Signal demodulation method, device and electronic device thereof

Abstract

The embodiment of the present invention discloses a signal demodulation method, device and electronic device thereof, the method comprising: sampling the differential phase of a received signal according to an oversampling rate to obtain a phase differential signal; modulating the obtained differential phase signal according to a Gaussian filter function constructed based on a Laurent decomposition expression to obtain a differential phase signal including 2 N The invention comprises a method for demodulating a GFSK signal using a dataset of differential reference signals of various combinations, where N is the number of symbol bits for maximum likelihood evaluation; demodulating the first M symbols of the GFSK signal in the received signal based on the GFSK signal's preamble, where M is the number of preamble bits plus 1; and demodulating the remaining symbols of the GFSK signal using maximum likelihood evaluation based on the demodulated symbols of the GFSK signal and the dataset. This method utilizes a dataset constructed using a Laurent decomposition expression and maximum likelihood evaluation to achieve GFSK signal demodulation. This method has lower complexity, better frequency offset resistance, and can improve demodulation sensitivity, effectively reducing the pressure of frequency offset estimation and compensation.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of Bluetooth communications, and in particular to a signal demodulation method, device, and electronic equipment. Background Art

[0002] Bluetooth BR communications use Gaussian frequency shift keying (GFSK) baseband modulation. GFSK demodulation is a key technology in digital communication systems based on GFSK modulation. Its performance and structure determine the receiver's sensitivity and the complexity of its digital integrated circuit implementation. Furthermore, the maximum frequency deviation allowed during Bluetooth transmission can reach ±75 kHz, which requires a robust frequency offset estimation and compensation algorithm at the receiver end, as well as a demodulation algorithm with robust frequency offset.

[0003] Traditional differential demodulation methods offer relatively low complexity, but their reception performance is relatively poor. Common low-complexity demodulation methods include differential phase detection, feedback equalization, and matched filtering. While robust to frequency offset, these methods have limited demodulation thresholds. The Viterbi algorithm is the theoretically optimal receiver algorithm, but its computational complexity increases exponentially, hardware implementation is difficult, and its robustness to frequency offset is poor.

[0004] The embodiment of the present invention provides a non-correlated low-complexity demodulation algorithm based on Laurent decomposition, which has good frequency deviation robustness and a significantly improved demodulation threshold compared with differential phase detection, feedback equalization and matched filtering. Summary of the Invention

[0005] In order to solve the above technical problems, a technical solution adopted in an embodiment of the present invention is: to provide a signal demodulation method, which is applied to a received signal modulated as a GFSK signal, comprising: sampling the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal; modulating the received signal to obtain a phase differential signal including 2 according to a Gaussian filter function constructed based on the Laurent decomposition expression; N The invention relates to a method for demodulating a GFSK signal in a received signal using a data set of a differential reference signal of a combination of the two, wherein N is the number of symbol bits of the maximum likelihood evaluation; demodulating the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal, wherein M is the number of bits of the preamble plus 1; and demodulating the remaining symbols of the GFSK signal by maximum likelihood evaluation according to the demodulated symbols of the GFSK signal and the data set.

[0006] In some embodiments, the differential phase of the received signal is sampled at an oversampling rate to obtain a phase differential signal, including: performing phase extraction on the received signal to obtain a phase signal; performing a differential operation on the phase signal to obtain the differential phase; and sampling the differential phase at an oversampling rate to obtain the phase differential signal.

[0007] In some embodiments, demodulating the first M symbols of the GFSK signal in the received signal based on the preamble code of the GFSK signal includes: obtaining a first data subset from the data set based on the preamble code of the GFSK signal; and demodulating the first M symbols of the GFSK signal in the received signal through maximum likelihood evaluation based on the first data subset.

[0008] In some embodiments, demodulating the remaining symbols of the GFSK signal by maximum likelihood evaluation includes: feeding back the penultimate symbol and the penultimate symbol of the demodulated symbols, obtaining a second data subset from the data set; and demodulating the next symbol of the penultimate symbol by maximum likelihood evaluation based on the second data subset.

[0009] In some embodiments, the Gaussian filter function is the sum of the first term and the second term of the Laurent decomposition expression.

[0010] In some embodiments, the number of bits of the preamble is 4.

[0011] In some embodiments, the demodulation by maximum likelihood estimation includes: calculating a minimum square norm of the phase difference signal and the differential reference signal to obtain a symbol combination with a minimum Euclidean distance.

[0012] In order to solve the above technical problems, another technical solution adopted by the embodiment of the present invention is: to provide a signal demodulation device, which is applied to a received signal modulated into a GFSK signal, comprising: a sampling module, which is used to sample the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal; a modulation module, which modulates the 2 N A data set of differential reference signals of a combination, N being the number of symbol bits of maximum likelihood evaluation; a first demodulation module, configured to demodulate the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal, where M is the number of bits of the preamble plus 1; and a second demodulation module, configured to demodulate the remaining symbols of the GFSK signal by maximum likelihood evaluation based on the demodulated symbols of the GFSK signal and the data set.

[0013] To solve the above technical problems, another technical solution adopted in the embodiment of the present invention is: to provide an electronic device, comprising: at least one processor; at least one network interface, the network interface being communicatively connected to the corresponding processor; and a memory being communicatively connected to the at least one processor; wherein the network interface is used to establish a communication connection between the processor and other external devices; the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute a signal demodulation method as described above.

[0014] In order to solve the above technical problems, another technical solution adopted in the embodiment of the present invention is: providing a computer storage medium storing computer executable instructions, which are executed by one or more processors, so that the one or more processors can execute a signal demodulation method as described above.

[0015] The beneficial effects of the embodiments of the present invention are: different from the existing technology, the embodiments of the present invention are based on a data set constructed by the Laurent decomposition expression, and use maximum likelihood evaluation to realize the demodulation of the GFSK signal. This method has lower complexity and better anti-frequency deviation effect, and can improve the demodulation sensitivity and effectively reduce the pressure of frequency deviation estimation compensation. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 1 is a flow chart of a signal demodulation method provided by an embodiment of the present invention;

[0017] Figure 2 is a flowchart of step S100 of the signal demodulation method provided in an embodiment of the present invention;

[0018] Figure 3 is a flowchart of step S200 of the signal demodulation method provided in an embodiment of the present invention;

[0019] Figure 4 Flowchart of step S400 of the signal demodulation method provided by an embodiment of the present invention.

[0020] Figure 5 1 is a schematic structural diagram of a signal demodulation device provided by an embodiment of the present invention;

[0021] Figure 6 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0022] In order to facilitate the understanding of the present application, the present application is described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as being "fixed to" another element, it can be directly on the other element, or there can be one or more centered elements therebetween. When an element is described as being "connected to" another element, it can be directly connected to the other element, or there can be one or more centered elements therebetween. The terms "upper", "lower", "inner", "outer", "bottom" and the like used in this specification indicate an orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", "third" and the like are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0023] Unless otherwise defined, all technical and scientific terms used in this specification have the same meanings as those commonly understood by those skilled in the art to which this application belongs. The terms used in this specification and in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application. The term "and / or" as used in this specification includes any and all combinations of one or more of the relevant listed items.

[0024] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0025] Frequency shift keying (FSK) modulation is an early modulation method used in information transmission. The most common is a dual-frequency FSK system, which uses two frequencies to carry binary 1s and 0s. In binary FSK, the frequency of a carrier signal with a constant amplitude switches as the input bit stream changes (called high and low frequencies, representing binary 1s and 0s). GFSK, on ​​the other hand, is a continuous-phase FSK modulation technique that adds a pre-filtering Gaussian filter to the FSK signal to pre-process the baseband signal.

[0026] It should be noted that the embodiments of the present invention are applied to Basic Rate (BR) Bluetooth communications. Here, the frame structure of a BR Bluetooth signal is briefly described. The frame structure of a BR Bluetooth signal includes an access code, a header, and an information payload. The access code is used by the receiving device to identify the received packet. The access code is a 68- or 72-bit segment. A 68-bit access code includes the preamble and sync word, while a 72-bit access code includes the preamble, sync word, and trailer. The first bit of the preamble and sync word in a BR Bluetooth signal are closely related, with only two fixed combinations: 10101 and 01010. The trailer and the last bit of the sync word are also closely related, with only two fixed combinations: 01010 and 10101.

[0027] In some embodiments of the present invention, a non-correlated demodulation algorithm for GFSK signals is provided. The method uses the Laurent decomposition expression to construct a GFSK signal including 2 N The system uses a data set of differential reference signals to demodulate GFSK signals by calculating the least squares norm of the phase differential signal and the differential reference signal. This improves demodulation sensitivity and effectively reduces the pressure of frequency offset estimation and compensation.

[0028] In order to achieve the above technical effects, the technical method of the present invention is as follows, and its flow chart is as follows Figure 1 As shown:

[0029] Step S100: sampling the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal.

[0030] Step S200: According to the Gaussian filter function constructed based on the Laurent decomposition expression, the modulation is performed to obtain the 2 N The dataset of differential reference signals with different combinations.

[0031] Step S300: Demodulate the first M symbols of the GFSK signal in the received signal according to the preamble code of the GFSK signal.

[0032] Step S400: demodulating the remaining symbols of the GFSK signal by maximum likelihood estimation according to the demodulated symbols of the GFSK signal and the data set.

[0033] In some embodiments of the present application, step S100 specifically includes the following steps, and its flowchart is as follows: Figure 2 As shown:

[0034] Step S110: performing phase extraction on the received signal to obtain a phase signal.

[0035] In this embodiment, the received signal can be expressed as:

[0036]

[0037] in, represents the GFSK phase, and φ(n) represents the noise phase.

[0038] Perform phase extraction on the received signal to obtain the phase signal:

[0039]

[0040] Step S120: performing a differential operation on the phase signal to obtain a differential phase.

[0041] Perform differential operation on equation (2) to obtain the differential phase

[0042]

[0043] Step S130: sampling the differential phase according to the oversampling rate to obtain a phase differential signal.

[0044] The differential phase is oversampled according to the symbol rate to obtain a phase differential signal with higher resolution. The symbol rate refers to the speed at which data is transmitted. The number of symbols sent in one second is the symbol rate, which determines the signal frequency. According to the Nyquist sampling theorem, the sampling rate must be greater than or equal to twice the maximum frequency of the sampled signal. This means that a sampling rate equal to twice the maximum signal frequency satisfies this requirement; however, a sampling rate greater than twice the maximum frequency of the sampled signal is considered oversampling.

[0045] Because GFSK signals undergo downsampling and low-pass filtering at the receiver, the phase difference of the GFSK signal deviates significantly from the ideal Gaussian filter modulation signal, but instead resembles the signal constructed using the Laurent decomposition expression. Verification shows that the mean square error between the phase difference of the GFSK signal at the receiver and the modulated signal constructed using the Laurent decomposition expression is smaller than the mean square error between the phase difference of the GFSK signal and the Gaussian filter modulation signal.

[0046] Therefore, in this embodiment, the modulated signal constructed based on the Laurent decomposition expression is used as a data set to perform maximum likelihood evaluation on the phase difference signal.

[0047] The Laurent decomposition expression is known to be:

[0048]

[0049] It can be understood as the superposition of multiple pulse signals.

[0050] Taking into account algorithm complexity and demodulation performance, the embodiment of the present invention uses maximum likelihood estimation with a 5-bit symbol length, resulting in 32 symbol combinations. If higher demodulation performance is required, maximum likelihood estimation with a larger symbol length can be used, but this will undoubtedly increase algorithm complexity.

[0051] The 32 symbol combinations are modulated and sampled using a Gaussian filter function constructed using the Laurent decomposition expression, forming a data set of 32 differential reference signals θref. It should be noted that because the energy in the Laurent decomposition expression is concentrated in the first and second terms, in this embodiment, the Gaussian filter function is the sum of the first term c0 and the second term c1 of the expression.

[0052] In some embodiments of the present application, step S300 specifically includes the following steps, and its flowchart is as follows: Figure 3 As shown:

[0053] Step S310: Acquire a first data subset from a data set according to a preamble of a GFSK signal.

[0054] In the embodiment of the present application, the GFSK signal is a BR Bluetooth signal. In the above process, it is known that the first bit of the preamble and sync word of the BR Bluetooth signal has only two fixed combinations, namely {10101} and {01010}. Therefore, it is only necessary to search the data set for the differential reference signals corresponding to these two symbol combinations as the first data subset.

[0055] Step S320: Demodulate the first M symbols of the GFSK signal in the received signal by maximum likelihood estimation according to the first data subset.

[0056] Using the two differential reference signals in the first data subset as reference items, a maximum likelihood estimation is performed on the first five symbols of the GFSK signal. Specifically, by calculating the least squares norm of the phase difference signal and the two differential reference signals in the first data subset, the symbol combination corresponding to the differential reference signal is the first five symbols of the GFSK signal.

[0057] In some embodiments of the present application, step S400 specifically includes the following steps, and its flowchart is as follows: Figure 4 As shown:

[0058] Step S410: Feedback the penultimate symbol and the penultimate symbol in the demodulated symbols, and obtain a second data subset from the data set.

[0059] After demodulating the first five bits of the GFSK signal, the fourth and fifth bits are fed back to the data set, and differential reference signals corresponding to eight symbol combinations with the fourth and fifth bits of the GFSK signal as the first and second bits are obtained from the data set as the second data subset.

[0060] The embodiment of the present invention adopts maximum likelihood evaluation with a 5-bit symbol length, which can reduce the number of evaluations under the premise that the first two symbols are known. Without demodulating the 4th and 5th symbols in advance, when performing maximum likelihood evaluation on the differential phase signal, the reference items (i.e., differential reference signals) are as high as 32 items, i.e., the entire data set, which will undoubtedly increase the demodulation complexity exponentially. In addition, it is known that when modulating GFSK, because the length of the Gaussian filter is three symbols, the three symbols before and after are correlated. If maximum likelihood evaluation with a 3-bit symbol length is adopted, when the first two symbols are known, the differential phase signal has only two reference items when performing maximum likelihood evaluation. Although it has extremely low demodulation complexity, it is conceivable that its demodulation effect is poor.

[0061] Step S420: Demodulate the next symbol of the penultimate symbol through maximum likelihood estimation according to the second data subset.

[0062] Using the eight differential reference signals in the second data subset as reference items, a maximum likelihood estimation is performed on the sixth symbol of the GFSK signal. Specifically, by calculating the least squares norm of the phase difference signal and the eight differential reference signals in the first data subset, the sixth symbol of the GFSK signal can be demodulated based on the symbol combination corresponding to the differential reference signals.

[0063] The fifth and sixth symbols are then fed back into the data set. From this data set, differential reference signals corresponding to eight symbol combinations, each with the fifth and sixth symbols of the GFSK signal as the first and second symbols, are obtained and used as the second data subset. Using the eight differential reference signals in the second data subset as references, a maximum likelihood estimation is performed on the seventh symbol of the GFSK signal, allowing the seventh symbol of the GFSK signal to be demodulated. Subsequent symbols can be demodulated in this manner.

[0064] It should be noted that because the data frame of a BR Bluetooth signal includes a frame header containing information such as the data frame length, it is possible to predict when demodulation will be complete. Therefore, when a GFSK signal is demodulated to the second-to-last symbol, the second data subset only includes differential reference signals corresponding to four symbol combinations. When demodulating to the last symbol, the second data subset only includes differential reference signals corresponding to two symbol combinations.

[0065] Unlike existing technologies, this invention utilizes maximum likelihood estimation demodulation, which is significantly less complex than coherent likelihood demodulation methods such as Viterbi. Compared to commonly used non-coherent DFE algorithms, it improves demodulation sensitivity by 1dB and offers improved frequency offset immunity. At ±30kHz frequency offset, the sensitivity performance drops by only 0.2dB, effectively reducing the burden on frequency offset estimation and compensation.

[0066] In some other embodiments of the present application, a signal demodulation device based on the above signal demodulation method is provided. The structural diagram of the device is shown in FIG. Figure 5 As shown, it specifically includes: a sampling module 100, a modulation module 200, a first demodulation module 300 and a second demodulation module 400.

[0067] The sampling module 100 is used to sample the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal.

[0068] The modulation module 200 modulates a data set including 2N combinations of differential reference signals according to a Gaussian filter function constructed based on the Laurent decomposition expression, where N is the number of symbol bits of the maximum likelihood evaluation.

[0069] The first demodulation module 300 is configured to demodulate the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal, where M is the number of bits of the preamble plus 1.

[0070] The second demodulation module 400 is configured to demodulate the remaining symbols of the GFSK signal by maximum likelihood estimation according to the demodulated symbols of the GFSK signal and the data set.

[0071] Different from the existing technology, the implementation method of the present invention uses a data set constructed based on the Laurent decomposition expression to realize the demodulation of the GFSK signal using maximum likelihood evaluation. This method has lower complexity and better anti-frequency deviation effect, and can improve the demodulation sensitivity and effectively reduce the pressure of frequency deviation estimation compensation.

[0072] Figure 6 FIG. 1 is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. Figure 6 As shown, the electronic device 500 includes:

[0073] One or more processors 501, network interface 502, and memory 503, Figure 6 In the figure, a processor 501, a network interface 502 and a memory 503 are taken as an example.

[0074] The network interface 502 is in communication with the corresponding processor 501, and the processor 501 and the memory 503 can be connected via a bus or other means. Figure 6 The bus connection is taken as an example.

[0075] The network interface 502 is used to establish a communication connection between the processor 501 and other external devices, and includes the following types of interfaces: RJ-45 interface, SC fiber optic interface, AUI interface, FDDI interface, and Console interface.

[0076] Memory 503, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer executable programs, and modules. Processor 501 executes the non-volatile software programs, instructions, and units stored in memory 503 to perform various functional applications and data processing of the electronic device, thereby implementing the signal demodulation method of the above-described method embodiment.

[0077] The memory 503 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 503 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 503 may optionally include a memory remotely located relative to the processor 501, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0078] The one or more units are stored in the memory 503, and when executed by one or more processors 501, perform the signal demodulation method in any of the above method embodiments, for example, perform the signal demodulation method described above. Figure 1 Steps S100 to S400 of the method or implementation Figure 5 The functions of each module in the device shown.

[0079] The electronic device can execute the signal demodulation method provided by the embodiment of the present invention, and has the corresponding program module and beneficial effects of the execution method. For technical details not fully described in the electronic device embodiment, please refer to the signal demodulation method provided by the embodiment of the present invention.

[0080] Embodiments of the present invention also provide a non-volatile computer-readable storage medium. This non-volatile computer-readable storage medium may be included in the device described in the above embodiments, or may exist independently and not incorporated into the device. This non-volatile computer-readable storage medium carries one or more programs. When these one or more programs are executed, they implement the signal demodulation method of the embodiments of the present disclosure.

[0081] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Based on the idea of ​​the present application, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations in different aspects of the present application as above, which are not provided in detail for the sake of simplicity. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A signal demodulation method, applied to a received signal modulated as a GFSK signal, characterized in that: include: Sampling the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal; According to the Gaussian filter function constructed based on the Laurent decomposition expression, the modulation acquisition includes 2 N The dataset of differential reference signals of various combinations, N is the number of symbol bits for maximum likelihood evaluation; Demodulate the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal, where M is the number of bits of the preamble plus 1; Remaining symbols of the GFSK signal are demodulated by maximum likelihood estimation based on the demodulated symbols of the GFSK signal and the data set.

2. The method according to claim 1, characterized in that The step of sampling the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal includes: Performing phase extraction on the received signal to obtain a phase signal; performing a differential operation on the phase signal to obtain the differential phase; The differential phase is sampled according to an oversampling rate to obtain the phase differential signal.

3. The method according to claim 1, characterized in that The demodulating the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal includes: Acquire a first data subset from the data set according to a preamble of the GFSK signal; According to the first data subset, first M symbols of the GFSK signal in the received signal are demodulated by maximum likelihood estimation.

4. The method according to claim 1, wherein Demodulating the remaining symbols of the GFSK signal by maximum likelihood estimation includes: Feedback the penultimate symbol and the penultimate symbol of the demodulated symbols, and obtain a second data subset from the data set; According to the second data subset, a symbol next to the penultimate symbol is demodulated by maximum likelihood estimation.

5. The method according to claim 1, characterized in that The Gaussian filter function is the sum of the first term and the second term of the Laurent decomposition expression.

6. The method according to claim 1, characterized in that The number of bits of the leading code is 4.

7. The method according to any one of claims 1 to 6, characterized in that The demodulation by maximum likelihood estimation includes: The minimum square norm of the phase difference signal and the differential reference signal is calculated to obtain a symbol combination with the minimum Euclidean distance.

8. A signal demodulation device, applied to a received signal modulated into a GFSK signal, characterized in that: include: The sampling module is used to sample the differential phase of the received signal according to the oversampling rate to obtain a phase differential signal; The modulation module is based on the Gaussian filter function constructed based on the Laurent decomposition expression. The modulation includes 2 N The dataset of differential reference signals of various combinations, N is the number of symbol bits for maximum likelihood evaluation; A first demodulation module, configured to demodulate the first M symbols of the GFSK signal in the received signal according to the preamble of the GFSK signal, where M is the number of bits of the preamble plus 1; The second demodulation module is configured to demodulate the remaining symbols of the GFSK signal by maximum likelihood estimation according to the demodulated symbols of the GFSK signal and the data set.

9. An electronic device, characterized in that: include: at least one processor; at least one network interface, the network interface being communicatively connected to a corresponding processor; as well as, a memory communicatively connected to the at least one processor; wherein, The network interface is used to establish a communication connection between the processor and other external devices; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the signal demodulation method according to any one of claims 1 to 8.

10. A non-volatile computer storage medium, characterized in that The computer storage medium stores computer-executable instructions, which are executed by one or more processors, enabling the one or more processors to execute a signal demodulation method according to any one of claims 1 to 8.

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