Joint blind equalization method, device, electronic device, medium and program product

Abstract

The present invention discloses a joint blind equalization method, device, electronic device, medium and program product. By combining an improved MCMA algorithm based on simulated annealing and a DDLMS algorithm whose step size is adjusted by an inverse hyperbolic sine function, the problem that the existing blind equalization method is not effective in low signal-to-noise ratio environments is solved. Specifically, in the early stage of communication, the tap coefficients of the equalizer are adjusted using the improved MCMA algorithm to perform preliminary equalization processing to quickly achieve a stable equalization effect, and then switch to the DDLMS algorithm with a step size optimization mechanism, thereby further improving the steady-state error performance in subsequent stages. It can avoid the dependence of traditional adaptive equalization on training sequences, effectively reduce channel resource consumption, and improve the equalization effect in complex transmission environments through step size optimization, adapting to the equalization needs in low signal-to-noise ratio scenarios.

Claims

1. A joint blind equalization method, characterized in that: include: For a received signal obtained by a receiving end, adjusting tap coefficients of an equalizer using an improved modified normal mode blind equalization (MCMA) algorithm based on simulated annealing, so as to equalize the received signal according to the current tap coefficients of the equalizer to obtain a first target signal; Determining whether the first target signal achieves a preset equalization effect; When the first target signal reaches the preset equalization effect, adjusting the step size of the decision-directed least mean square (DDLMS) algorithm; adjusting the tap coefficients of the equalizer according to the step size of the DDLMS algorithm, so as to equalize the first target signal according to the current tap coefficients of the equalizer to obtain a second target signal; The probability formula for receiving a new solution in the MCMA algorithm improved based on simulated annealing is: , where P is the probability of accepting a new solution, is the cost function value of the MCMA algorithm at time t+1, is the cost function value of the MCMA algorithm at time t, is the temperature at time t, Negatively correlated with the number of iterations.

2. The joint blind equalization method according to claim 1, wherein: Determining whether the first target signal achieves a preset equalization effect includes: Calculating a first distance between the first target signal and the nearest symbol point in the constellation diagram; Determine whether the first distance is less than a preset distance, where the preset distance is the product of the distance between the two nearest symbol points in the constellation diagram and a preset parameter, where 0<the preset parameter<1; If the first distance is less than the preset distance, it is determined that the preset balancing effect is satisfied; otherwise, it is determined that the preset balancing effect is not satisfied.

3. The joint blind equalization method according to claim 2, wherein: Calculating a first distance from the first target signal to the nearest symbol point in the constellation diagram includes: Acquire signals output by the equalizer k times continuously, where the signals output k times continuously include the first target signal and a signal output by the equalizer k-1 times continuously before outputting the first target signal, where k is an integer greater than 1; Calculate the average distance between the signal outputted k times in succession and the nearest symbol point in the constellation diagram, and use the average distance as the first distance; Determining whether the first distance is less than a preset distance includes: Determining whether the average distance is less than the preset distance; If the average distance is less than the preset distance, it is determined that the preset balancing effect is satisfied; otherwise, it is determined that the preset balancing effect is not satisfied.

4. The joint blind equalization method according to claim 3, wherein: Calculate the average distance between the signal outputted for k consecutive times and the nearest symbol point in the constellation diagram, including: according to Calculate the average distance between the signal outputted for k consecutive times and the nearest symbol point in the constellation diagram; in, is the distance from the signal equalized by the MCMA algorithm improved by simulated annealing in the nth iteration to the nearest symbol point in the constellation diagram, is the average distance, and n is the total number of iterations.

5. The joint blind equalization method according to claim 3, wherein: Determining whether the average distance is less than the preset distance includes: according to Determining whether the average distance is less than the preset distance; in, is the average distance, represents a vector composed of the weight values ​​of each tap of the equalizer in the nth iteration, X(n) is the data vector input to the equalizer in the nth iteration, a(n) is the original signal sent by the transmitter, d is the distance between the two nearest symbol points in the constellation diagram, and g is the preset parameter.

6. The joint blind equalization method according to any one of claims 1 to 5, wherein: The tap coefficients of the equalizer are adjusted using the improved MCMA algorithm based on simulated annealing, including: use adjusting the tap coefficients of the equalizer; Wherein, W(n+1) represents the tap coefficient of the equalizer at the n+1th iteration, W(n) represents the tap coefficient of the equalizer at the nth iteration, is the step size of the MCMA algorithm improved based on simulated annealing, y(n) is the signal output by the equalizer in the nth iteration, represents the error between the modulus value of the signal output by the equalizer in the nth iteration and the constant modulus value when executing the MCMA algorithm improved by simulated annealing, x(n) is the received signal, It is represented by taking the complex conjugate of x(n), and the constant modulus is a constant calculated based on the original signal sent by the transmitting end.

7. The joint blind equalization method according to any one of claims 1 to 5, wherein: Adjusting the tap coefficients of the equalizer according to the step size of the DDLMS algorithm includes: use adjusting the tap coefficients of the equalizer; Wherein, W(n+1) represents the tap coefficient of the equalizer at the n+1th iteration, W(n) represents the tap coefficient of the equalizer at the nth iteration, is the step size of the DDLMS algorithm, y(n) is the signal output by the equalizer in the nth iteration, represents the error between the signal output by the equalizer in the nth iteration and the signal after the decision when executing the DDLMS algorithm, x(n) is the received signal, It is represented by taking the complex conjugate of x(n), and the signal after judgment is a signal obtained after the signal output by the equalizer in the nth iteration is judged by the judge.

8. A joint blind equalization device, characterized in that: include: a first equalizing unit, configured to adjust tap coefficients of an equalizer using a modified normal mode blind equalization (MCMA) algorithm improved based on simulated annealing for a received signal obtained by a receiving end, so as to equalize the received signal according to the current tap coefficients of the equalizer to obtain a first target signal; a judging unit, configured to judge whether the first target signal achieves a preset equalization effect; an adjusting unit, configured to adjust a step size of a decision-directed least mean square (DDLMS) algorithm when the first target signal achieves the preset equalization effect; a second equalizing unit, configured to adjust the tap coefficients of the equalizer according to a step size of the DDLMS algorithm, so as to equalize the first target signal according to the current tap coefficients of the equalizer to obtain a second target signal; The probability formula for receiving a new solution in the MCMA algorithm improved based on simulated annealing is: , where P is the probability of accepting a new solution, is the cost function value of the MCMA algorithm at time t+1, is the cost function value of the MCMA algorithm at time t, is the temperature at time t, Negatively correlated with the number of iterations.

9. A joint blind equalization electronic device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the joint blind equalization method according to any one of claims 1 to 7 when executing a computer program.

10. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the joint blind equalization method according to any one of claims 1 to 7 are implemented.

11. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the steps of the joint blind equalization method according to any one of claims 1 to 7 are implemented.

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