Frequency-based signal modulation method, device, terminal equipment and storage medium

Abstract

The present invention provides a frequency-based signal modulation method, device, terminal equipment and storage medium, the method comprising: performing phase encoding on data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal; generating an adaptive frequency slope according to channel conditions detected in real time, applying the adaptive frequency slope to the initial linear frequency modulation signal, and obtaining a linear frequency modulation signal for transmission; controlling the receiving end to restore the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise. The present invention can improve the anti-interference capability and spectrum efficiency of Chirp spread spectrum modulation in a multipath environment.

Description

Technical Field

[0001] The present invention relates to the technical field of spread spectrum modulation, and in particular to a frequency-based signal modulation method, device, terminal equipment and storage medium. Background Art

[0002] Spread Spectrum Modulation (SSM) is a communication technology that improves the signal's anti-interference ability and coverage by introducing additional bandwidth into the transmission signal. The basic idea of ​​spread spectrum modulation is to expand the bandwidth of the transmission signal to a much larger bandwidth than the original information signal, so that the original signal can be restored by demodulation at the receiving end. Under the same transmission power, the energy of the spread spectrum signal is dispersed over a wider frequency band, and its coverage is usually wider than that of a narrowband signal, so the signal fading at the receiving end can be reduced. In addition, the spread spectrum signal is distributed over a wider frequency spectrum, making it difficult to be intercepted and interfered with, and it also has high concealment and security.

[0003] The frequency slope of the traditional Chirp signal is fixed. When the signal reaches the receiving end through different paths in a multipath propagation environment, if it encounters severe multipath effects, the signal with a fixed frequency slope is difficult to effectively resist such interference, thus affecting the communication quality. In addition, traditional spread spectrum modulation usually uses linear frequency changes to represent data. Although its symbol bandwidth is wide, the amount of information carried by each symbol is actually limited. Under the same bandwidth, the frequency utilization rate of spread spectrum modulation is lower than the transmission efficiency of other modulation technologies. Traditional spread spectrum modulation (including Chirp modulation) has obvious limitations in multipath environments and spectrum efficiency. Summary of the invention

[0004] The present invention aims to provide a frequency-based signal modulation method, device, terminal equipment and storage medium to solve the above technical problems and improve the anti-interference ability and spectrum efficiency of Chirp spread spectrum modulation in a multipath environment.

[0005] In order to solve the above technical problems, the present invention provides a frequency-based signal modulation method, comprising:

[0006] Phase encoding the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal;

[0007] generating an adaptive frequency slope according to a channel condition detected in real time, and applying the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission;

[0008] The receiving end is controlled to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

[0009] In the above scheme, the data bits to be transmitted are phase-encoded based on a preset phase encoding function. Nonlinear phase coding can increase the time-frequency localization characteristics of the signal, making the signal less susceptible to delay spread and frequency selective fading in a multipath environment. Through phase coding, more information can be embedded in each modulation symbol, thereby increasing the information density of the symbol. In a multipath propagation environment, time delays and frequency offsets may occur when the signal reaches the receiving end through different paths. Through the adaptive frequency slope, the frequency change of the signal can be dynamically adjusted to reduce the impact of the multipath effect. The adaptive frequency slope enables the receiving end to better track the frequency change of the signal, thereby improving the coherence and demodulation performance of the signal. The receiving end demodulates the signal through the maximum likelihood algorithm, which can effectively reduce the impact of Gaussian noise on signal demodulation and improve the detection performance and bit error rate performance of the signal.

[0010] In one implementation, performing phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal specifically includes:

[0011] Obtain the number of data bits transmitted in a single symbol period, and construct a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values;

[0012] Acquire data bits to be transmitted, and perform phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is:

[0013] φ(t)=α0+α1t+α2t 2 ;

[0014] Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients;

[0015] A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is:

[0016] s(t)=Acos(2πf0t+φ(t));

[0017] Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

[0018] In the above scheme, by obtaining the number of data bits in a single symbol period, and based on the binary value permutations and combinations of these data bits, a mapping relationship between data bits and phase coefficients is constructed. Each binary value permutation and combination corresponds to a set of phase coefficient values. This mapping relationship allows the data bits to be directly represented by the change of the phase coefficient, thereby realizing the phase encoding of the data. The quadratic polynomial function introduces nonlinear phase changes, which can increase the complexity of the signal compared to the traditional linear phase change, thereby improving the ability to resist multipath interference. A binary value permutation and combination is randomly selected in the mapping relationship as the phase encoding result. This method increases the randomness of the signal, thereby further improving the signal's anti-interference ability.

[0019] In one implementation, generating an adaptive frequency slope according to the channel condition detected in real time, applying the adaptive frequency slope to the initial linear frequency modulation signal, and obtaining the linear frequency modulation signal for transmission specifically includes:

[0020] Detect the signal-to-noise ratio condition of the real-time detection channel, and calculate the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is:

[0021]

[0022] Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; k max is the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed;

[0023] The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is:

[0024] f(t)=f0+k(t)×t;

[0025] Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time;

[0026] The instantaneous frequency is applied to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission; wherein the linear frequency modulation signal is expressed as:

[0027]

[0028] Where A is the signal amplitude; φ(t) is a quadratic polynomial function.

[0029] In the above scheme, the channel conditions are detected in real time and the frequency slope is adjusted, so that the system can flexibly respond to different channel environments and improve transmission quality and reliability. Through adaptive frequency slope, the signal can better adapt to changes in channel conditions and reduce the impact of multipath effects. The dynamic adjustment of the frequency slope makes the signal bandwidth utilization higher, thereby improving spectrum efficiency.

[0030] In one implementation, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, specifically including:

[0031] Obtain a first linear frequency modulation signal; wherein the expression of the first linear frequency modulation signal is:

[0032] r(t)=s′(t)+n(t);

[0033] Wherein, r(t) is the first linear frequency modulation signal, s′(t) is the linear frequency modulation signal; n(t) is Gaussian noise;

[0034] Based on the maximum likelihood estimation algorithm, a first hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0035]

[0036] In the formula, is the first hypothesis signal; P(r(t)|s′(t)) is the conditional probability;

[0037] The likelihood function is solved by minimum mean square error to obtain the first hypothesis signal and use the first hypothesis signal as the estimated value of the linear frequency modulation signal; wherein the expression of the likelihood function is updated as follows:

[0038]

[0039] In the formula, ∥r(t)-s′(t)∥ 2 is the Euclidean distance between the first linear modulation signal and the hypothesized signal;

[0040] A phase coefficient of the first assumed signal is extracted, and the first assumed signal is mapped back to the data bit according to the phase coefficient and the mapping relationship.

[0041] In the above scheme, the original signal is extracted from the noise through the maximum likelihood estimation and minimum mean square error method to improve the signal reception quality. Through the mapping of phase coefficients to data bits, the transmitted data can be accurately restored to ensure the integrity and correctness of the data.

[0042] In one implementation, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, and further includes:

[0043] Based on the initial channel estimation value and the maximum likelihood estimation algorithm, an initial hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0044]

[0045] The initial channel estimation value is updated by a minimum mean square error filter to obtain a channel estimation update value; the likelihood function is re-solved based on the channel estimation update value and the maximum likelihood estimation algorithm until a preset cutoff condition is reached, and a hypothetical signal that makes the likelihood function take a maximum value is used as an estimation value of the linear frequency modulation signal.

[0046] In the above scheme, the estimation accuracy of the linear frequency modulation signal can be significantly improved by iteratively updating the channel estimation and signal estimation. The iterative process can better adapt to the changes in channel conditions and maintain the accuracy of signal estimation.

[0047] In a second aspect, the present application further provides a frequency-based signal modulation device, comprising: a first signal module, a second signal module and a signal restoration module;

[0048] The first signal module is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal;

[0049] The second signal module is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission;

[0050] The signal restoration module is used to control the receiving end to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

[0051] In the above scheme, the data bits to be transmitted are phase-encoded based on a preset phase encoding function. Nonlinear phase coding can increase the time-frequency localization characteristics of the signal, making the signal less susceptible to delay spread and frequency selective fading in a multipath environment. Through phase coding, more information can be embedded in each modulation symbol, thereby increasing the information density of the symbol. In a multipath propagation environment, time delays and frequency offsets may occur when the signal reaches the receiving end through different paths. Through the adaptive frequency slope, the frequency change of the signal can be dynamically adjusted to reduce the impact of the multipath effect. The adaptive frequency slope enables the receiving end to better track the frequency change of the signal, thereby improving the coherence and demodulation performance of the signal. The receiving end demodulates the signal through the maximum likelihood algorithm, which can effectively reduce the impact of Gaussian noise on signal demodulation and improve the detection performance and bit error rate performance of the signal.

[0052] In one implementation, the first signal module is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal, specifically including:

[0053] Obtain the number of data bits transmitted in a single symbol period, and construct a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values;

[0054] Acquire data bits to be transmitted, and perform phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is:

[0055] φ(t)=α0+α1t+α2t 2 ;

[0056] Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients;

[0057] A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is:

[0058] s(t)=Acos(2πf0t+φ(t));

[0059] Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

[0060] In one implementation, the second signal module is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission, specifically including:

[0061] Detect the signal-to-noise ratio condition of the real-time detection channel, and calculate the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is:

[0062]

[0063] Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; k max is the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed;

[0064] The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is:

[0065] f(t)=f0+k(t)×t;

[0066] Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time;

[0067] The instantaneous frequency is applied to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission; wherein the linear frequency modulation signal is expressed as:

[0068]

[0069] Where A is the signal amplitude; φ(t) is a quadratic polynomial function.

[0070] In one implementation, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, specifically including:

[0071] Obtain a first linear frequency modulation signal; wherein the expression of the first linear frequency modulation signal is:

[0072] r(t)=s′(t)+n(t);

[0073] Wherein, r(t) is the first linear frequency modulation signal, s′(t) is the linear frequency modulation signal; n(t) is Gaussian noise;

[0074] Based on the maximum likelihood estimation algorithm, a first hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0075]

[0076] In the formula, is the first hypothesis signal; P(r(t)|s′(t)) is the conditional probability;

[0077] The likelihood function is solved by minimum mean square error to obtain the first hypothesis signal and use the first hypothesis signal as the estimated value of the linear frequency modulation signal; wherein the expression of the likelihood function is updated as follows:

[0078]

[0079] In the formula, ∥r(t)-s′(t)∥ 2 is the Euclidean distance between the first linear modulation signal and the hypothesized signal;

[0080] A phase coefficient of the first assumed signal is extracted, and the first assumed signal is mapped back to the data bit according to the phase coefficient and the mapping relationship.

[0081] In one implementation, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, and further includes:

[0082] Based on the initial channel estimation value and the maximum likelihood estimation algorithm, an initial hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0083]

[0084] The initial channel estimation value is updated by a minimum mean square error filter to obtain a channel estimation update value; the likelihood function is re-solved based on the channel estimation update value and the maximum likelihood estimation algorithm until a preset cutoff condition is reached, and a hypothetical signal that makes the likelihood function take a maximum value is used as an estimation value of the linear frequency modulation signal.

[0085] In a third aspect, the present application also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, the frequency-based signal modulation method as described above is implemented.

[0086] In a fourth aspect, the present application also provides a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the frequency-based signal modulation method as described above. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 A schematic flow chart of a frequency-based signal modulation method provided in one embodiment of the present invention;

[0088] Figure 2 A schematic diagram of a module of a frequency-based signal modulation device provided in one embodiment of the present invention. DETAILED DESCRIPTION

[0089] The specific implementation of the present invention is further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0090] The terms "first" and "second" and the like in the specification, claims and drawings of this application are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0091] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0092] Example 1

[0093] See also Figure 1 , Figure 1 The flowchart of a frequency-based signal modulation method provided in an embodiment of the present invention is as follows. The embodiment of the present invention provides a frequency-based signal modulation method, including steps 101 to 103, each of which is as follows:

[0094] Step 101: phase-encode the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal.

[0095] In one embodiment, performing phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal specifically includes:

[0096] Obtain the number of data bits transmitted in a single symbol period, and construct a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values;

[0097] Acquire data bits to be transmitted, and perform phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is:

[0098] φ(t)=α0+α1t+α2t 2 ;

[0099] Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients;

[0100] A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is:

[0101] s(t)=Acos(2πf0t+φ(t));

[0102] Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

[0103] In the embodiment of the present invention, the transmitter obtains the data bit b[n] to be transmitted from the data source. The permutation and combination relationship of the binary value of the number of data bits transmitted in each symbol period is mapped to the combination of phase coding, and the quadratic polynomial function φ(t)=α0+α1t+α2t 2 Define the phase of the Chirp signal. By introducing the quadratic polynomial function, the phase change of the signal is more flexible, which can make full use of spectrum resources and improve spectrum efficiency. Assuming that the number of data bits transmitted in a single symbol period is N, there are 2 combinations of binary values ​​of data bits in a single symbol period. N There are four possible phase coding combinations, each of which corresponds to a set of phase coefficients (α0, α1, and α2). α0 represents the phase of the signal at t=0; α1 represents the linear change of the phase over time; α2 represents the nonlinear change of the phase over time. For example, assuming that two data bits are transmitted in each symbol period, and the binary value of the data bit is usually 0 or 1, there are four phase coding combinations in each period, namely 00, 01, 10, and 11, namely:

[0104] Bit 00: φ(t) = 0;

[0105] Bit 01: φ(t) = α1t;

[0106] Bit 10: φ(t) = α2t 2 ;

[0107] Bit 11: φ(t)=α1t+α2t 2 ;

[0108] For Bit 00: φ: α0 = 0, α1 = 0, α2 = 0; for Bit 01: α0 = 0, α1 = α1, α2 = 0; for Bit 10: α0 = 0, α1 = 0, α2 = α2; for Bit 11: α0 = 0, α1 = α1, α2 = α2. If the randomly selected binary permutation combination is [1, 0], the corresponding phase coefficient (α0, α1α2) = (100, 200, 100), then the generated phase encoding result is φ(t) = 100 + 200t + 100t 2 The initial linear frequency modulation signal generated is s(t)=Acos(2πf0t+100+200t+100t 2 ). By encoding the data bit b[n] through the quadratic polynomial function and mapping relationship, the encoding sequence φ[n] can be obtained.

[0109] Based on the above mapping relationship, each data bit combination corresponds to a unique phase encoding function. In different data bit combinations, the phase coefficient has different values, thereby realizing nonlinear phase modulation of the data bit. And each symbol period can represent four different phase encodings, thereby realizing the transmission of two bits of information per symbol period, instead of the traditional transmission of one information bit per symbol period. In the mapping relationship, a binary value permutation and combination is randomly selected as the phase encoding result, and the corresponding phase coefficient is obtained. By randomly selecting to generate a signal, the randomness of the signal can be increased and the probability of being intercepted or interfered can be reduced. It should be noted that the phase coefficient is a custom constant, which can be set according to the specific design or bandwidth limitation, and is not limited here. The starting frequency can be set according to the system and specific requirements, and is also not limited here.

[0110] Step 102: Generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission.

[0111] In one embodiment, the step of generating an adaptive frequency slope according to the channel condition detected in real time, and applying the adaptive frequency slope to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission specifically includes:

[0112] Detect the signal-to-noise ratio condition of the real-time detection channel, and calculate the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is:

[0113]

[0114] Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; k maxis the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed;

[0115] The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is:

[0116] f(t)=f0+k(t)×t;

[0117] Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time;

[0118] The instantaneous frequency is applied to the initial chirp signal to obtain the chirp signal for transmission.

[0119] In the embodiment of the present invention, the transmitter detects the signal-to-noise ratio condition of the current channel in real time by receiving feedback signals or using channel estimation technology. The signal-to-noise ratio is an important indicator for measuring channel quality, which is defined as the ratio of signal power to noise power. When the signal-to-noise ratio is low, the frequency slope is close to the minimum allowed frequency slope k. min , to reduce the frequency change rate of the signal and enhance the signal's anti-noise ability; when the signal-to-noise ratio is high, the frequency slope is close to the maximum allowed frequency slope k max , in order to increase the frequency change rate of the signal, make full use of the channel bandwidth, and improve the transmission efficiency. Then, a linear frequency modulation signal for transmission is generated according to the obtained frequency slope. Specifically, the frequency slope is applied to the initial linear frequency modulation signal, and the expression of the initial linear frequency modulation signal is updated to obtain the linear frequency modulation signal; wherein, the expression of the linear frequency modulation signal is:

[0120]

[0121] The linear frequency modulation signal is a signal transmitted on the baseband. In specific applications, the linear frequency modulation signal also needs to be up-converted to a carrier frequency f c , can be transmitted through the antenna. The linear frequency modulation signal expression after up-conversion is S(t)=s′(t)cos(2πf c t). Adaptive frequency slope adjustment can dynamically optimize the signal transmission performance according to the channel conditions and improve the anti-interference ability. The combination of nonlinear phase coding and adaptive frequency slope enables the system to support higher data rates under the same bandwidth.

[0122] Step 103: Control the receiving end to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

[0123] In one embodiment, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, specifically including:

[0124] Obtain a first linear frequency modulation signal; wherein the expression of the first linear frequency modulation signal is:

[0125] r(t)=s′(t)+n(t);

[0126] Wherein, r(t) is the first linear frequency modulation signal, s′(t) is the linear frequency modulation signal; n(t) is Gaussian noise;

[0127] Based on the maximum likelihood estimation algorithm, a first hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0128]

[0129] In the formula, is the first hypothesis signal; P(r(t)|s′(t)) is the conditional probability;

[0130] The likelihood function is solved by minimum mean square error to obtain the first hypothesis signal and use the first hypothesis signal as the estimated value of the linear frequency modulation signal; wherein the expression of the likelihood function is updated as follows:

[0131]

[0132] In the formula, ∥r(t)-s′(t)∥ 2 is the Euclidean distance between the first linear modulation signal and the hypothesized signal;

[0133] A phase coefficient of the first assumed signal is extracted, and the first assumed signal is mapped back to the data bit according to the phase coefficient and the mapping relationship.

[0134] The signal received at the receiving end will be affected by additive white Gaussian noise, so it is necessary to recover the linear frequency modulation signal transmitted by the receiving end from the noise. In the embodiment of the present invention, the maximum likelihood estimation algorithm is selected for signal recovery. The goal of maximum likelihood estimation is to select the hypothesized signal that maximizes the likelihood function. For Gaussian noise, maximum likelihood estimation is equivalent to minimizing the mean square error, that is, selecting the hypothesis signal with the smallest Euclidean distance between the hypothesis signal and the received first modulated signal as the first hypothesis signal, and using it as the estimated value of the first linear modulated signal. It should be noted that after completing the maximum likelihood estimation, The mapping relationship is mapped back to the original data bits. According to the phase decoding result and the pre-built mapping relationship, the first hypothesis signal at the receiving end is mapped back to the original data bits at the transmitting end. Through maximum likelihood estimation, the system can effectively deal with additive white Gaussian noise and improve the accuracy of signal recovery.

[0135] In one embodiment, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, and further includes:

[0136] Based on the initial channel estimation value and the maximum likelihood estimation algorithm, an initial hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0137]

[0138] The initial channel estimation value is updated by a minimum mean square error filter to obtain a channel estimation update value; the likelihood function is re-solved based on the channel estimation update value and the maximum likelihood estimation algorithm until a preset cutoff condition is reached, and a hypothetical signal that makes the likelihood function take a maximum value is used as an estimation value of the linear frequency modulation signal.

[0139] In an embodiment of the present invention, the signal estimation value and the linear modulation signal estimation value are repeatedly updated through an iterative detection mechanism, thereby improving the accuracy of demodulation. Specifically, the received first linear modulation signal is demodulated by the initial channel estimation value to obtain an initial hypothesis signal. It should be noted that the initial channel estimation value is determined comprehensively based on multiple factors such as the pilot signal, training sequence, channel model, signal-to-noise ratio, multipath effect, mobile speed, algorithm complexity and environmental factors, and can also be directly solved by the least square method and the minimum mean square error. Then, the channel estimation value is updated using the initial hypothesis signal and the minimum mean square error filter to obtain the channel estimation update value. Among them, the expression of the channel estimation update value and the expression of the minimum mean square error filter are:

[0140]

[0141] Where h is the channel; is the hypothesized signal obtained in the previous iteration; H is the channel matrix; is the noise variance; I is the noise variance.

[0142] In a multi-antenna system, H is usually a complex matrix. Then, based on the obtained channel estimation update value and the maximum likelihood estimation algorithm, the likelihood function is recalculated until the preset cutoff condition is reached. The cutoff conditions include: reaching the preset maximum number of iterations, the change in the solution result is less than the preset threshold, and the bit error rate is less than the preset threshold. When the iteration meets any of the above cutoff conditions, the solution of the channel estimation update value can be terminated, and the hypothetical signal that makes the likelihood function take the maximum value at this time is used as the estimated value of the linear frequency modulation signal. Through the above-mentioned iterative detection mechanism, the system can gradually improve the accuracy of symbol estimation and effectively deal with the complexity brought by nonlinear phase coding, thereby achieving higher demodulation performance and lower bit error rate.

[0143] In an embodiment of the present invention, a frequency-based signal modulation device is also provided, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, the above-mentioned frequency-based signal modulation method is implemented.

[0144] In an embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute the above-mentioned frequency-based signal modulation method.

[0145] Exemplarily, the computer program can be divided into one or more modules, one or more modules are stored in the memory and executed by the processor to complete the present invention. One or more modules can be a series of computer program instruction segments that can complete specific functions, and the instruction segments are used to describe the execution process of the computer program in the frequency-based signal modulation device.

[0146] The frequency-based signal modulation device may be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The frequency-based signal modulation device may include, but is not limited to, a processor, a memory, and a display. Those skilled in the art may understand that the above components are merely examples of frequency-based signal modulation devices and do not constitute a limitation on frequency-based signal modulation devices. More or fewer components may be included, or some components may be combined, or different components may be included. For example, the frequency-based signal modulation device may also include input and output devices, network access devices, buses, etc.

[0147] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the frequency-based signal modulation device, and uses various interfaces and lines to connect the various parts of the entire frequency-based signal modulation device.

[0148] The memory can be used to store computer programs and / or modules. The processor realizes various functions of the frequency-based signal modulation device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, a text conversion function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, text message data, etc.), etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0149] Wherein, if the module based on the modulation of the frequency-based signal is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0150] The embodiment of the present invention provides a frequency-based signal modulation method, which performs phase encoding on the data bits to be transmitted based on a preset phase encoding function. Nonlinear phase encoding can increase the time-frequency localization characteristics of the signal, so that the signal is not easily affected by delay spread and frequency selective fading in a multipath environment. Through phase encoding, more information can be embedded in each modulation symbol, thereby improving the information density of the symbol. In a multipath propagation environment, time delay and frequency offset may occur when the signal reaches the receiving end through different paths. Through the adaptive frequency slope, the frequency change of the signal can be dynamically adjusted to reduce the impact of the multipath effect. The adaptive frequency slope enables the receiving end to better track the frequency change of the signal, thereby improving the coherence and demodulation performance of the signal. The receiving end demodulates the signal through the maximum likelihood algorithm, which can effectively reduce the impact of Gaussian noise on signal demodulation and improve the detection performance and bit error rate performance of the signal.

[0151] Example 2

[0152] See also Figure 2 , Figure 2 Schematic diagram of a module of a frequency-based signal modulation device provided in an embodiment of the present invention. The embodiment of the present invention provides a frequency-based signal modulation device, including: a first signal module 201, a second signal module 202 and a signal restoration module 203;

[0153] The first signal module 201 is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal;

[0154] The second signal module 202 is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission;

[0155] The signal restoration module 203 is used to control the receiving end to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

[0156] In one embodiment, the first signal module is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal, specifically including: obtaining the number of data bits transmitted in a single symbol period, and constructing a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values; obtaining the data bits to be transmitted, and performing phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is:

[0157] φ(t)=α0+α1t+α2t 2 ;

[0158] Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients;

[0159] A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is:

[0160] s(t)=Acos(2πf0t+φ(t));

[0161] Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

[0162] In one embodiment, the second signal module is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission, specifically including: detecting the signal-to-noise ratio condition of the real-time detection channel, and calculating the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is:

[0163]

[0164] Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; kmax is the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed;

[0165] The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is:

[0166] f(t)=f0+k(t)×t;

[0167] Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time;

[0168] The instantaneous frequency is applied to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission; wherein the linear frequency modulation signal is expressed as:

[0169]

[0170] Where A is the signal amplitude; φ(t) is a quadratic polynomial function.

[0171] In one embodiment, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, specifically including:

[0172] Obtain a first linear frequency modulation signal; wherein the expression of the first linear frequency modulation signal is:

[0173] r(t)=s′(t)+n(t);

[0174] Wherein, r(t) is the first linear frequency modulation signal, s′(t) is the linear frequency modulation signal; n(t) is Gaussian noise;

[0175] Based on the maximum likelihood estimation algorithm, a first hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0176]

[0177] In the formula, is the first hypothesis signal; P(r(t)|s′(t)) is the conditional probability;

[0178] The likelihood function is solved by minimum mean square error to obtain the first hypothesis signal and use the first hypothesis signal as the estimated value of the linear frequency modulation signal; wherein the expression of the likelihood function is updated as follows:

[0179]

[0180] In the formula, ∥r(t)-s′(t)∥ 2 is the Euclidean distance between the first linear modulation signal and the hypothesized signal;

[0181] A phase coefficient of the first assumed signal is extracted, and the first assumed signal is mapped back to the data bit according to the phase coefficient and the mapping relationship.

[0182] In one embodiment, the controlling receiving end restores the received first linear frequency modulation signal based on a maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, and further includes:

[0183] Based on the initial channel estimation value and the maximum likelihood estimation algorithm, an initial hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is:

[0184]

[0185] The initial channel estimation value is updated by a minimum mean square error filter to obtain a channel estimation update value; the likelihood function is re-solved based on the channel estimation update value and the maximum likelihood estimation algorithm until a preset cutoff condition is reached, and a hypothetical signal that makes the likelihood function take a maximum value is used as an estimation value of the linear frequency modulation signal.

[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the device described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0187] The embodiment of the present invention provides a frequency-based signal modulation device, which performs phase encoding on the data bits to be transmitted based on a preset phase encoding function. The nonlinear phase encoding can increase the time-frequency localization characteristics of the signal, so that the signal is not easily affected by delay spread and frequency selective fading in a multipath environment. Through phase encoding, more information can be embedded in each modulation symbol, thereby improving the information density of the symbol. In a multipath propagation environment, time delay and frequency offset may occur when the signal reaches the receiving end through different paths. Through the adaptive frequency slope, the frequency change of the signal can be dynamically adjusted to reduce the impact of the multipath effect. The adaptive frequency slope enables the receiving end to better track the frequency change of the signal, thereby improving the coherence and demodulation performance of the signal. The receiving end demodulates the signal through the maximum likelihood algorithm, which can effectively reduce the impact of Gaussian noise on signal demodulation and improve the detection performance and bit error rate performance of the signal.

[0188] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present invention. These improvements and substitutions should also be regarded as the scope of protection of the present invention.

Claims

1. A frequency-based signal modulation method, characterized in that: include: Phase encoding the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal; generating an adaptive frequency slope according to a channel condition detected in real time, and applying the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission; The receiving end is controlled to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

2. A frequency-based signal modulation method as claimed in claim 1, characterized in that: The phase encoding of the data bits to be transmitted based on the preset phase encoding function to generate the initial linear frequency modulation signal specifically includes: Obtain the number of data bits transmitted in a single symbol period, and construct a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values; Acquire data bits to be transmitted, and perform phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is: φ(t)=α0+α1t+α2t 2 ; Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients; A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is: s(t)=Acos(2πf0t+φ(t)); Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

3. A frequency-based signal modulation method as claimed in claim 2, characterized in that: The step of generating an adaptive frequency slope according to the channel condition detected in real time, and applying the adaptive frequency slope to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission specifically includes: Detect the signal-to-noise ratio condition of the real-time detection channel, and calculate the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is: Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; k max is the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed; The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is: f(t)=f0+k(t)×t; Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time; The instantaneous frequency is applied to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission; wherein the linear frequency modulation signal is expressed as: Where A is the signal amplitude; φ(t) is a quadratic polynomial function.

4. A frequency-based signal modulation method as claimed in claim 2, characterized in that: The controlling receiving end restores the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, specifically including: Obtain a first linear frequency modulation signal; wherein the expression of the first linear frequency modulation signal is: r(t)=s′(t)+n(t); Wherein, r(t) is the first linear frequency modulation signal, s′(t) is the linear frequency modulation signal; n(t) is Gaussian noise; Based on the maximum likelihood estimation algorithm, a first hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is: In the formula, is the first hypothesis signal; P(r(t)|s′(t)) is the conditional probability; The likelihood function is solved by minimum mean square error to obtain the first hypothesis signal and use the first hypothesis signal as the estimated value of the linear frequency modulation signal; wherein the expression of the likelihood function is updated as follows: In the formula, ||r(t)-s′(t)|| 2 is the Euclidean distance between the first linear modulation signal and the hypothesized signal; A phase coefficient of the first assumed signal is extracted, and the first assumed signal is mapped back to the data bit according to the phase coefficient and the mapping relationship.

5. A frequency-based signal modulation method as claimed in claim 1, characterized in that: The controlling receiving end restores the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal, and further includes: Based on the initial channel estimation value and the maximum likelihood estimation algorithm, an initial hypothesis signal that maximizes the likelihood function is obtained; wherein the expression of the likelihood function is: The initial channel estimation value is updated by a minimum mean square error filter to obtain a channel estimation update value; the likelihood function is re-solved based on the channel estimation update value and the maximum likelihood estimation algorithm until a preset cutoff condition is reached, and a hypothetical signal that makes the likelihood function take a maximum value is used as an estimation value of the linear frequency modulation signal.

6. A frequency-based signal modulation device, characterized in that: include: A first signal module, a second signal module and a signal restoration module; The first signal module is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal; The second signal module is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission; The signal restoration module is used to control the receiving end to restore the received first linear frequency modulation signal based on the maximum likelihood algorithm to obtain an estimated value of the linear frequency modulation signal; wherein the first linear frequency modulation signal includes the linear frequency modulation signal and Gaussian noise.

7. A frequency-based signal modulation device as claimed in claim 6, characterized in that: The first signal module is used to perform phase encoding on the data bits to be transmitted based on a preset phase encoding function to generate an initial linear frequency modulation signal, specifically including: Obtain the number of data bits transmitted in a single symbol period, and construct a mapping relationship between data bits and phase coefficients based on the binary value permutations and combinations of the data bits in the single symbol period; wherein each of the binary value permutations and combinations corresponds to a set of phase coefficient values; Acquire data bits to be transmitted, and perform phase encoding on the data bits based on a quadratic polynomial function to obtain a phase encoding sequence; wherein the expression of the quadratic polynomial function is: φ(t)=α0+α1t+α2t 2 ; Where φ(t) is a quadratic polynomial function; α0, α1 and α2 are phase coefficients; A binary value permutation combination is randomly selected from the mapping relationship as a phase encoding result, and the initial linear frequency modulation signal is generated according to the phase encoding result; wherein the expression of the initial linear frequency modulation signal is: s(t)=Acos(2πf0t+φ(t)); Where A is the signal amplitude; f0 is the starting frequency; t is the time; φ(t) is the quadratic polynomial function.

8. A frequency-based signal modulation device as claimed in claim 6, characterized in that: The second signal module is used to generate an adaptive frequency slope according to the channel condition detected in real time, and apply the adaptive frequency slope to the initial linear frequency modulation signal to obtain a linear frequency modulation signal for transmission, specifically including: Detect the signal-to-noise ratio condition of the real-time detection channel, and calculate the frequency slope according to the signal-to-noise ratio condition; wherein the expression of the frequency slope is: Where k(t) is the frequency slope that changes with time; k min is the minimum frequency slope allowed; k max is the maximum frequency slope allowed; SNR(t) is the signal-to-noise ratio at the current moment; SNR min is the minimum allowed signal-to-noise ratio; SNR max is the maximum signal-to-noise ratio allowed; The instantaneous frequency of the linear frequency modulation signal is generated according to the frequency slope; wherein the expression of the instantaneous frequency is: f(t)=f0+k(t)×t; Where f(t) is the instantaneous frequency; f0 is the starting frequency; k(t) is the frequency slope that changes with time; The instantaneous frequency is applied to the initial linear frequency modulation signal to obtain the linear frequency modulation signal for transmission; wherein the linear frequency modulation signal is expressed as: Where A is the signal amplitude; φ(t) is a quadratic polynomial function.

9. A terminal device, characterized in that: The invention comprises a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the frequency-based signal modulation method according to any one of claims 1 to 5 is implemented when the processor executes the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the frequency-based signal modulation method according to any one of claims 1 to 5.

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