A communication-sensing integrated waveform design method based on reference signal

Abstract

The present invention discloses a communication perception integrated waveform design method based on reference signals, which belongs to the field of communication technology and solves the technical problem that the structure of existing reference signals is fixed and affects the effective use of wireless resources. The method is: reconstructing the structure of the reference signal based on the orthogonal frequency division multiplexing OFDM frame structure, that is, within a coherent processing interval CPI, the reference signal is uniformly inserted into a two-dimensional time-frequency resource grid in a rectangular discrete manner, and an OFDM symbol and a subcarrier constitute a resource unit RE; a CPI is composed of OFDM symbols and subcarriers, M OFDM symbols and N subcarriers are used for perception, and the rest are used for communication; the reference signal interval in the time domain is, and the interval in the frequency domain is; adjusting the interval in the time domain and the frequency domain, deriving the weighted sum of the distance estimation and speed estimation CRB, and the communication rate, minimizing the weighted sum of the CRB under the threshold constraint of ensuring the communication rate, and obtaining an ISAC waveform that meets different communication and perception performance requirements.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and more specifically, to a communication-perception integrated waveform design method based on a reference signal. Background Art

[0002] With the rapid development of communication technology, the next generation of communication technology (Sixth-Generation, 6G) will achieve high-precision target perception while achieving high-speed communication, so that the physical world can be seamlessly mapped to the digital world, which is crucial for applications in scenarios such as low-altitude drones, traffic vehicle networks, and even the metaverse. Integrated Sensing and Communication (ISAC) jointly designs the functions of communication and perception by sharing hardware and spectrum resources to improve spectrum efficiency. However, since communication waveforms are usually designed to send random communication data, and perception waveforms are usually designed to have constant envelope characteristics, the design purposes of communication and perception waveforms are different, and their design requirements are also different. Therefore, in the ISAC system, integrated waveform design is the focus of research, which can greatly improve the synergistic gain of communication and perception.

[0003] ISAC waveform design is generally divided into three categories: communication-oriented waveform design, perception-oriented waveform design, and joint waveform design. Communication-oriented waveform design refers to adding perception functions to the existing mobile communication system standards without making major modifications to the cellular system. It is usually based on orthogonal frequency division multiplexing (OFDM) technology and is a more direct and low-cost approach. In addition, perception-oriented waveform design refers to embedding communication data in the perception waveform. Although it has excellent perception performance, it will greatly limit the performance of communication. In order to achieve a highly unified integrated waveform, the joint waveform design aims to build the ISAC waveform from scratch rather than based on an existing waveform.

[0004] In the integrated OFDM waveform design based on reference signals, its ISAC system is highly compatible with the physical layer of the current communication system, which helps to achieve a smooth evolution to 6G. Usually, a reference signal is inserted in the process of binary data modulation for channel estimation. It is a fixed sequence with strong autocorrelation and has the potential to be applied to radar perception. The reference signals of the existing OFDM communication system include synchronization signals, demodulation reference signals, channel state information reference signals, positioning reference signals, etc., and their structures are fixed. The perception performance of synchronization signals and demodulation reference signals can be analyzed by self-ambiguity functions and cross-ambiguity functions. Compared with synchronization signals, demodulation reference signals and channel state information reference signals, the feasibility and superiority of the perception performance of positioning reference signals are better. However, the structure of these reference signals is fixed, which limits the perception ability. Therefore, it is necessary to build a more flexible reference signal in the ISAC system to realize ISAC waveform design.

[0005] In the existing ISAC system based on reference signals, the reference signals used for perception are usually synchronization signals, demodulation reference signals, channel state information reference signals, positioning reference signals, etc. in the communication system. The structures of these reference signals are fixed, and it is difficult to design the performance of perception and communication, which affects the effective use of wireless resources. For example, since the distribution patterns of the time-frequency resources corresponding to the demodulation reference signal and the positioning reference signal are different and limited in number, different reference signals correspond to different and limited perception performance. Summary of the invention

[0006] The technical problem to be solved by the present invention is to address the above-mentioned deficiencies in the prior art. The purpose of the present invention is to provide a communication-perception integrated waveform design method based on a reference signal, which can design a flexible reference signal structure to meet the performance requirements of perception and communication in different scenarios.

[0007] The technical solution of the present invention is: a communication perception integrated waveform design method based on a reference signal, which reconstructs the structure of the reference signal on the basis of an orthogonal frequency division multiplexing OFDM frame structure, thereby designing a communication perception integrated waveform;

[0008] Specifically, within a coherent processing interval CPI, the reference signal is uniformly inserted into a two-dimensional time-frequency resource grid in a rectangular discrete manner, and an OFDM symbol and a subcarrier constitute a resource unit RE;

[0009] The specific parameters are: a CPI is composed of OFDM symbols and subcarriers, of which M OFDM symbols and N subcarriers are used for sensing, and the rest are used for communication; the interval of the reference signal in the time domain is , the interval in the frequency domain is ;

[0010] By adjusting the interval of the reference signal in the time domain and frequency domain, the weighted sum of the CRBs for distance estimation and speed estimation, as well as the communication rate under the mean square error of channel estimation are derived, so that the weighted sum of CRBs is minimized under the threshold constraint of ensuring the communication rate, and an ISAC waveform that meets different communication and perception performance requirements is obtained.

[0011] As a further improvement, the following steps are included:

[0012] Step 1. Obtain the resource distribution of the communication and sensing reference signal RE in a CPI. The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform, converts the symbols into analog signals, and sends them to the user end on the carrier frequency.

[0013] Step 2. The user end performs channel estimation based on the reference signal received in the ISAC signal and transforms it into the frequency domain through Fourier transform, obtains the mean square error of the channel estimation error, and then obtains the communication rate of the user end;

[0014] Step 3. The user end also acts as a sensing target and reflects the ISAC signal back to the base station. The base station derives the distance and speed estimation CRB based on the reference signal in the echo signal and establishes the weighted sum of the distance and speed estimation CRB.

[0015] Step 4. Based on the derived communication rate and CRB weighted sum, establish the problem of minimizing the CRB weighted sum under the threshold constraint of ensuring the communication rate, and transform the original non-convex problem into a convex problem through relaxation and approximation methods. The CVX tool can be directly used to obtain the interval of the reference signal in the time domain and frequency domain, that is, to obtain a compromise between communication and perception performance.

[0016] Furthermore, a two-dimensional time-frequency resource grid in CPI is initialized and the reference signal is evenly distributed in a rectangular manner, including OFDM symbols and subcarriers , and the reference signal in the time domain interval and frequency domain spacing ;

[0017] The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform. The signal sent by the base station in the tth time slot can be expressed as:

[0018] (1);

[0019] in, represents the modulation symbol used for communication, and Represent the index of subcarrier and OFDM symbol respectively; represents the modulation symbol used for perception, and Represent the index of subcarrier and OFDM symbol respectively; Indicates the subcarrier spacing; Indicates the duration of each OFDM symbol; represents the rectangular function j represents the imaginary unit, .

[0020] Furthermore, the user end, as the receiving end of the communication data, converts the received time domain signal into the frequency domain after Fourier transform, and the modulation symbol received by the user end It can be expressed as:

[0021] (2);

[0022] in, represents the sent communication and the perceived modulation symbols, and , r and u represent the indices of subcarrier and OFDM symbol respectively; represents the channel gain of the transmission from the base station to the user; represents zero mean and has a variance of cyclically symmetric complex Gaussian noise.

[0023] Furthermore, in the channel estimation process, the channel error It is mainly caused by imperfect estimation filters and noise, and can be expressed as:

[0024] (3);

[0025] in, Indicates channel information of a reference signal; represents the filter error, and is an ideal filter; represents a non-ideal filter; express In the reference signal density The sampling noise under has zero mean and variance The cyclically symmetric complex Gaussian noise is ;

[0026] Channel Error After two-dimensional discrete Fourier transform and Parseval theorem, the mean square error of channel estimation is It can be expressed as:

[0027] (4);

[0028] in, Indicates the original channel The sampling of power spectral density, that is ; exist The two-dimensional Fourier transform in the range is ; The linear interpolator can be expressed as:

[0029] ;

[0030] By using the second-order Taylor approximation, the mean square error of the channel estimation is It can be approximately expressed as:

[0031] (5);

[0032] in, and denote the z-order moment of the Doppler spectrum and power delay distribution, respectively.

[0033] Furthermore, in a CPI, the mean square error of the channel estimation based on Formula 5 is , the communication rate of the ISAC system can be expressed as:

[0034] (6);

[0035] in, is the average gain of the lth path, is the variance of the frequency domain estimator.

[0036] Furthermore, the user end also acts as a sensing target to reflect the ISAC signal back to the base station side. The base station receives the signal and samples it through matched filtering, retains only the reference signal, and transforms it into the frequency domain through Fourier transform. The received modulation symbol It can be expressed as:

[0037] (7);

[0038] Among them, R and v represent the relative distance and speed between the sensing target and the base station; represents the carrier center frequency; c represents the speed of light; represents zero mean and has a variance of Circularly symmetric complex Gaussian noise;

[0039] in As the reference signal is a known symbol, it can be obtained from Remove it and keep only the estimated vector The relevant information can be expressed as:

[0040] (8);

[0041] in, is the noise term;

[0042] By estimating the vector The inverse of the Fisher information matrix is ​​used to obtain the perceived CRB matrix. First, the Fisher information matrix is ​​given for:

[0043] (9);

[0044] Among them, each element in the matrix can be expressed as:

[0045] (10);

[0046] in, and ; express The conditional probability density function of ;

[0047] By calculation The inverse matrix of can obtain the CRB of distance and speed respectively:

[0048] (11);

[0049] (12);

[0050] in, as well as ;

[0051] Through and The weighted sum is used as the perceptual performance in the ISAC system and can be expressed as:

[0052] (13);

[0053] in, is a weighting factor that balances the importance of distance and speed estimation under different requirements.

[0054] Furthermore, in order to design the interval of the reference signal, the weighted sum of the perceived CRBs is minimized under the condition of ensuring the minimum threshold of the user communication rate, that is, the following optimization problem is solved:

[0055] (14);

[0056] in, Indicates the minimum communication rate threshold;

[0057] In a CPI, usually and , then the weighted sum of the perceived CRB can be approximated as:

[0058] (15);

[0059] The interval parameter of the reference signal in the constraint is relaxed from an integer variable to a continuous variable. Through relaxation and approximation, the optimization problem of formula (14) can be transformed into:

[0060] (16);

[0061] The transformed optimization problem is a convex optimization problem, which can be directly solved using the CVX tool to obtain the reference signal interval, that is, to obtain a compromise between communication and perception performance.

[0062] Beneficial Effects

[0063] Compared with the prior art, the present invention has the following advantages:

[0064] 1. The reference signals of the present invention are uniformly inserted into a two-dimensional time-frequency resource grid in a rectangular discrete manner, and the requirements of different perception and communication performances are met by adjusting the intervals of the time domain and frequency domain reference signals.

[0065] 2. The present invention jointly optimizes the interval of reference signals in the time domain and the frequency domain by deriving the Cramé-Rao bound (CRB) under distance and speed estimation and the communication rate under the mean square error of channel estimation.

[0066] 3. The present invention solves the optimization problem of minimizing the weighted sum of perceived CRBs under the condition of ensuring the minimum threshold of user communication rate, and converts the original non-convex optimization problem into a convex optimization problem through relaxation and approximation methods, which can quickly solve and obtain approximate results with small errors. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 A distribution pattern diagram of the reference signal in the two-dimensional time-frequency resource in the present invention;

[0068] Figure 2 It is a system model diagram in the present invention;

[0069] Figure 3 It is a trade-off curve diagram of the minimum communication rate and the weighted sum of the perceived CRB in the present invention. DETAILED DESCRIPTION

[0070] The present invention will be further described below with reference to the specific embodiments in the accompanying drawings.

[0071] The purpose of the present invention is to solve the problem of limited perception performance of the existing ISAC system based on reference signals. It is intended to construct a flexible reference signal structure and establish a communication and perception integrated system transmission model. By deriving the Cramer-Rao bound (CRB) under distance and speed estimation and the communication rate under the mean square error of channel estimation, the reference signal intervals in the time domain and frequency domain are jointly optimized, and the perception performance under different communication rate constraints is studied to obtain a performance compromise between communication and perception.

[0072] See also Figure 1 to Figure 3 The method of the present invention takes a base station and a user end as an example. The base station is used as a transceiver integrating communication and perception. The user end is used as a communication receiver and at the same time as a perception target to reflect the communication and perception integrated echo signal to the base station side. The base station analyzes the received echo to obtain the perception parameters. Specifically, Figure 2 shown.

[0073] A communication-perception integrated waveform design method based on reference signals is proposed. In order to meet the different needs of communication and perception, the structure of the reference signal is reconstructed on the basis of the OFDM frame structure, so as to design a communication-perception integrated waveform. Specifically, within a coherent processing interval CPI, the reference signal is uniformly inserted into a two-dimensional time-frequency resource grid in a rectangular discrete manner. An OFDM symbol and a subcarrier constitute a resource unit RE. The filled RE represents the reference signal for perception, and the blank RE is used to transmit communication data, such as Figure 1 As shown in the figure. The specific parameters are: a CPI consists of OFDM symbols and There are M OFDM symbols and N subcarriers for sensing, and the rest for communication. The reference signal interval in the time domain is , the interval in the frequency domain is By adjusting the interval of the reference signal in the time domain and frequency domain, the weighted sum of the distance estimation and speed estimation CRBs, as well as the communication rate under the mean square error of the channel estimation are derived, so that the weighted sum of the CRBs is minimized under the threshold constraint of ensuring the communication rate, and an ISAC waveform that meets different communication and perception performance requirements is obtained.

[0074] The implementation of this method includes the following steps:

[0075] Step 1. Obtain the resource distribution of the communication and sensing reference signal RE in a CPI. The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform, converts the symbols into analog signals, and sends them to the user end on the carrier frequency.

[0076] Step 2. The user end performs channel estimation (i.e., demodulation of auxiliary communication data) based on the reference signal received in the ISAC signal and through Fourier transform to the frequency domain, obtains the mean square error of the channel estimation error, and then obtains the communication rate of the user end;

[0077] Step 3. The user end also acts as a sensing target and reflects the ISAC signal back to the base station. The base station derives the distance and speed estimation CRB based on the reference signal in the echo signal and establishes the weighted sum of the distance and speed estimation CRB.

[0078] Step 4. Based on the derived communication rate and CRB weighted sum, establish the problem of minimizing the CRB weighted sum under the threshold constraint of ensuring the communication rate, and transform the original non-convex problem into a convex problem through relaxation and approximation methods. The CVX tool can be directly used to obtain the interval of the reference signal in the time domain and frequency domain, that is, to obtain a compromise between communication and perception performance.

[0079] The following is a more detailed description of the process in which a base station sends an ISAC signal, a user terminal receives it, and the user terminal, as a sensing target, reflects the echo signal to the base station as a scenario:

[0080] Initialize a two-dimensional time-frequency resource grid in CPI and the reference signal is evenly distributed in a rectangular manner, including OFDM symbols and subcarriers , and the reference signal in the time domain interval and frequency domain spacing .

[0081] The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform. The signal sent by the base station in the tth time slot can be expressed as:

[0082] (1);

[0083] in, represents the modulation symbol used for communication, and Represent the index of subcarrier and OFDM symbol respectively; represents the modulation symbol used for perception, and Represent the index of subcarrier and OFDM symbol respectively; Indicates the subcarrier spacing; Indicates the duration of each OFDM symbol; represents the rectangular function j represents the imaginary unit, .

[0084] The user end is the receiving end of the communication data. The received time domain signal is converted to the frequency domain after Fourier transform. The modulation symbol received by the user end It can be expressed as:

[0085] (2);

[0086] in, represents the sent communication and the perceived modulation symbols, and , r and u represent the indices of subcarrier and OFDM symbol respectively; represents the channel gain of the transmission from the base station to the user; represents zero mean and has a variance of cyclically symmetric complex Gaussian noise.

[0087] In the channel estimation process, the channel error It is mainly caused by imperfect estimation filters and noise, and can be expressed as:

[0088] (3);

[0089] in, Indicates channel information of a reference signal; represents the filter error, and is an ideal filter; represents a non-ideal filter; express In the reference signal density The sampling noise under has zero mean and variance The cyclically symmetric complex Gaussian noise is .

[0090] Channel Error After two-dimensional discrete Fourier transform and Parseval theorem, the mean square error of channel estimation is It can be expressed as:

[0091] (4);

[0092] in, Indicates the original channel The sampling of power spectral density, that is ; exist The two-dimensional Fourier transform in the range is ; The linear interpolator can be expressed as:

[0093] .

[0094] By using the second-order Taylor approximation, the mean square error of the channel estimation is It can be approximately expressed as:

[0095] (5);

[0096] in, and denote the z-order moment of the Doppler spectrum and power delay distribution, respectively.

[0097] In a CPI, the mean square error of the channel estimation based on Equation 5 is , the communication rate of the ISAC system can be expressed as:

[0098] (6);

[0099] in, is the average gain of the lth path, is the variance of the frequency domain estimator.

[0100] From Formula 6, we can get the influence of the reference signal interval on the communication rate.

[0101] The user end also acts as a sensing target and reflects the ISAC signal back to the base station. The base station receives the signal and samples it through matched filtering, retaining only the reference signal, and transforms it into the frequency domain through Fourier transform. The received modulation symbol It can be expressed as:

[0102] (7);

[0103] Among them, R and v represent the relative distance and speed between the sensing target and the base station; represents the carrier center frequency; c represents the speed of light; represents zero mean and has a variance of cyclically symmetric complex Gaussian noise.

[0104] in As the reference signal is a known symbol, it can be obtained from Remove it and keep only the estimated vector The relevant information can be expressed as:

[0105] (8);

[0106] in, is the noise term.

[0107] By estimating the vector The inverse of the Fisher information matrix is ​​used to obtain the perceived CRB matrix. First, the Fisher information matrix is ​​given for:

[0108] (9);

[0109] Among them, each element in the matrix can be expressed as:

[0110] (10);

[0111] in, and ; express The conditional probability density function of .

[0112] By calculation The inverse matrix of can obtain the CRB of distance and speed respectively:

[0113] (11);

[0114] (12);

[0115] in, as well as .

[0116] Through and The weighted sum is used as the perceptual performance in the ISAC system and can be expressed as:

[0117] (13);

[0118] in, is a weighting factor that balances the importance of distance and speed estimation under different requirements.

[0119] From formula 13, we can get the influence of the reference signal interval on the perceived CRB weighted sum.

[0120] To design the interval of the reference signal, the weighted sum of the perceived CRBs is minimized under the condition of ensuring the minimum threshold of the user communication rate, that is, to solve the following optimization problem:

[0121] (14);

[0122] in, It represents the minimum communication rate threshold. The problem is analyzed as a mixed integer problem, which is difficult to handle and can be processed in the next step.

[0123] In a CPI, usually and , then the weighted sum of the perceived CRB can be approximated as:

[0124] (15);

[0125] And the interval parameter of the reference signal in the constraint is relaxed from an integer variable to a continuous variable. Through relaxation and approximation, the optimization problem of formula (14) can be transformed into:

[0126] (16);

[0127] That is, the transformed optimization problem is a convex optimization problem, which can be directly solved using the CVX tool to obtain the reference signal interval, that is, to obtain a compromise between communication and perception performance.

[0128] The analysis method proposed in this technical solution is numerically simulated and compared with the exhaustive solution method of the original problem. The performance trade-off curve between communication and perception is as follows: Figure 3 The results show that although the exhaustive method can obtain the optimal result, the computational complexity is high, while our method can quickly solve the approximate result with a small error.

[0129] The above are only preferred embodiments of the present invention. It should be pointed out that for those skilled in the art, several modifications and improvements can be made without departing from the structure of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. A communication-sensing integrated waveform design method based on reference signals, characterized in that: Reconstruct the structure of the reference signal based on the OFDM frame structure to design a waveform that integrates communication and perception; Specifically, within a coherent processing interval CPI, the reference signal is uniformly inserted into a two-dimensional time-frequency resource grid in a rectangular discrete manner, and an OFDM symbol and a subcarrier constitute a resource unit RE; The specific parameters are: a CPI is composed of OFDM symbols and subcarriers, of which M OFDM symbols and N subcarriers are used for sensing, and the rest are used for communication; the interval of the reference signal in the time domain is , the interval in the frequency domain is ; Based on the interval parameters of the reference signal in the time domain and frequency domain, the weighted sum of the CRBs for distance estimation and speed estimation, as well as the communication rate under the mean square error of channel estimation are derived, so that the weighted sum of CRBs is minimized under the threshold constraint of ensuring the communication rate, and an ISAC waveform that meets different communication and perception performance requirements is obtained.

2. According to claim 1, a communication perception integrated waveform design method based on reference signal is characterized in that: The following steps are involved: Step 1. Obtain the resource distribution of the communication and sensing reference signal RE in a CPI. The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform, converts the symbols into analog signals, and sends them to the user end on the carrier frequency. Step 2. The user end performs channel estimation based on the reference signal received in the ISAC signal and converts it into the frequency domain through Fourier transform, obtains the mean square error of the channel estimation error, and then obtains the communication rate of the user end; Step 3. The user end also acts as a sensing target and reflects the ISAC signal back to the base station. The base station derives the distance and speed estimation CRB based on the reference signal in the echo signal and establishes the weighted sum of the distance and speed estimation CRB. Step 4. Based on the derived communication rate and CRB weighted sum, establish the problem of minimizing the CRB weighted sum under the threshold constraint of ensuring the communication rate, and transform the original non-convex problem into a convex problem through relaxation and approximation methods. The CVX tool can be directly used to obtain the interval of the reference signal in the time domain and frequency domain, that is, to obtain a compromise between communication and perception performance.

3. The communication-aware integrated waveform design method based on reference signal according to claim 2 is characterized in that: Initialize a two-dimensional time-frequency resource grid in CPI and the reference signal is evenly distributed in a rectangular manner, including OFDM symbols and subcarriers , and the reference signal in the time domain interval and frequency domain spacing ; The ISAC base station converts the modulation symbols in the two-dimensional time-frequency resources in the CPI into the time domain through inverse Fourier transform. The signal sent by the base station in the tth time slot can be expressed as: (1)； in, represents the modulation symbol used for communication, and Represent the index of subcarrier and OFDM symbol respectively; represents the modulation symbol used for perception, and Represent the index of subcarrier and OFDM symbol respectively; Indicates the subcarrier spacing; Indicates the duration of each OFDM symbol; represents the rectangular function; j represents the imaginary unit, .

4. The communication-aware integrated waveform design method based on reference signal according to claim 3 is characterized in that: The user end is the receiving end of the communication data. The received time domain signal is converted to the frequency domain after Fourier transform. The modulation symbol received by the user end It can be expressed as: (2)； in, represents the sent communication and the perceived modulation symbols, and , r and u represent the indices of subcarrier and OFDM symbol respectively; represents the channel gain of the transmission from the base station to the user; represents zero mean and has a variance of cyclically symmetric complex Gaussian noise.

5. The communication-awareness integrated waveform design method based on reference signal according to claim 4 is characterized in that: In the channel estimation process, the channel error It is mainly caused by imperfect estimation filters and noise, and can be expressed as: (3)； in, Indicates channel information of a reference signal; represents the filter error, and is an ideal filter; represents a non-ideal filter; express In the reference signal density The sampling noise under has zero mean and variance The cyclically symmetric complex Gaussian noise is ; Channel Error After two-dimensional discrete Fourier transform and Parseval theorem, the mean square error of channel estimation is It can be expressed as: (4)； in, Indicates the original channel The sampling of power spectral density, that is ; exist The two-dimensional Fourier transform in the range is ; The linear interpolator can be expressed as: ； By using the second-order Taylor approximation, the mean square error of the channel estimation is It can be approximately expressed as: (5)； in, and denote the z-order moment of the Doppler spectrum and power delay distribution, respectively.

6. The method for designing a communication-aware integrated waveform based on a reference signal according to claim 5, characterized in that: In a CPI, the mean square error of the channel estimation based on Equation 5 is , the communication rate of the ISAC system can be expressed as: (6)； in, is the average gain of the lth path, is the variance of the frequency domain estimator.

7. The method for designing a communication-aware integrated waveform based on a reference signal according to claim 6, characterized in that: The user end also acts as a sensing target and reflects the ISAC signal back to the base station. The base station receives the signal and samples it through matched filtering, retaining only the reference signal, and transforms it into the frequency domain through Fourier transform. The received modulation symbol It can be expressed as: (7)； Where A is the channel gain; R and v represent the relative distance and speed between the sensing target and the base station; represents the carrier center frequency; c represents the speed of light; represents zero mean and has a variance of Circularly symmetric complex Gaussian noise; in As the reference signal is a known symbol, it can be obtained from Remove it and keep only the estimated vector The relevant information can be expressed as: (8)； in, is the noise term; By estimating the vector The inverse of the Fisher information matrix is ​​used to obtain the perceived CRB matrix. First, the Fisher information matrix is ​​given for: (9)； Among them, each element in the matrix can be expressed as: (10)； in, and ; express The conditional probability density function of ; By calculation The inverse matrix of can obtain the CRB of distance and speed respectively: (11)； (12)； in, as well as ; Through and The weighted sum is used as the perceptual performance in the ISAC system and can be expressed as: (13)； in, is a weighting factor that balances the importance of distance and speed estimation under different requirements.

8. The communication-awareness integrated waveform design method based on reference signals according to claim 7 is characterized in that: To design the interval of the reference signal, the weighted sum of the perceived CRBs is minimized under the condition of ensuring the minimum threshold of the user communication rate, that is, to solve the following optimization problem: (14)； in, Indicates the minimum communication rate threshold; In a CPI, usually and , then the weighted sum of the perceived CRB can be approximated as: (15)； The interval parameter of the reference signal in the constraint is relaxed from an integer variable to a continuous variable. Through relaxation and approximation, the optimization problem of formula (14) can be transformed into: (16)； The transformed optimization problem is a convex optimization problem, which can be directly solved using the CVX tool to obtain the reference signal interval, that is, to obtain a compromise between communication and perception performance.

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