MAPSK blind equalization method and system suitable for low signal-to-noise ratio complex channel environment

Abstract

The invention discloses an MAPSK blind equalization method and system suitable for a low signal-to-noise ratio complex channel environment. The system comprises a transverse filter, an error calculator and a weight vector updater, wherein the transverse filter is used for receiving an MAPSK signal sequence subjected to symbol synchronization processing and is provided with a plurality of taps, the error calculator is used for calculating the amplitude and / or phase error of a signal according to the output of the transverse filter, and the weight vector updater is used for updating the weights of the taps of the transverse filter according to the calculated error. According to the blind equalization method provided by the invention, rapid convergence can be realized in a low signal-to-noise ratio and complex channel environment, and the communication quality and reliability of satellite communication can be remarkably improved.

Description

Technical Field

[0001] The present invention relates to the field of satellite communication, and particularly to satellite communication technology applying the MAPSK modulation system. Background Art

[0002] In an actual communication system, a signal is affected by various factors during transmission, such as atmospheric interference, rain fade, multipath effect, etc. These factors will cause inter-symbol interference (ISI), thus resulting in signal distortion. In order to eliminate the ISI caused by channel distortion or multipath effect, equalization technology is widely applied in communication systems. Blind equalization is a special equalization technology, which can achieve channel equalization without a training sequence, thus effectively reducing the bit error rate and improving the communication quality.

[0003] However, most of the existing blind equalization algorithms are optimized for the MQAM modulation system, and relatively few studies are conducted on the MAPSK (M-ary Amplitude Phase Shift Keying) modulation system. Among the existing blind equalization algorithms, the amplitude-based RDE (Radius Directed Equalization) blind equalization algorithm is considered to be the most suitable algorithm for the MAPSK modulation system, but it has significant problems in practical applications. For example, there will be a plateau during the convergence process, that is, the convergence speed suddenly decreases, resulting in a slow change in the residual ISI. This phenomenon is particularly serious in a low signal-to-noise ratio (SNR) environment, greatly limiting the application of the MAPSK modulation system in scenarios such as satellite communication with low SNR, complex channel environment, and high computational speed requirements. Therefore, developing an efficient blind equalization method that can converge quickly under low SNR conditions and adapt to complex channel environments is of great significance for improving the communication quality and reliability of satellite communication. Summary of the Invention

[0004] Aiming at the defects of the existing technology, the purpose of the present invention is to propose an efficient blind equalization method that can converge quickly under low SNR conditions and adapt to complex channel environments, especially satellite communication, which can significantly improve the communication quality and reliability of satellite communication.

[0005] The technical solution of the present invention is as follows:

[0006] A MAPSK blind equalization system applicable to a complex channel environment with low signal-to-noise ratio, comprising: a filter for receiving the MAPSK signal sequence after symbol synchronization processing, a weight vector updater for receiving the output of the filter and feeding it back to the input of the filter, and an error calculator for receiving the output of the filter and feeding it back to the input of the weight vector updater; wherein, the filter is a transversal filter with multiple taps; the error calculator calculates the amplitude and / or phase error of the signal according to the output of the filter, and the weight vector updater updates the weights of the taps of the transversal filter according to the error for the next filtering operation.

[0007] According to some preferred embodiments of the present invention, the MAPSK blind equalization system further includes a register connected to the filter for receiving the sampled data of the MAPSK signal sequence after the symbol synchronization processing.

[0008] The present invention further provides a MAPSK blind equalization method applying the above blind equalization system, comprising:

[0009] S1 Perform down-conversion processing on the MAPSK satellite signal received by the antenna to convert it into a baseband signal;

[0010] S2 Synchronize the symbols of the baseband signal to obtain a synchronized signal x(t);

[0011] S3 Initialize the weight vector W(n) of the taps of the filter to obtain a filter with initialized weight vector; filter the synchronized signal x(t) by the filter with initialized weight vector to obtain a filtered signal y(t);

[0012] S4 Calculate the error e(t) between the filtered signal y(t) and the desired signal through the following error function:

[0013]

[0014] wherein, R 2 is the statistical modulus value of the synchronized signal, as follows:

[0015] where E represents expectation, || represents modulus value,

[0016] λ is a set signal threshold;

[0017] S5 Update the weight vector W(n) of the taps of the filter through the following weight vector update model until the signal converges to a steady state:

[0018] w i (n + 1) = w i (n) + μe(t)x *(t)i = 1, 2, ..., N(2),

[0019] where, w i (n + 1) represents the weight value of the i-th tap of the filter at the (n + 1)-th moment, w i (n) represents the weight value of the i-th tap of the filter at the current moment, i.e., the n-th moment, μ represents the step-size iteration factor, e(t) represents the error function, x * (t) represents the conjugate of the synchronization signal x(t), and N represents the number of filter taps.

[0020] According to some preferred embodiments of the present invention, the initialization method is: setting the initial value of the weight of the tap located in the middle of the filter to 1, and the other positions to 0.

[0021] According to some preferred embodiments of the present invention, the obtaining of the filtered signal y(t) further includes: setting a register connected to the filter and receiving N consecutive sampling data of the synchronization signal x(t), performing a correlation operation on the filter with the initialized weight vector and the corresponding sampling data in the register to obtain the filtered signal y(t), where N is equal to the number of taps of the filter.

[0022] According to some preferred embodiments of the present invention, λ is set to the mean value of the amplitudes of the circumferences with the largest signal point distribution radius, i.e., the outer ring, and the circumference with the second largest signal point distribution radius, i.e., the sub-outer ring, in the MAPSK constellation diagram.

[0023] The beneficial effects of the present invention include:

[0024] The blind equalization method of the present invention only needs to utilize the error calculated by the outer ring, and can still converge quickly under low signal-to-noise ratio conditions, and is particularly suitable for satellite communication.

[0025] The present invention significantly improves the convergence speed and stability of MAPSK signals in a low signal-to-noise ratio environment through a specific error function model and filter coefficient update strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram of the blind equalization structure used in the present invention;

[0027] Figure 2 It is the received signal constellation diagram after down-conversion and timing synchronization obtained in Embodiment 1;

[0028] Figure 3 It is the residual ISI curve diagram of the method of the present invention and the RDE algorithm under the same multipath conditions in Embodiment 1;

[0029] Figure 4It is a graph showing the MSE convergence of the method of the present invention and the RDE algorithm under the same multipath conditions in Embodiment 1. Detailed implementation manners

[0030] The present invention will be described in detail below with reference to embodiments and the accompanying drawings. However, it should be understood that the embodiments and the drawings are only used for exemplary description of the present invention and do not constitute any limitation to the protection scope of the present invention. All reasonable transformations and combinations within the scope of the inventive concept of the present invention fall within the protection scope of the present invention.

[0031] Refer to the attached Figure 1 For the MAPSK blind equalization method applicable to a complex channel environment with low signal-to-noise ratio of the present invention, the blind equalization structure used includes: a filter for receiving the signal sequence after symbol synchronization processing, a weight vector updater for receiving the output of the filter and feeding it back to the input of the filter, and an error calculator for receiving the output of the filter and feeding it back to the input of the weight vector updater.

[0032] Among them, the filter is a transversal filter with multiple taps, and the tap weights of the transversal filter are updated by the weight vector updater.

[0033] According to the above blind equalization structure, the present invention can use the output y(t) of the filter as the input of the error calculator to calculate the amplitude and phase error e(t), and use e(t) as the input of the weight vector updater to update the filter weight vector. The updated weight vector W(n) is then fed back to the filter for the next moment's filtering operation.

[0034] According to some preferred embodiments of the present invention, the blind equalization structure further includes a register connected to the filter for receiving N sampled data of the signal sequence after symbol synchronization processing.

[0035] Under the above preferred blind equalization structure, the blind equalization method of the present invention includes:

[0036] S1 Perform down-conversion processing on the MAPSK satellite signal received by the antenna to convert it into a baseband signal.

[0037] S2 Perform symbol synchronization on the baseband signal to obtain a synchronized signal x(t).

[0038] S3 Initialize the weight vector W(n) of the filter taps to obtain a filter with initialized weight vectors, and perform a correlation operation on the filter with initialized weight vectors and the corresponding sampled data in the register to obtain a filtered signal y(t).

[0039] In some specific embodiments, the initialization method is: set the initial value of the weight of the tap in the middle position of the filter to 1, and the other positions to 0.

[0040] For example, in a specific embodiment, if the number of taps N of the filter is 7, the initial weight vector W(n) = [0, 0, 1, 0, 0] T .

[0041] In some specific embodiments, the correlation operation is as follows: multiply each filter tap by the sampling data at the corresponding position stored in the register, and then sum all the multiplication results to obtain the filtered signal.

[0042] S4 calculates the error e(t) between the filtered signal y(t) and the desired signal through the following error function:

[0043]

[0044] where R 2 is the statistical modulus value of the signal, as follows:

[0045] where E represents expectation, || represents modulus value,

[0046] λ is the set signal threshold.

[0047] In some specific embodiments, the signal threshold can be set to the mean value of the amplitudes of the circumference with the largest signal point distribution radius (i.e., the outer ring) and the circumference with the second largest signal point distribution radius (i.e., the sub-outer ring) in the MAPSK constellation diagram.

[0048] S5 updates the weight vector W(n) of the filter tap through the following weight vector update model until the signal reaches steady-state convergence:

[0049] w i (n + 1) = w i (n) + μe(t)x * (t) i = 1, 2,..., N(2),

[0050] where w i (n + 1) represents the weight value of the i-th tap of the filter at the (n + 1)-th moment, w i (n) represents the weight value of the i-th tap of the filter at the current moment, i.e., the n-th moment, μ represents the step size iteration factor, e(t) represents the error function, x * (t) represents the conjugate of the synchronization signal x(t), and N represents the number of filter taps.

[0051] Embodiment 1

[0052] Blind equalization simulation of MAPSK signals in satellite communication is carried out by the blind equalization method of the present invention and the traditional amplitude-based RDE (Radius Directed Equalization) blind equalization algorithm.

[0053] The simulated satellite signal-to-noise ratio used is 20 dB, and the channel parameters are [0.7632, -0.2567,

[0054] -0.1343, 0.0592, 0.0267, 0.0098]. The signal modulation system is 64APSK, the constellation point configuration is 8 + 16 + 20 + 20, the number of filter taps is 15, and the register can store 15 consecutive sampling data of the signal.

[0055] Among them, the error function adopted by the RDE algorithm is as follows:

[0056] e RDE (t) = y(t)(R k 2 -|y(t)| 2 )|y(t)| ∈ λ k

[0057] is the statistical modulus value of different ring regions, λ k is the set signal range, k represents the serial number of the ring region. In this embodiment, 64APSK has 4 rings, so k = 1, 2, 3, 4.

[0058] After calculation, in this embodiment, R k ∈ {1, 0.6923, 0.4231, 0.1923}.

[0059] At the same time, record the residual ISI and MSE of the two algorithms according to the following calculation formula:

[0060]

[0061] The constellation diagram of the synchronization signal x(t) obtained by the blind equalization method of the present invention is as shown in the appendix Figure 2 It can be seen that the received signal constellation points are mixed together and no effective decision can be made.

[0062] The residual ISI curve diagram of the blind equalization method of the present invention and the RDE algorithm is as shown in the appendix Figure 3 It can be seen that the residual ISI of the blind equalization algorithm of the present invention (the OCMA curve shown in the figure) reaches stability at the 6×10 4 th iteration, while the residual ISI of the traditional RDE algorithm (the RDE curve shown in the figure) reaches stability at the 1.4×10 5 th iteration. This shows that the blind equalization algorithm of the present invention has a faster convergence speed than the traditional RDE algorithm.

[0063] The MSE convergence curve diagram is as shown in the appendix Figure 4As shown, although the MSE of the blind equalization algorithm of the present invention is larger than that of the traditional RDE algorithm in the initial stage, the MSE rapidly decreases to be less than that of the traditional RDE algorithm after the equalization converges. This shows that the blind equalization algorithm of the present invention has a smaller MSE than the traditional RDE algorithm, and the equalization output will be closer to the ideal constellation diagram.

[0064] The above embodiments are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the idea of the present invention belong to the protection scope of the present invention. It should be pointed out that for those of ordinary skill in the art, improvements and refinements made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. MAPSK blind equalization system suitable for low signal-to-noise ratio complex channel environment, characterized by: It includes: A filter for receiving a MAPSK signal sequence after symbol synchronization processing, a weight vector updater for receiving the output of the filter and feeding it back to the weight vector updater for the filter, and an error calculator for receiving the output of the filter and feeding it back to the weight vector updater; wherein the filter is a transversal filter with multiple taps; the error calculator calculates the amplitude and / or phase error of the signal based on the output of the filter, and the weight vector updater updates the weights of the taps of the transversal filter based on the error for filtering operation at the next moment.

2. The MAPSK blind equalization system according to claim 1, characterized in that: It also includes a register connected to the filter and receiving the sampling data of the MAPSK signal sequence after the symbol synchronization processing.

3. The MAPSK blind equalization method using the blind equalization system according to claim 1 or 2, characterized in that: It includes: S1 performs down-conversion processing on the MAPSK satellite signal received by the antenna and converts it into a baseband signal; S2 performs symbol synchronization on the baseband signal to obtain a synchronization signal x(t); S3 initializes the weight vector W(n) of the taps of the filter to obtain a filter initialized with the weight vector; The synchronization signal x(t) is filtered by the filter initialized by the weight vector to obtain a filtered signal y(t); S4 calculates the error e(t) between the filtered signal y(t) and the expected signal through the following error function: Among them, R 2 The statistical modulus value of the synchronization signal is as follows: Where E represents the expectation, || represents the modulus value, λ is the set signal threshold; S5 updates the weight vector W(n) of the filter taps through the following weight vector update model until the signal converges to a steady state: w i (n+1)=w i (n)+μe(t)x * (t)i=1,2,...,N(2) Among them, w i (n+1) represents the weight of the ith tap of the filter at time n+1, w i (n) represents the weight of the ith tap of the filter at the current moment, i.e., at moment n, μ represents the step size iteration factor, e(t) represents the error function, and x * (t) represents the conjugate of the synchronization signal x(t), and N represents the number of filter taps.

4. The MAPSK blind equalization method according to claim 3, characterized in that: The initialization method is: setting the initial value of the weight of the tap located in the middle position of the filter to 1, and setting the initial value of the weight of the tap at other positions to 0.

5. The MAPSK blind equalization method according to claim 3, characterized in that: The acquisition of the filtered signal y(t) also includes: setting a register connected to the filter to receive N consecutive sampling data of the synchronization signal x(t), performing correlation operations on the filter initialized with the weight vector and the corresponding sampling data in the register to obtain the filtered signal y(t), wherein N is equal to the number of taps of the filter.

6. The MAPSK blind equalization method according to claim 3, characterized in that: The λ is set to be the average of the amplitudes of the circle with the largest signal point distribution radius, i.e., the outer ring, and the circle with the second largest signal point distribution radius, i.e., the sub-outer ring, in the MAPSK signal constellation diagram.

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