R auto(k+N)确定自相关函数的峰值
    Figure PCTCN2018101903-appb-100002
    若所述信息传输系统不存在频偏，则峰值
    Figure PCTCN2018101903-appb-100003
    为：
    Figure PCTCN2018101903-appb-100004
    若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
    Figure PCTCN2018101903-appb-100005
    为：
    Figure PCTCN2018101903-appb-100006
    根据所述自相关函数R auto(k+N)确定自相关函数的谷值
    Figure PCTCN2018101903-appb-100007
    Figure PCTCN2018101903-appb-100008
    其中，s preamble(k)为训练序列，w(k)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；
    Figure PCTCN2018101903-appb-100009
    为与谷值对应的时间下标。
  3. 根据权利要求2所述的信噪比确定方法，其特征在于，利用所述峰值与所述谷值确定信噪比，包括：
    利用所述峰值
    Figure PCTCN2018101903-appb-100010
    与所述谷值
    Figure PCTCN2018101903-appb-100011
    以及信噪比确定规则确定信噪比SNR；其中，所述信噪比确定规则为：
    Figure PCTCN2018101903-appb-100012
    其中，|·|表示绝对值运算。
  4. 一种基于MMSE均衡器的信道均衡方法，其特征在于，包括：
    获取如权利要求1至3中任意一项所述的信噪比确定方法得到的信噪比，以及频域信道冲激响应；
    利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
    利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
    通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
  5. 根据权利要求4所述的信道均衡方法，其特征在于，所述利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子，包括：
    利用尺度校正因子确定规则，以及信道频域响应的平均值
    Figure PCTCN2018101903-appb-100013
    信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；
    其中，所述尺度校正因子确定规则为：
    Figure PCTCN2018101903-appb-100014
  6. 一种信息传输系统接收端的信噪比确定装置，所述信噪比确定装置基于采用重复训练序列结构实现时序同步的信息传输系统，其特征在于，所述信噪比确定装置包括：
    第一获取模块，用于获取自相关函数的峰值和谷值；所述峰值代表信号平均功率与噪声平均功率之和；所述谷值代表噪声平均功率；
    信噪比确定模块，用于利用所述峰值与所述谷值确定信噪比。
  7. 根据权利要求6所述的信噪比确定装置，其特征在于，所述第一获取模块包括：
    自相关函数确定单元，用于确定自相关函数R auto(k+N)；所述自相关函数
    Figure PCTCN2018101903-appb-100015
    其中，k表示与时间有关的下标，N为重复训练序列的长度，r(k+m)为与k时刻延后m个采样周期的信号；m为延迟的采样周期；(.) *表示共轭运算；
    第一峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
    Figure PCTCN2018101903-appb-100016
    若所述信息传输系统不存在频偏，则峰值
    Figure PCTCN2018101903-appb-100017
    为：
    Figure PCTCN2018101903-appb-100018
    第二峰值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的峰值
    Figure PCTCN2018101903-appb-100019
    若所述信息传输系统存在频偏ε＝f offset/Δf，f offset表示载波偏移，Δf表示子载波频率间隔，则峰值
    Figure PCTCN2018101903-appb-100020
    为：
    Figure PCTCN2018101903-appb-100021
    谷值确定单元，用于根据所述自相关函数R auto(k+N)确定自相关函数的谷值
    Figure PCTCN2018101903-appb-100022
    Figure PCTCN2018101903-appb-100023
    其中，s preamble(k)为训练序列，w(m)为噪声，P signal为信号平均功率，P noise为噪声平均功率；k Δ为与峰值对应的时间下标；
    Figure PCTCN2018101903-appb-100024
    为与谷值对应的时间下标。
  8. 根据权利要求7所述的信噪比确定装置，其特征在于，所述信噪比确定模块具体用于：利用所述峰值
    Figure PCTCN2018101903-appb-100025
    与所述谷值
    Figure PCTCN2018101903-appb-100026
    以及信噪比确定规则确定信噪比SNR；其中，所述信噪比确定规则为：
    Figure PCTCN2018101903-appb-100027
    其中，|·|表示绝对值运算。
  9. 一种基于MMSE均衡器的信道均衡装置，其特征在于，包括：
    第二获取模块，用于获取如权利要求4至6中任意一项所述的信噪比确定装置得到的信噪比，以及频域信道冲激响应；
    均衡器系数确定模块，用于利用所述信噪比和所述频域信道冲激响应确定MMSE均衡器系数；
    尺度校正因子确定模块，用于利用信道频域响应的平均值、信号的平均功率、噪声的平均功率，确定尺度校正因子；
    信号均衡模块，用于通过所述MMSE均衡器系数和所述尺度校正因子对接收的频域信号进行均衡处理，得到尺寸校正后的频域信号。
  10. 根据权利要求9所述的信道均衡装置，其特征在于，所述尺度校正因子确定模块具体用于利用尺度校正因子确定规则，以及信道频域响应的平均值
    Figure PCTCN2018101903-appb-100028
    信号的平均功率P signal、噪声的平均功率P noise，确定尺度校正因子Θ；
    其中，所述尺度校正因子确定规则为：
    Figure PCTCN2018101903-appb-100029
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