A low complexity apsk soft demapping method suitable for DVB-S2X system

Abstract

The application discloses a low-complexity APSK soft demapping method suitable for a DVB-S2X system, comprising the following steps: dividing a standard constellation diagram to obtain a judgment area of each constellation point; calculating a phase value of a receiving point, and determining a corresponding reference point according to the judgment area where the phase value is located for each ring in the standard constellation diagram to obtain a reference point set; subtracting the receiving point from each reference point in the reference point set, generating a new reference point set by comparing all the difference values; calculating the Euclidean distance between the receiving point and each new reference point based on the new reference point set; determining the minimum value of the Euclidean distance between the receiving point and each new reference point, and calculating a log-likelihood ratio according to the minimum value to realize soft demapping. The application has a very small bit error rate error, can effectively improve the efficiency of soft demapping when implemented in FPGA, is compatible with all modulation modes in the DVB-S2X standard, supports a higher data throughput and application flexibility.

Description

Technical Field

[0001] This invention belongs to the field of digital signal processing technology, specifically relating to a low-complexity APSK soft demapping method suitable for DVB-S2X systems. Background Technology

[0002] With the advent of the information age, the Digital Video Broadcasting-Satellite (DVB-S) standard has been around for over a decade. The DVB-S2X standard, released in 2014, significantly improves spectral efficiency through a combination of high-order APSK modulation and various code rates. In addition to the existing QPSK, 8PSK, 16APSK, and 32APSK modulation schemes in the DVB-S2 system, DVB-S2X adds 64APSK, 128APSK, and 256APSK modulation schemes, and also adds various constellation point mapping rules for same-order modulation to meet the needs of different environments. However, while high-order modulation schemes bring good spectral gain, they also greatly increase the complexity of the receiver; soft demapping is one important module in this regard.

[0003] Traditional soft demapping methods used in DVB-S2X systems mainly include the LOG-MAP algorithm, the MAX-LOG-MAP algorithm, and the Euclidean algorithm. However, these algorithms require frequent calculations of the Euclidean distance between the receiver point and the theoretical point within the entire standard constellation point set. If these algorithms are directly applied to the FPGA implementation of high-order APSK modulation, the complexity will increase dramatically with the modulation order. Therefore, a simpler soft demapping method is needed for FPGA implementation.

[0004] Q. Wang et al. proposed a simplified demapping method for uniform APSK, which utilizes phase information and some characteristics of uniform mapping to minimize the set of points for which Euclidean distance needs to be calculated, thereby reducing complexity. Existing technologies also include a lookup table-based demapping method applicable to non-uniform APSK mapping. This method stores constellation diagram information for different mapping schemes, similarly reducing the set of constellation points for which Euclidean distance needs to be calculated. However, this method only implements 8APSK and 32APSK schemes, which is relatively limited. Furthermore, an improved lookup table-based soft demapping method for FPGA-based DVB-S2X systems uses a partitioning approach, taking only two reference points from each ring for Euclidean distance calculation. It supports all DVB-S2X modes, significantly reducing the complexity of soft demapping. However, this method still requires multiple Euclidean distance calculations as the modulation order increases, resulting in high complexity in hardware implementation. Summary of the Invention

[0005] To address the aforementioned problems in the existing technology, this invention provides a low-complexity APSK soft demapping method suitable for DVB-S2X systems. The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a low-complexity APSK soft demapping method suitable for DVB-S2X systems, comprising: The standard constellation chart is divided into decision regions for each constellation point; Calculate the phase value of the receiving point, and for each ring in the standard constellation diagram, determine the corresponding reference point according to the decision region where the phase value is located, to obtain a set of reference points; The receiving point is subtracted from each of the minimum Euclidean distance reference points in the reference point set, and a new reference point set is generated by comparing all the obtained differences. Based on the new set of reference points, calculate the Euclidean distance between the receiving point and each new minimum Euclidean distance reference point; The minimum Euclidean distance between the receiving point and each new reference point is determined, and the log-likelihood ratio is calculated based on the minimum value to achieve soft demapping.

[0006] In one embodiment of the present invention, the step of calculating the phase value of the receiving point and determining the corresponding reference point for each ring in the standard constellation diagram based on the decision region where the phase value is located, to obtain a set of reference points, includes: According to the receiving point Calculate the tangent value from the real and imaginary parts. ;in, Represents the imaginary unit. , Representing the receiving points The real and imaginary parts; For each ring in the standard constellation diagram, determine the tangent value. The area where the judgment was made; tangent value The constellation points within the judgment area are designated as receiving points. The corresponding reference points form a set of reference points.

[0007] In one embodiment of the present invention, the reference point set includes a minimum Euclidean distance reference point set mapped to 0. and the set of minimum Euclidean distance reference points mapped to 1 ,in, This indicates the number of rings in the standard constellation diagram. Represents the imaginary unit. Indicates the first The minimum Euclidean distance reference point with a mapping of 0. , They represent The real and imaginary parts, Indicates the first The minimum Euclidean distance reference point mapped to 1, , They represent The real and imaginary parts.

[0008] In one embodiment of the present invention, the step of subtracting the receiving point from each reference point in the reference point set and generating a new reference point set by comparing all the obtained differences includes: The difference between the receiving point and each minimum Euclidean distance reference point mapped to 0 is obtained. ={ = }, ={ };in, , Representing the receiving points The real and imaginary parts, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the imaginary parts; The difference between the receiving point and each minimum Euclidean distance reference point mapped to 1 is obtained. ={ = }, ={ };in, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference from the imaginary part; Determine separately , , and minimum value , , and and minimum value , , and The corresponding minimum Euclidean distance reference points with a mapping of 0 and minimum Euclidean distance reference points with a mapping of 1, respectively; Minimum value , , and The minimum Euclidean distance reference points with mappings of 0 and 1 are respectively determined as four new minimum Euclidean distance reference points, generating a new set of reference points.

[0009] In one embodiment of the present invention, the four new minimum Euclidean distance reference points include: and ,in, This represents the set of reference points with the minimum Euclidean distance to the new mapping of 0. express The Middle k A new reference point with a minimum Euclidean distance of 0 is mapped to. , They represent The real and imaginary parts, This represents the set of reference points with the minimum Euclidean distance that are mapped to 1. express The Middle k A new reference point with a minimum Euclidean distance of 1 is mapped to. , They represent The real and imaginary parts.

[0010] In one embodiment of the present invention, the minimum value is... , , and After determining the minimum Euclidean distance reference points mapped to 0 and mapped to 1 as four new minimum Euclidean distance reference points and generating a new set of reference points, the process also includes: Acquire and save the receiving point and The set of absolute values ​​of the difference of real parts and the receiving point and The set of absolute values ​​of the difference of the imaginary parts ; Acquire and save the receiving point and The set of absolute values ​​of the difference of real parts and the receiving point and The set of absolute values ​​of the difference of the imaginary parts .

[0011] In one embodiment of the present invention, the step of calculating the Euclidean distance between the receiving point and each new reference point based on the new set of reference points includes: According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the imaginary parts is used to calculate the receiving point and... Euclidean distance between them: ; According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the real and real parts is used to calculate the receiving point and Euclidean distance between them: .

[0012] In one embodiment of the present invention, the step of determining the minimum Euclidean distance between the receiving point and each new reference point, and calculating the log-likelihood ratio based on the minimum value to achieve soft demapping includes: Determine the receiving point and Minimum Euclidean distance between and with Minimum Euclidean distance between ; Based on the minimum value of Euclidean distance Minimum distance from Euclidean distance Calculate the first k Log-likelihood ratio of bits: ; In the formula, This represents the variance of the complex Gaussian white noise in the channel.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention provides a low-complexity APSK soft demapping method suitable for DVB-S2X systems. Based on the idea of ​​partitioned lookup tables, this method performs a more simplified soft demapping of high-order APSK modulation signals. It not only has a very small bit error rate, but also effectively improves the efficiency of soft demapping in FPGA implementation, reduces DSP resources by 75%, and is compatible with all modulation methods in the DVB-S2X standard, supporting high data throughput and application flexibility.

[0014] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0015] Figure 1 This is a flowchart of a low-complexity APSK soft demapping method for DVB-S2X systems provided in this embodiment of the invention; Figure 2 This is another flowchart of the low-complexity APSK soft demapping method for DVB-S2X systems provided in this embodiment of the invention; Figure 3 This is a comparison chart of the BER of the soft demapping results of 64APSK modulation under 11-20dB Eb / No noise provided in the embodiments of the present invention; Figure 4 This is a comparison chart of the BER of the soft demapping results of 64APSK modulation under 15-23dB Eb / No noise provided in the embodiments of the present invention; Figure 5 This is a comparison chart of the BER of the soft demapping results of 64APSK modulation under 20-29dB Eb / No noise provided in the embodiments of the present invention. Detailed Implementation

[0016] The present invention will be further described in detail below with reference to specific embodiments, but the implementation of the present invention is not limited thereto.

[0017] Figure 1 This is a flowchart of a low-complexity APSK soft demapping method for DVB-S2X systems provided in this embodiment of the invention. Figure 1 As shown, this embodiment of the invention provides a low-complexity APSK soft demapping method suitable for DVB-S2X systems, including: S1. Divide the standard constellation diagram to obtain the decision region for each constellation point; S2. Calculate the phase value of the receiving point, and for each ring in the standard constellation diagram, determine the corresponding reference point according to the decision region where the phase value is located, and obtain the reference point set; S3. Subtract the receiving point from each reference point in the reference point set, and generate a new reference point set by comparing all the differences obtained. S4. Based on the new set of reference points, calculate the Euclidean distance between the receiving point and each new reference point; S5. Determine the minimum Euclidean distance between the receiving point and each new reference point, and calculate the log-likelihood ratio based on the minimum value to achieve soft demapping.

[0018] In one optional implementation, the modulation method used in this embodiment is: -APSK modulation, for both non-uniform and uniform modulation, taking the standard constellation diagram of this modulation method as an example, which includes x rings, the constellation points on each ring include constellation points mapped to 0 and constellation points mapped to 1. When dividing the standard constellation diagram, the median of the phase values ​​of two adjacent constellation points with the same mapping value on the ring is taken to divide the region between these two constellation points, forming the decision region of each constellation point on each ring.

[0019] It should be understood that different mapping methods and code rates in the DVB-S2X system correspond to different modcods. Therefore, by identifying the modcod, the reference points mapped to 0 or 1 on each ring corresponding to different modulation methods and different phases can be stored in the ROM.

[0020] Optionally, step S2, which involves calculating the phase value of the receiving point and determining the corresponding reference point for each ring in the standard constellation diagram based on the decision region where the phase value is located, to obtain the reference point set, includes: S201, According to the receiving point Calculate the tangent value from the real and imaginary parts. ;in, Represents the imaginary unit. , Representing the receiving points The real and imaginary parts; S202. For each ring in the standard constellation diagram, determine the tangent value. The area where the judgment was made; S203, The tangent value The constellation points within the judgment area are designated as receiving points. The corresponding reference points form a set of reference points.

[0021] It should be noted that, in FPGA implementation, the CORDIC IP core of Xinlix's FIFO call can be used to calculate the tangent value. .

[0022] In this embodiment, the reference point set includes the minimum Euclidean distance reference point set mapped to 0. and the set of minimum Euclidean distance reference points mapped to 1 ,in, This indicates the number of rings in a standard constellation chart. Represents the imaginary unit. Indicates the first The minimum Euclidean distance reference point with a mapping of 0. , They represent The real and imaginary parts, Indicates the first The minimum Euclidean distance reference point mapped to 1, , They represent The real and imaginary parts.

[0023] Step S3, which involves subtracting the receiving point from each minimum Euclidean distance reference point in the reference point set and generating a new reference point set by comparing all the obtained differences, includes: S301. Subtract the receiving point from each minimum Euclidean distance reference point mapped to 0, and obtain... ={ = }, ={ };in, , Representing the receiving points The real and imaginary parts, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the imaginary parts; S302. Subtract the receiving point from each minimum Euclidean distance reference point mapped to 1 to obtain... ={ = }, ={ };in, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference from the imaginary part; S303, determine respectively , , and minimum value , , and and minimum value , , and The corresponding minimum Euclidean distance reference points with a mapping of 0 and minimum Euclidean distance reference points with a mapping of 1, respectively; S304, Minimum value , , and The minimum Euclidean distance reference points with mappings of 0 and 1 are respectively identified as four new minimum Euclidean distance reference points, generating a new set of reference points.

[0024] Specifically, the four new minimum Euclidean distance reference points include: and ,in, This represents the set of reference points with the minimum Euclidean distance to the new mapping of 0. express The Middle k A new reference point with a minimum Euclidean distance of 0 is mapped to. , They represent The real and imaginary parts, This represents the set of reference points with the minimum Euclidean distance that are mapped to 1. express The Middle k A new reference point with a minimum Euclidean distance of 1 is mapped to. , They represent The real and imaginary parts.

[0025] Furthermore, the minimum value , , and After determining the minimum Euclidean distance reference points mapped to 0 and mapped to 1 as four new minimum Euclidean distance reference points and generating a new set of reference points, the process also includes: Get and save the receiving point and The set of absolute values ​​of the difference of real parts and receiving point and The set of absolute values ​​of the difference of the imaginary parts ; Get and save the receiving point and The set of absolute values ​​of the difference of real parts and receiving point and The set of absolute values ​​of the difference of the imaginary parts .

[0026] It should be noted that... , , and The stored data can be directly used for subsequent Euclidean distance calculations, thereby reducing redundant calculations.

[0027] Optionally, step S5, which involves calculating the Euclidean distance between the receiving point and each new reference point based on the new set of reference points, includes: According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the imaginary parts is used to calculate the receiving point and... Euclidean distance between them: ; According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the real parts is used to calculate the receiving point and Euclidean distance between them: .

[0028] Finally, the minimum Euclidean distance between the receiving point and each new reference point is determined, and the log-likelihood ratio is calculated based on this minimum value. The steps for implementing soft demapping include: Determine the receiving point and Minimum Euclidean distance between and with Minimum Euclidean distance between ; Based on the minimum value of Euclidean distance Minimum distance from Euclidean distance Calculate the first k Log-likelihood ratio of bits: ; In the formula, This represents the variance of the complex Gaussian white noise in the channel.

[0029] The following simulation experiment further illustrates the low-complexity APSK soft demapping method for DVB-S2X systems provided by this invention.

[0030] Simulation conditions: The software simulation experiments were conducted using MATLAB 2020b, taking higher-order APSK (64 APSK, 128 APSK, and 256 APSK) as examples. The channel used in the simulation was an additive white Gaussian noise channel. The hardware simulation experiments were conducted using Vivado 2018.2, with the VC709 FPGA chip selected.

[0031] Figure 3 This is a comparison chart of the BER (Bit Rate) of soft demapping results for 64APSK modulation under 11-20dB Eb / No noise, provided in an embodiment of the present invention. Figure 4 This is a comparison chart of the BER (Bit Rate) of soft demapping results for 64APSK modulation under 15-23dB Eb / No noise, provided in an embodiment of the present invention. Figure 5 This is a comparison chart of the BER (Bit Error Rate) of soft demapping results for 64APSK modulation under 20-29dB Eb / No noise, provided in an embodiment of the present invention. Specifically, as shown... Figure 3-5 As shown, higher-order 64APSK, 128APSK, and 256APSK modulation schemes are used, with the horizontal axis representing the signal-to-noise ratio (SNR) and the vertical axis representing the bit error rate (BER). It can be seen that the BER value of the signal obtained using the simplified APSK soft demapping method provided by this invention is very close to that of existing methods that directly calculate the Euclidean distance to the reference point, indicating that the performance loss of the algorithm is minimal after significant optimization in hardware implementation.

[0032] After synthesis and implementation in Vivado 2018.3, the resource usage of the low-complexity APSK soft demapping method for DVB-S2X systems provided by this invention, when compatible with all DVB-S2X modulation schemes, is shown in Table 1.

[0033] Table 1 Resource Usage Table

[0034] As can be seen from Table 1, the proportion of dedicated resources related to APSK soft demapping is relatively low, thus achieving the goal of reducing resource consumption.

[0035] As can be seen from the above embodiments, the beneficial effects of the present invention are as follows: This invention provides a low-complexity APSK soft demapping method suitable for DVB-S2X systems. Based on the idea of ​​partitioned lookup tables, this method performs a more simplified soft demapping of high-order APSK modulation signals. It not only has a very small bit error rate, but also effectively improves the efficiency of soft demapping in FPGA implementation, reduces DSP resources by 75%, and is compatible with all modulation methods in the DVB-S2X standard, supporting high data throughput and application flexibility.

[0036] In the description of this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0037] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A low-complexity APSK soft demapping method suitable for DVB-S2X systems, characterized in that, include: The standard constellation diagram is divided into regions to determine the decision area for each constellation point; Calculate the phase value of the receiving point, and for each ring in the standard constellation diagram, determine the corresponding reference point according to the decision region where the phase value is located, to obtain a set of reference points; The receiving point is subtracted from each of the minimum Euclidean distance reference points in the reference point set. By comparing all the obtained differences, a new reference point set is generated, including: The difference between the receiving point and each minimum Euclidean distance reference point mapped to 0 is obtained. ={ = }, ={ };in, , Representing the receiving points The real and imaginary parts, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 0 and The set of absolute values ​​of the difference of the imaginary parts; This indicates the number of rings in the standard constellation diagram. Represents the imaginary unit. Indicates the first The minimum Euclidean distance reference point with a mapping of 0. , They represent The real and imaginary parts, Indicates the first The minimum Euclidean distance reference point mapped to 1, , They represent The real and imaginary parts; The difference between the receiving point and each minimum Euclidean distance reference point mapped to 1 is obtained. ={ = }, ={ };in, express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference of the real parts. express and The absolute value of the difference Represents the minimum Euclidean distance reference point mapped to 1 and The set of absolute values ​​of the difference from the imaginary part; Determine separately , , and minimum value , , and and minimum value , , and The corresponding minimum Euclidean distance reference points with a mapping of 0 and minimum Euclidean distance reference points with a mapping of 1, respectively; Minimum value , , and The minimum Euclidean distance reference points with mappings of 0 and 1 are respectively determined as four new minimum Euclidean distance reference points, generating a new set of reference points; Based on the new set of reference points, calculate the Euclidean distance between the receiving point and each new minimum Euclidean distance reference point; The minimum Euclidean distance between the receiving point and each new reference point is determined, and the log-likelihood ratio is calculated based on the minimum value to achieve soft demapping.

2. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 1, characterized in that, The steps of calculating the phase value of the receiving point and determining the corresponding reference point for each ring in the standard constellation diagram based on the decision region where the phase value is located, to obtain the reference point set, include: According to the receiving point Calculate the tangent value from the real and imaginary parts. ;in, Represents the imaginary unit. , Representing the receiving points The real and imaginary parts; For each ring in the standard constellation diagram, determine the tangent value. The area where the judgment was made; tangent value The constellation points within the judgment area are designated as receiving points. The corresponding reference points form a set of reference points.

3. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 1, characterized in that, The set of reference points includes the set of reference points with the minimum Euclidean distance mapped to 0. and the set of minimum Euclidean distance reference points mapped to 1 ,in, This indicates the number of rings in the standard constellation diagram. Represents the imaginary unit. Indicates the first The minimum Euclidean distance reference point with a mapping of 0. , They represent The real and imaginary parts, Indicates the first The minimum Euclidean distance reference point mapped to 1, , They represent The real and imaginary parts.

4. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 3, characterized in that, The four new minimum Euclidean distance reference points include: and ,in, This represents the set of reference points with the minimum Euclidean distance to the new mapping of 0. express The Middle k A new reference point with a minimum Euclidean distance of 0 is mapped to. , They represent The real and imaginary parts, This represents the set of reference points with the minimum Euclidean distance that are mapped to 1. express The Middle k A new reference point with a minimum Euclidean distance of 1 is mapped to. , They represent The real and imaginary parts.

5. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 4, characterized in that, Minimum value , , and After determining the minimum Euclidean distance reference points mapped to 0 and mapped to 1 as four new minimum Euclidean distance reference points and generating a new set of reference points, the process also includes: Acquire and save the receiving point and The set of absolute values ​​of the difference of real parts and the receiving point and The set of absolute values ​​of the difference of the imaginary parts ; Acquire and save the receiving point and The set of absolute values ​​of the difference of real parts and the receiving point and The set of absolute values ​​of the difference of the imaginary parts .

6. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 5, characterized in that, Based on the new set of reference points, the steps of calculating the Euclidean distance between the receiving point and each of the new reference points include: According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the imaginary parts is used to calculate the receiving point and... Euclidean distance between them: ； According to the receiving point and The absolute value of the difference between the real parts and the receiving point and The absolute value of the difference between the real and real parts is used to calculate the receiving point and Euclidean distance between them: 。 7. The low-complexity APSK soft demapping method for DVB-S2X systems according to claim 6, characterized in that, The steps of determining the minimum Euclidean distance between the receiving point and each new reference point, and calculating the log-likelihood ratio based on the minimum value to achieve soft demapping include: Determine the receiving point and Minimum Euclidean distance between and with Minimum Euclidean distance between ; Based on the minimum value of Euclidean distance Minimum distance from Euclidean distance Calculate the first k The log-likelihood ratio of bits: ； In the formula, This represents the variance of the complex Gaussian white noise in the channel.

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