A Communication and Sensing Integration Method and Device Based on Partial Non-Orthogonal Multiple Access

Abstract

The present invention relates to the field of communication technologies, and particularly to a communication and sensing integration method and apparatus based on partial non-orthogonal multiple access. The method includes: constructing a communication and sensing integration multiplexing framework based on Semi-NOMA, that is, communication and sensing signals are multiplexed only in part of the frequency bands by using the NOMA method, while frequency multiplexing is still achieved in an orthogonal manner in the remaining frequency bands; introducing the performance index of radar estimation rate, and constructing a system optimization objective function for balancing the communication rate and the radar estimation rate by combining the communication rates of system users; introducing the performance index of communication outage probability, which can effectively guarantee the basic communication service quality of communication users while realizing communication and sensing integration.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and particularly to a communication and sensing integration method and apparatus based on partial non-orthogonal multiple access. Background Art

[0002] Non-orthogonal multiple access (NOMA) technology is a way of multiplexing the information flows of multiple users with different powers on the same time-frequency resource for information transmission. Its basic idea is to adopt a non-orthogonal transmission method at the sending end to actively introduce interference information, and at the receiving end, the information flows of different users are correctly separated through successive interference cancellation (SIC) technology, which can significantly improve the spectrum efficiency and save frequency resources.

[0003] In a wireless communication system, the total wireless resources are severely limited. Most of the existing resource allocation mechanisms rely on the allocation of orthogonal resources, such as frequency division multiple access, time division multiple access, and beam allocation. The advantages of these resource allocation methods are less interference and simple management. However, since each user can only transmit in a specific frequency, time, or beam, the resource utilization rate is low and cannot meet the high-demand scenarios such as high-bandwidth, low-latency, or large-scale connection communication.

[0004] When facing higher communication requirements, such as a communication system with ultra-high bandwidth, low latency, or large-scale device connection, the traditional orthogonal resource allocation method can no longer fully meet the requirements. At this time, the NOMA-assisted ISAC system becomes an important direction. Pure NOMA allocation can significantly improve the spectrum utilization rate. However, since the communication and sensing modules share the same time-frequency resource, the interference in the system is large, which will have a negative impact on the communication quality and user experience.

[0005] In the prior art, Documents 1-3 ([Q. Zhang et al., “Time-division ISAC enabled connected automated vehicles cooperation algorithm design and performance evaluation,” IEEE J. Sel. Areas Commun., vol. 40, no. 7, pp. 2206–2218, July 2022], [C. Shi et al., “Power minimization-based robust OFDM radar waveform design for radar and communication systems in coexistence,” IEEE Trans. Signal Process., vol. 66, no. 5, pp. 1316–1330, Mar 2017], [X. Chen et al., “Code-division OFDM joint communication and sensing system for 6G machine-type communication,” IEEE Internet Things J., vol. 8, no. 15, pp. 12 093–12105, Aug 2021.]) have studied the communication and sensing integration mechanism based on orthogonal resource reuse / orthogonal multiple access in three dimensions of time domain, frequency domain and code domain. Specifically, the wireless resources are divided into mutually orthogonal resource blocks in the time domain, frequency domain or code domain to support communication and sensing tasks respectively, and the base station or user terminal uses the non-interfering and mutually orthogonal wireless resource blocks to implement communication and sensing functions. Although this method has a relatively low implementation complexity, its spectral efficiency is low. Document 4 [X. Mu, Z. Wang, and Y. Liu, “NOMA for integrating sensing and communications toward 6G: A multiple access perspective,” IEEE Wireless Communications, vol. 31, no. 3, pp. 316–323, 2024.] proposes a communication and sensing integration mechanism based on pure NOMA. Among them, the user communicates with the base station by sending an uplink signal, and the base station sends a downlink sensing signal and realizes sensing by receiving the target echo signal.To improve the spectrum utilization efficiency, the user uplink communication signal and the base station downlink sensing signal multiplex the same frequency band in the way of NOMA.

[0006] In the above communication and sensing integration mechanism based on orthogonal multiple access / orthogonal resource multiplexing, although it is easy to implement, the system spectrum efficiency is not high; while in the communication and sensing integration mechanism based on non-orthogonal multiple access / non-orthogonal resource multiplexing, the interference between communication and sensing is strong, which easily leads to the decline of the communication effective capacity and sensing accuracy. All in all, the existing methods cannot achieve an effective trade-off between effectively guaranteeing the system spectrum efficiency and the communication and sensing performance. Summary of the Invention

[0007] To solve the technical problem that the existing technology cannot achieve an effective trade-off between effectively guaranteeing the system spectrum efficiency and the communication and sensing performance, the embodiments of the present invention provide a communication and sensing integration method and device based on partial non-orthogonal multiple access. The technical solutions are as follows:

[0008] On the one hand, a communication and sensing integration method based on partial non-orthogonal multiple access is provided, and the method includes:

[0009] S1. Construct an ISAC system based on Semi-NOMA; the ISAC system includes at least one physical resource block PRB in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area;

[0010] S2. Based on the ISAC system, construct a signal model of the ISAC system based on Semi-NOMA;

[0011] S3. Take the radar estimation rate as the sensing performance index, and based on the signal model of the ISAC system based on Semi-NOMA, establish a system user communication rate function and a radar estimation rate function of the sensing target distance;

[0012] S4. Calculate the Cramér-Rao lower bound of the target distance; calculate the communication outage probability of the ISAC area;

[0013] S5. Based on the Cramér-Rao lower bound of the target distance and the communication outage probability of the ISAC area, construct a system total rate objective function for the trade-off between the communication rate and the radar estimation rate, optimize the objective function and obtain the optimal solution to complete the communication and sensing integration based on partial non-orthogonal multiple access.

[0014] Optionally, the ISAC system based on Semi-NOMA includes:

[0015] Communication users, radar targets, and a dual-functional ISAC base station;

[0016] Among them, the communication user maintains uplink communication with the ISAC base station. The ISAC base station sends a sensing signal to the coverage area, which reaches the ISAC base station end after being reflected by the sensing target. On the ISAC area transmission frequency band, the communication signal on the uplink shares part of the frequency band resources with the sensing echo and is multiplexed in the NOMA manner. On other frequency bands, the uplink communication signal and the sensing echo are multiplexed orthogonally and are transmitted in the pure communication area and the pure sensing area respectively, forming an uplink ISAC system based on Semi-NOMA.

[0017] Optionally, in S2, based on the ISAC system, a signal model of the ISAC system based on Semi-NOMA is constructed, including:

[0018] Since the ISAC system shares part of the frequency band resources in the ISAC area, the time-domain expression of the signal at the transmitting end is shown in the following formula:

[0019]

[0020] Among them, is the sensing signal sent by the ISAC base station, is the uplink communication signal sent by the user, represents the th symbol of the th subcarrier in the th symbol period, is the communication symbol on the th subcarrier of the th symbol period; M is the number of OFDMs. The sensing symbols are mapped to the PRB at intervals of time and frequency as the unit. The number of subcarriers carrying the sensing signal is and and represent the number of subcarriers in the pure sensing area, the ISAC area, and the pure communication area respectively. is the rectangular pulse function; represents the subcarrier spacing; j represents the imaginary unit; T s represents the OFDM symbol duration, which is composed of the data duration T d and the cyclic prefix time;

[0021] The signal reaching the ISAC base station end is a mixture of the sensing echo signal reflected by the sensing target and the uplink communication signal. Then the mixed signal is shown in the following formula:

[0022]

[0023] Among them, , They are the sensing echo and the communication signal arriving at the ISAC base station respectively. is the transmission power of the communication user. is the large-scale fading coefficient of the communication user's uplink communication link. They are the transmission power of the sensing signal and the large-scale fading coefficient of the base station respectively. represents the small-scale fading experienced by the communication signal. They represent the small-scale fading experienced by transmitting and receiving the sensing signal respectively. , denoted as , where represents the sensing signal with a round-trip time delay . is the noise signal, and the noise power is .

[0024] Optionally, in S3, taking the radar estimation rate as the sensing performance index, based on the signal model of the ISAC system with Semi-NOMA, establishing the radar estimation rate function for the target distance, and obtaining the information amount of the target distance, including:

[0025] Obtaining the sensing echo in the previous sensing period; where the previous sensing period is multiple pulse repetition intervals T before the current period m ;

[0026] By observing the sensing echo in the previous sensing period through the radar, modeling the fluctuation process of the target parameters, and calculating the radar estimation rate; introducing the radar estimation rate sensing performance index to measure the sensing mutual information.

[0027] Based on the signal model of the ISAC system with Semi-NOMA, establishing the system user communication rate function and the radar estimation rate function for the sensed target distance ; represents the signal-to-interference ratio in the pure communication area. represents the signal-to-interference ratio in the ISAC area.

[0028] Optionally, modeling the fluctuation process of the target parameters and calculating the radar estimation rate, including:

[0029] Modeling the fluctuation process of the target parameters, and the modeling process follows the Nakagami-m distribution.

[0030] The radar estimation rate is as shown in the following formula:

[0031]

[0032] where denotes the pulse repetition interval, is the pulse duration, is the duty cycle, and the variance of the target parameter fluctuation process based on the Nakagami - m distribution is , denotes the expected power; the Cramer - Rao lower bound CRLB of the target distance R is .

[0033] Optionally, in S4, calculating the Cramer - Rao lower bound of the target distance includes:

[0034] The sensed echo signal uses a two - dimensional fast Fourier algorithm to perform inverse Fourier transform on the sensed signal of the frequency axis and Fourier transform on the sensed signal of the time axis to obtain the time delay and Doppler frequency shift information of the signal. Through , the estimated distance of the target is obtained, where c is the speed of light. The Cramer - Rao lower bound of the target distance R is shown by the following formula:

[0035] ;

[0036] where, denotes the square of the data duration; denotes the square of the speed of light.

[0037] Optionally, in S4, calculating the communication outage probability in the ISAC region includes:

[0038] According to the following formula, the communication outage probability in the ISAC region:

[0039] ;

[0040] where, Pr represents the probability symbol; denotes the signal - to - interference - plus - noise ratio threshold.

[0041] Optionally, based on the target distance estimation and the communication outage probability in the ISAC region, constructing the system total rate objective function for the trade - off between the communication rate and the radar estimation rate, optimizing the objective function and obtaining the optimal solution includes:

[0042] Establish the system total rate for the trade - off between the communication rate and the radar estimation rate , where the system optimization problem is the system total rate for the trade - off between the communication rate and the radar estimation rate ; where, the system total rate for the trade - off between the communication rate and the radar estimation rate consists of: the communication rate in the pure communication region is , the communication rate in the ISAC region is , and the radar estimation rate of the target distance is ;

[0043] The system optimization problem is transformed into the following optimization problem:

[0044]

[0045]

[0046]

[0047]

[0048]

[0049]

[0050] Among them, α represents the frequency band occupancy ratio of the pure communication area; ɛ represents the frequency band occupancy ratio of the ISAC area; η represents the frequency band occupancy ratio of the pure sensing area; α + ɛ + η ≤ 1 represents that the total frequency band occupancy ratio of the entire system is less than or equal to 1;

[0051] The sequence convex optimization algorithm SCP is used to solve the optimization problem.

[0052] On the other hand, a communication and sensing integration device based on partial non-orthogonal multiple access is provided. This device is applied to the communication and sensing integration method based on partial non-orthogonal multiple access. The device includes:

[0053] The ISAC system construction module is used to construct an ISAC system based on Semi-NOMA; the ISAC system includes at least one physical resource block PRB in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area;

[0054] The system signal model construction module is used to construct an ISAC system signal model based on Semi-NOMA based on the ISAC system;

[0055] The radar estimation rate module is used to use the radar estimation rate as a sensing performance index, and based on the ISAC system signal model of Semi-NOMA, establish a system user communication rate function and a radar estimation rate function of the sensing target distance;

[0056] The parameter calculation module is used to calculate the Cramer-Rao lower bound of the target distance; calculate the communication outage probability of the ISAC area;

[0057] The optimization and solution module is used to construct a system total rate objective function that balances the communication rate and the radar estimation rate based on the Cramer-Rao lower bound of the target distance and the communication outage probability of the ISAC area, optimize the objective function, and obtain the optimal solution to complete the communication and sensing integration based on partial non-orthogonal multiple access.

[0058] On the other hand, a communication and sensing integrated device based on partial non-orthogonal multiple access is provided. The communication and sensing integrated device based on partial non-orthogonal multiple access includes: a processor; a memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, any one of the methods in the above-mentioned communication and sensing integration method based on partial non-orthogonal multiple access is implemented.

[0059] On the other hand, a computer-readable storage medium is provided. At least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement any one of the methods in the above-mentioned communication and sensing integration method based on partial non-orthogonal multiple access.

[0060] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0061] In the embodiments of the present invention, a partial non-orthogonal multiple access (Semi-NOMA) mechanism is innovatively introduced, that is, the communication and sensing functions only achieve frequency reuse in a NOMA manner in some frequency bands, while still achieving frequency reuse in an orthogonal manner in other frequency bands. This ISAC mechanism based on Semi-NOMA can flexibly configure the time, frequency, and energy resources of the communication and sensing functions, thereby effectively taking into account the quality of communication and sensing services of users and the spectrum efficiency of the system. Description of the Drawings

[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0063] Figure 1 It is a flowchart of the communication and sensing integration method based on partial non-orthogonal multiple access provided by the embodiments of the present invention;

[0064] Figure 2 It is a schematic diagram of the frequency resource allocation of pure NOMA and semi-NOMA provided by the embodiments of the present invention;

[0065] Figure 3 It is a schematic diagram of the ISAC system based on Semi-NOMA provided by the embodiments of the present invention;

[0066] Figure 4 It is a schematic diagram of the PRB resource allocation of the ISAC system based on Semi-NOMA provided by the embodiments of the present invention;

[0067] Figure 5Block diagram of a communication and sensing integration device based on partial non - orthogonal multiple access provided by an embodiment of the present invention;

[0068] Figure 6 Schematic structural diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0069] The following describes the technical solutions in the present invention with reference to the accompanying drawings.

[0070] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two can be selected.

[0071] In the embodiments of the present invention, sometimes a subscript such as W1 may be written in a non - subscript form such as W1. When the difference is not emphasized, the meaning to be expressed is the same.

[0072] To make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will be described in detail with reference to the accompanying drawings and specific embodiments.

[0073] The embodiments of the present invention provide a communication and sensing integration method based on partial non - orthogonal multiple access. This method can be implemented by a communication and sensing integration device based on partial non - orthogonal multiple access. The communication and sensing integration device based on partial non - orthogonal multiple access can be a terminal or a server. As Figure 1 shown in the flowchart of the communication and sensing integration method based on partial non - orthogonal multiple access, as Figure 1 shown, the communication and sensing integration method based on partial non - orthogonal multiple access proposed by the present invention. The processing flow of this method can include the following steps:

[0074] S1. Construct an ISAC system based on Semi - NOMA; the ISAC system includes at least one physical resource block PRB in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area.

[0075] In a feasible implementation manner, a communication and sensing integration mechanism based on a pure NOMA method proposed in Document 4. Among them, the user communicates with the base station by sending an uplink signal, and the base station sends a downlink sensing signal and realizes sensing by receiving the target echo signal. To improve the spectrum utilization efficiency, the user's uplink communication signal and the base station's downlink sensing signal multiplex the same frequency band in a NOMA manner, as Figure 2as shown in (a); while this invention innovatively introduces the Semi-NOMA (Semi-Non-Orthogonal Multiple Access) mechanism, such as Figure 2 in (b), that is, the communication and sensing functions only achieve frequency reuse in a NOMA manner in some frequency bands, while in other frequency bands, frequency reuse is still achieved in an orthogonal manner. This ISAC mechanism based on Semi-NOMA can flexibly configure the time, frequency, and energy resources of the communication and sensing functions, thus effectively taking into account the quality of communication and sensing services of users and the system spectrum efficiency.

[0076] In a feasible implementation manner, the ISAC system based on Semi-NOMA includes:

[0077] such as Figure 3 the ISAC system based on Semi-NOMA shown: The system includes communication users, radar targets (such as vehicles, drones, etc.), and a dual-functional ISAC base station;

[0078] Among them, while the communication user maintains uplink communication with the base station, the base station sends a sensing signal to the coverage area, and after being reflected by the sensing target, it reaches the base station side. At this time, on the system transmission frequency band, the uplink communication signal and the sensing echo share part of the frequency band resources and are multiplexed in a NOMA manner, that is, the ISAC area. On other frequency bands, the uplink communication signal and the sensing echo are multiplexed in an orthogonal manner and are transmitted in the pure communication area and the pure sensing area respectively, forming a schematic diagram of the uplink ISAC system based on Semi-NOMA.

[0079] In a feasible implementation manner, Figure 4 Taking a PRB as an example, an embodiment of time-frequency resource multiplexing of communication and sensing signals based on Semi-NOMA is given. As shown in the figure, the PRB is divided into three parts: a pure communication area, an ISAC area, and a pure sensing area.

[0080] In a feasible implementation manner, the present invention realizes integrated communication and sensing based on Semi-NOMA, that is, the communication and sensing signals only achieve multiplexing in a NOMA manner in some frequency bands, while in the remaining frequency bands, frequency reuse is still achieved in an orthogonal manner; specifically, it involves the time-frequency interval of the comb-shaped spectrum of the sensing signal, the time, frequency, and energy resource allocation of communication and sensing functions, etc.

[0081] S2. Based on the ISAC system, construct a signal model of the ISAC system based on Semi-NOMA;

[0082] In a feasible implementation manner, based on the above-mentioned PRB design of the 5G NR frame, within the coverage radius d of the ISAC base station, the base station sends a sensing signal to the sensing target and receives the sensing echo. The communication user establishes an uplink communication with the ISAC base station, and shares part of the frequency band resources in the ISAC area. Therefore, the time-domain expression of the signal at the transmitting end is shown in the following formula:

[0083]

[0084] where is the sensing signal sent by the ISAC base station, is the uplink communication signal sent by the user, represents the sensing symbol on the th sub-carrier in the th symbol, is the communication symbol on the nth sub-carrier in the mth symbol; M is the number of OFDMs. The sensing symbols are mapped to the PRB at intervals of time and frequency as the unit. The number of sub-carriers carrying the sensing signal is , the number of sensing symbols is , and the sub-carriers carrying the communication signal are , where , and represent the number of sub-carriers in the pure sensing area, the ISAC area, and the pure communication area respectively. is the rectangular pulse function; the OFDM symbol duration is composed of the cyclic prefix time and the data duration , that is . is the sub-carrier spacing; j represents the imaginary unit; T s represents the OFDM symbol duration, which is composed of the data duration T d and the cyclic prefix time.

[0085] The signal experiences small-scale fading (Nakagami-m (m>1)) and large-scale fading during the transmission process. Therefore, the signal arriving at the ISAC base station is a mixture of the sensing echo signal reflected by the sensing target and the uplink communication signal. Then the mixed signal is shown in the following formula:

[0086]

[0087] where , are the sensing echo and the communication signal arriving at the ISAC base station respectively, is the transmitting power of the communication user, is the large-scale fading coefficient of the uplink communication link of the communication user; are the transmission power of the sensing signal and the large-scale fading coefficient of the base station, respectively, represents the small-scale fading experienced by the communication signal, respectively represent the small-scale fading experienced by the transmitted sensing signal and the received sensing signal; , denoted as , where represents the sensing signal with a round-trip time delay , is the noise signal, and the noise power is .

[0088] S3. Take the radar estimation rate as the sensing performance index, and based on the signal model of the ISAC system with Semi-NOMA, establish the system user communication rate function and the radar estimation rate function of the sensing target distance;

[0089] In a feasible implementation, in S3, take the radar estimation rate as the sensing performance index, and based on the signal model of the ISAC system with Semi-NOMA, establish the radar estimation rate function for the target distance, and obtain the information amount of the target distance, including:

[0090] Obtain the sensing echo in the previous sensing period; wherein, the previous sensing period is multiple pulse repetition intervals T before the current period m ;

[0091] Through the observation of the radar based on the sensing echo in the previous sensing period, model the fluctuation process of the target parameters, and calculate the radar estimation rate; introduce the radar estimation rate sensing performance index to measure the sensing mutual information;

[0092] Based on the signal model of the ISAC system with Semi-NOMA, establish the system user communication rate function and the radar estimation rate function of the sensing target distance ; represents the signal-to-interference ratio in the pure communication area; represents the signal-to-interference ratio in the ISAC area.

[0093] In a feasible implementation, introduce the radar estimation rate as a sensing performance index to measure the sensing mutual information. Similar to the communication information rate, it describes the measure of the information carried by the sensing echo reaching the base station after being reflected by the sensing target about the target parameters (time delay, Doppler frequency shift, etc.) within a period of time.

[0094] In a feasible implementation, model the fluctuation process of the target parameters and calculate the radar estimation rate, including:

[0095] Model the fluctuation process of the target parameter, and the modeling process follows the Nakagami-m distribution;

[0096] Radar estimation rate As shown in the following formula:

[0097]

[0098] Wherein, represents the pulse repetition interval, is the pulse duration, is the duty cycle, and the variance of the target parameter fluctuation process based on the Nakagami-m distribution is , represents the expected power; the Cramér-Rao lower bound CRLB of the target distance R is .

[0099] In a feasible implementation manner, the present invention introduces a performance index of radar estimation rate, which is similar to the communication information rate, and describes the measure of the information carried by the sensing echo reaching the base station about the target parameters (time delay, Doppler frequency shift, etc.) after the sensing signal is reflected by the sensing target within a period of time. From the perspective of information theory, it realizes the unified measure of communication and radar sensing performance. By combining the communication rate of system users, a system optimization objective function for the trade-off between communication rate and radar estimation rate is constructed.

[0100] S4. Calculate the Cramér-Rao lower bound of the target distance; calculate the communication outage probability in the ISAC region;

[0101] In a feasible implementation manner, in S4, calculating the Cramér-Rao lower bound of the target distance includes:

[0102] The sensing echo signal uses a two-dimensional fast Fourier algorithm to perform inverse Fourier transform on the sensing signal on the frequency axis and Fourier transform on the sensing signal on the time axis to obtain the time delay and Doppler frequency shift information of the signal. Through , the estimated distance of the target is obtained, where c is the speed of light. The Cramér-Rao lower bound of the target distance R is calculated as shown in the following formula:

[0103] ;

[0104] Wherein, represents the square of the data duration; represents the square of the speed of light.

[0105] In a feasible implementation manner, in S4, calculating the communication outage probability in the ISAC region includes:

[0106] The received signal at the base station side is the superposition of the sensing echo and the uplink communication signal, and the base station side SIC receiver is required to perform detection and decision to separate the sensing signal and the communication signal. Since only the communication signal contains information bits, and the received echo signal is sent by the base station side and undergoes long-distance transmission, the intensity of the echo signal is often lower than that of the communication signal. Therefore, the SIC decoding order is fixed. First, the communication signal is judged, and the communication signal is removed from the superimposed signal, and then the sensing echo signal can be obtained to estimate the sensing-related parameters of the radar target. Therefore, calculating the signal-to-interference ratio of the communication signal at the base station side includes the signal-to-interference ratio in the pure communication area and the signal-to-interference ratio in the ISAC area :

[0107]

[0108] Detect and judge the sensing echo signal from the superimposed signal. Assuming that SIC is perfectly executed and the communication signal is completely removed, the signal-to-interference-plus-noise ratio of the obtained sensing echo signal is:

[0109]

[0110] Considering that the signal-to-interference-plus-noise ratio in the ISAC area is affected by the sensing signal and usually has a higher requirement for power, the communication outage probability in the ISAC area is:

[0111] ;

[0112] where Pr represents the probability symbol; represents the signal-to-interference ratio threshold.

[0113] In a feasible implementation manner, introducing the performance index of communication outage probability can effectively guarantee the basic communication service quality of communication users while realizing communication and sensing integration, especially in the ISAC area frequency band where communication and sensing functions multiplex spectrum resources through the NOMA method.

[0114] S5. Based on the target distance estimation and the communication outage probability in the ISAC area, construct the system total rate objective function that balances the communication rate and the radar estimation rate, optimize the objective function and obtain the optimal solution to complete communication and sensing integration based on partial non-orthogonal multiple access.

[0115] In a feasible implementation manner, based on the target distance estimation and the communication outage probability in the ISAC area, construct the system total rate objective function that balances the communication rate and the radar estimation rate, optimize the objective function and obtain the optimal solution, including:

[0116] Establish the system total rate that balances the communication rate and the radar estimation rate , as follows:

[0117]

[0118] Among them, the total system rate of the trade-off between the communication rate and the radar estimation rate consists of: the communication rate in the pure communication area is , the communication rate in the ISAC area is , and the radar estimation rate of the target distance is ;

[0119] Explore the frequency band resource allocation of the three functional areas in the PRB and the communication power allocation of the system to achieve the maximization of the total system rate problem;

[0120] There are discrete variables in the optimization variables of this objective function. For the convenience of calculation, consider the continuousization of discrete variables into , , similarly, the number of subcarriers for sensing is continuously transformed into , and it satisfies , so the system optimization problem is transformed into the following optimization problem:

[0121]

[0122]

[0123]

[0124]

[0125]

[0126]

[0127] Among them, α represents the frequency band occupancy ratio of the pure communication area; ɛ represents the frequency band occupancy ratio of the ISAC area; η represents the frequency band occupancy ratio of the pure sensing area; α + ɛ + η ≤ 1 represents that the total frequency band occupancy ratio of the entire system is less than or equal to 1;

[0128] The above optimization problem means that under the constraints of communication and sensing power, the communication outage probability of the average distance, and the CRLB of the target distance, by traversing the signals in the PRB at the time-frequency interval , , solve for the frequency band occupancy ratios of the three functional areas and the communication power that can maximize the objective function (the part after max).

[0129] This problem is a non-convex problem, and the Sequential Convex Programming (SCP) algorithm is used to solve the above problem. An initial point is selected to perform first-order Taylor linearization on the objective function and constraint conditions, construct a sub-problem of convex optimization, and use existing convex optimization algorithms to solve this sub-problem. The selection of the initial point directly affects the optimal solution.

[0130] In the embodiments of the present invention, an integrated communication and sensing mechanism based on Semi-NOMA is innovatively proposed. With the goal of maximizing the sum rate of system communication and sensing, the time, frequency, and energy resources of the 5G NR uplink subframe are flexibly scheduled. Specifically, the frequency band within the system uplink subframe is divided into three parts: a pure communication area, a pure sensing area, and an ISAC area. Among them, the base station sends a downlink sensing signal and realizes target sensing by receiving the echo signal from the target. The frequency band of this sensing signal covers the pure sensing area and the ISAC area; users send uplink signals to achieve communication with the base station, and the uplink communication frequency band of users in the system covers the pure communication area and the ISAC area; the sensing signal and the communication signal are multiplexed only in the ISAC area through the NOMA method, while in the pure communication area and the pure sensing area, the spectrum resources are still multiplexed in an orthogonal manner, so it is called Semi-NOMA. The integrated communication and sensing mechanism based on Semi-NOMA proposed in this invention patent maximizes the sum rate of system communication and sensing by optimizing the number of subcarriers in the pure communication area, sensing area, and ISAC area, the time-frequency resource interval of the comb-shaped spectrum of the sensing signal, and the power of the communication and sensing signals, while ensuring the outage probability of communication users and the Cramer-Rao bound of target sensing.

[0131] Figure 5 It is a block diagram of an integrated communication and sensing device 300 based on partial non-orthogonal multiple access shown according to an exemplary embodiment. This device 300 is used for the integrated communication and sensing method based on partial non-orthogonal multiple access. Refer to Figure 5 , this device includes an ISAC system construction module 310, a system signal model construction module 320, a radar estimation rate module 330, a parameter calculation module 340, and an optimization solution module 350. Among them:

[0132] The ISAC system construction module 310 is used to construct an ISAC system based on Semi-NOMA; the ISAC system includes at least one physical resource block (PRB) in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area;

[0133] The system signal model construction module 320 is used to construct an ISAC system signal model based on Semi-NOMA based on the ISAC system;

[0134] The radar estimation rate module 330 is used to take the radar estimation rate as a sensing performance index, and based on the signal model of the ISAC system with Semi-NOMA, establish a system user communication rate function and a radar estimation rate function for the perceived target distance;

[0135] The parameter calculation module 340 is used to calculate the Cramer-Rao lower bound of the target distance; calculate the communication outage probability in the ISAC area;

[0136] The optimization and solution module 350 is used to construct a total system rate objective function that balances the communication rate and the radar estimation rate based on the Cramer-Rao lower bound of the target distance and the communication outage probability in the ISAC area, optimize the objective function, and obtain the optimal solution to complete communication and sensing integration based on partial non-orthogonal multiple access.

[0137] Optionally, the ISAC system based on Semi-NOMA includes:

[0138] Communication users, radar targets, and a dual-functional ISAC base station;

[0139] Among them, the communication users maintain uplink communication with the ISAC base station. The ISAC base station sends sensing signals to the coverage area, and after being reflected by the sensing target, they reach the ISAC base station side. On the transmission frequency band of the ISAC area, the communication signals of the uplink share part of the frequency band resources with the sensing echo and are multiplexed in the NOMA manner. On other frequency bands, the uplink communication signals and the sensing echo are multiplexed orthogonally and are transmitted in the pure communication area and the pure sensing area respectively, forming an uplink ISAC system based on Semi-NOMA.

[0140] Optionally, based on the ISAC system, construct a signal model of the ISAC system based on Semi-NOMA, including:

[0141] Since the ISAC system shares part of the frequency band resources in the ISAC area, the time-domain expression of the signal at the transmitter is as shown in the following formula:

[0142]

[0143] Among them, is the sensing signal sent by the ISAC base station, is the uplink communication signal sent by the user, represents the sensing symbol on the th subcarrier in the th symbol period, is the communication symbol on the nth subcarrier in the mth symbol period; M is the number of OFDMs, and the sensing symbols are mapped to the PRB at intervals of in time and frequency. The number of subcarriers carrying the sensing signal is , the number of sensed symbols is , the subcarriers carrying communication signals are , where , and respectively represent the number of subcarriers in the pure sensing region, the ISAC region, and the pure communication region. is a rectangular pulse function; represents the subcarrier spacing; j represents the imaginary unit; T s represents the OFDM symbol duration, which is composed of the data duration T d and the cyclic prefix time;

[0144] The signal arriving at the ISAC base station is a superposition of the sensed echo signal reflected by the sensing target and the uplink communication signal. Then the superimposed signal is shown by the following formula:

[0145]

[0146] where, , are the sensed echo and the communication signal arriving at the ISAC base station respectively, is the transmission power of the communication user, is the large-scale fading coefficient of the communication user's uplink communication link; are the transmission power and the large-scale fading coefficient of the base station's sensing signal respectively, represents the small-scale fading experienced by the communication signal, respectively represent the small-scale fading experienced by transmitting the sensing signal and receiving the sensing signal; , denoted as where represents the sensing signal with a round-trip time delay , is the noise signal, and the noise power is .

[0147] Optionally, taking the radar estimation rate as the sensing performance index, based on the signal model of the ISAC system with Semi-NOMA, establish a radar estimation rate function for the target distance, and obtain the information amount of the target distance, including:

[0148] Obtain the sensed echo in the previous sensing period; where, the previous sensing period is multiple pulse repetition intervals T m before the current period;

[0149] Through the observation of the sensed echo in the previous sensing period by the radar, model the fluctuation process of the target parameters, and calculate the radar estimation rate; introduce the radar estimation rate sensing performance index to measure the sensing mutual information;

[0150] Based on the signal model of the ISAC system with Semi-NOMA, establish the communication rate function of the system users and the radar estimation rate function of the perceived target distance ; Denote the signal-to-interference ratio in the pure communication area; Denote the signal-to-interference ratio in the ISAC area.

[0151] Optionally, model the fluctuation process of the target parameters and calculate the radar estimation rate, including:

[0152] Model the fluctuation process of the target parameters, and the modeling process follows the Nakagami-m distribution;

[0153] The radar estimation rate is as shown in the following formula:

[0154]

[0155] where, Denote the pulse repetition interval, is the pulse duration, is the duty cycle, and the variance of the target parameter fluctuation process based on the Nakagami-m distribution is , Denote the expected power; the Cramér-Rao lower bound CRLB of the target distance R is .

[0156] Optionally, calculate the Cramér-Rao lower bound of the target distance, including:

[0157] The perceived echo signal uses the two-dimensional fast Fourier algorithm to perform the inverse Fourier transform on the perceived signal on the frequency axis and the Fourier transform on the perceived signal on the time axis to obtain the time delay and Doppler frequency shift information of the signal. Through , obtain the estimated distance of the target, where c is the speed of light, and calculate the Cramér-Rao lower bound of the target distance R as shown in the following formula:

[0158] ;

[0159] where, Denote the square of the data duration; Denote the square of the speed of light.

[0160] Optionally, calculate the communication outage probability in the ISAC area, including:

[0161] According to the following formula for the communication outage probability in the ISAC area:

[0162] ;

[0163] Among them, Pr represents the probability symbol; represents the signal-to-interference-plus-noise ratio threshold.

[0164] Optionally, based on the target distance estimation and the communication interruption probability in the ISAC region, construct the total system rate objective function for the trade-off between the communication rate and the radar estimation rate, optimize the objective function, and obtain the optimal solution, including:

[0165] Establish the total system rate for the trade-off between the communication rate and the radar estimation rate , where the system optimization problem is the total system rate for the trade-off between the communication rate and the radar estimation rate ; among them, the total system rate for the trade-off between the communication rate and the radar estimation rate consists of: the communication rate in the pure communication region is , the communication rate in the ISAC region is , the radar estimation rate of the target distance is ;

[0166] The system optimization problem is transformed into the following optimization problem:

[0167]

[0168]

[0169]

[0170]

[0171]

[0172]

[0173] Among them, α represents the frequency band occupancy ratio of the pure communication region; ɛ represents the frequency band occupancy ratio of the ISAC region; η represents the frequency band occupancy ratio of the pure sensing region; α + ɛ + η ≤ 1 represents that the total frequency band occupancy ratio of the entire system is less than or equal to 1;

[0174] Use the sequential convex programming algorithm SCP to solve the optimization problem.

[0175] In the embodiments of the present invention, an integrated communication and sensing mechanism based on Semi-NOMA is innovatively proposed. With the goal of maximizing the sum rate of system communication and sensing, the time, frequency, and energy resources of the 5G NR uplink subframe are flexibly scheduled. Specifically, the frequency band within the system uplink subframe is divided into three parts: a pure communication area, a pure sensing area, and an ISAC area. Among them, the base station sends a downlink sensing signal and realizes target sensing by receiving the echo signal from the target. The frequency band of this sensing signal covers the pure sensing area and the ISAC area; the user sends an uplink signal to realize communication with the base station, and the uplink communication frequency band of the users in the system covers the pure communication area and the ISAC area; the sensing signal and the communication signal are multiplexed only in the ISAC area by means of NOMA, while in the pure communication area and the pure sensing area, the spectrum resources are still multiplexed in an orthogonal manner, so it is called Semi-NOMA. The integrated communication and sensing mechanism based on Semi-NOMA proposed in this invention patent maximizes the sum rate of system communication and sensing by optimizing the number of subcarriers in the pure communication area, the sensing area, and the ISAC area, the time-frequency resource interval of the comb-shaped spectrum of the sensing signal, and the power of the communication and sensing signals, while ensuring the outage probability of communication users and the Cramer-Rao bound of target sensing.

[0176] Figure 6 FIG. is a schematic structural diagram of an integrated communication and sensing device based on partial non-orthogonal multiple access provided by an embodiment of the present invention, as Figure 6 shown, the integrated communication and sensing device based on partial non-orthogonal multiple access may include the above Figure 5 shown integrated communication and sensing device based on partial non-orthogonal multiple access. Optionally, the integrated communication and sensing device 410 based on partial non-orthogonal multiple access may include a first processor 2001.

[0177] Optionally, the integrated communication and sensing device 410 based on partial non-orthogonal multiple access may further include a memory 2002 and a transceiver 2003.

[0178] Among them, the first processor 2001, the memory 2002, and the transceiver 2003, such as may be connected through a communication bus.

[0179] Next, in combination with Figure 6 each component of the integrated communication and sensing device 410 based on partial non-orthogonal multiple access will be specifically introduced:

[0180] Among them, the first processor 2001 is the control center of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access, which can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or can be an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention. For example: one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0181] Optionally, the first processor 2001 can execute various functions of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0182] In a specific implementation, as an embodiment, the first processor 2001 may include one or more CPUs, such as Figure 6 the CPU0 and CPU1 shown in

[0183] In a specific implementation, as an embodiment, the communication and sensing integrated device 410 based on partial non-orthogonal multiple access may also include multiple processors, such as Figure 6 the first processor 2001 and the second processor 2004 shown in. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0184] Among them, the memory 2002 is used to store software programs for executing the solution of the present invention and is controlled by the first processor 2001 for execution. The specific implementation method can refer to the above method embodiments and will not be elaborated here.

[0185] Optionally, the memory 2002 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or may also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 2002 may be integrated with the first processor 2001 or may exist independently and be coupled to the first processor 2001 through an interface circuit (not shown in Figure 6 of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access). The embodiments of the present invention do not make specific limitations on this.

[0186] The transceiver 2003 is used to communicate with a network device or communicate with a terminal device.

[0187] Optionally, the transceiver 2003 may include a receiver and a transmitter (not separately shown in Figure 6 ). Among them, the receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0188] Optionally, the transceiver 2003 may be integrated with the first processor 2001 or may exist independently and be coupled to the first processor 2001 through an interface circuit (not shown in Figure 6 of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access). The embodiments of the present invention do not make specific limitations on this.

[0189] It should be noted that Figure 6 the structure of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access shown in does not constitute a limitation on the router. The actual knowledge structure recognition device may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0190] In addition, the technical effects of the communication and sensing integrated device 410 based on partial non-orthogonal multiple access may refer to the technical effects of the communication and sensing integrated method based on partial non-orthogonal multiple access described in the above method embodiments, and will not be elaborated here.

[0191] It should be understood that the first processor 2001 in the embodiments of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0192] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchlink dynamic random access memory (SLDRAM), and direct rambus random access memory (DR RAM).

[0193] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable sensors. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more sets of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0194] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood by referring to the context.

[0195] It should be understood that in various embodiments of the present invention, the sequence numbers of the above processes do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0196] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professionals can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0197] The unit described as a separation component may or may not be physically separated. The component shown as a unit may or may not be a physical unit, that is, it may be located in one place or may be distributed over multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0198] In addition, in each embodiment of the present invention, each functional unit may be integrated in a processing unit, may be physically present separately for each unit, or two or more units may be integrated in one unit.

[0199] If the said function 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 technical solution of the present invention, in essence, or the part that contributes to the prior art or part of the technical solution can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present invention.

[0200] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the said claims.

Claims

1. A communication and sensing integration method based on partial non-orthogonal multiple access, characterized in that The method includes: S1. Construct an ISAC system based on Semi-NOMA; the ISAC system includes at least one physical resource block (PRB) in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area; S2. Based on the ISAC system, construct a signal model of the ISAC system based on Semi-NOMA; Since the ISAC system shares some of the frequency band resources in the ISAC area, the time-domain expression of the signal at the transmitter is as shown in the following formula: ； Among them, is the sensing signal sent by the ISAC base station, is the uplink communication signal sent by the user, represents the th symbol period, and is the sensing symbol on the th subcarrier; m is the communication symbol on the n th subcarrier of the M th symbol period; is the number of OFDMs. The sensing symbols are mapped to the PRB at time and frequency intervals of . The number of subcarriers carrying the sensing signal is , the number of sensing symbols is , and the subcarriers carrying the communication signal are , and respectively represent the number of subcarriers in the pure sensing area, the ISAC area, and the pure communication area; is the rectangular pulse function; ∆ f represents the subcarrier spacing; j represents the imaginary unit; T s represents the OFDM symbol duration, which is composed of the data duration T d and the cyclic prefix time; The signal arriving at the ISAC base station terminal is a superposition of the sensing echo signal reflected by the sensing target and the uplink communication signal. Then the superimposed signal is shown in the following formula: ； Among them, and are the sensing echo and the communication signal arriving at the ISAC base station respectively, is the transmission power of the communication user, is the large-scale fading coefficient of the uplink communication link of the communication user; are the transmission power and the large-scale fading coefficient of the sensing signal of the base station respectively, represents the small-scale fading experienced by the communication signal, represent the small-scale fading experienced by transmitting and receiving the sensing signal respectively; , denoted as , where represents the sensing signal with a round-trip time delay , is the noise signal, and the noise power is ; S3. Take the radar estimation rate as a sensing performance index, and based on the signal model of the ISAC system based on Semi-NOMA, establish a system user communication rate function and a radar estimation rate function of the sensing target distance; S4. Calculate the Cramér-Rao lower bound of the target distance; calculate the communication outage probability in the ISAC area; S5. Based on the Cramér-Rao lower bound of the target distance and the communication outage probability in the ISAC area, construct a system total rate objective function for trade-off between communication rate and radar estimation rate, optimize the objective function and obtain the optimal solution, and complete communication and sensing integration based on partial non-orthogonal multiple access.

2. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 1, wherein The ISAC system based on Semi-NOMA includes: Communication users, radar targets, and a dual-functional ISAC base station; Among them, the communication users maintain uplink communication with the ISAC base station, and the ISAC base station sends sensing signals to the coverage area, which reach the ISAC base station end after being reflected by the sensing target; on the transmission frequency band of the ISAC area, the communication signals of the uplink share part of the frequency band resources with the sensing echo in a NOMA manner; on other frequency bands, the uplink communication signals and the sensing echo are multiplexed in an orthogonal manner and are transmitted in the pure communication area and the pure sensing area respectively, forming an uplink ISAC system based on Semi-NOMA.

3. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 2, wherein In S3, taking the radar estimation rate as a sensing performance index, and based on the signal model of the ISAC system based on Semi-NOMA, establishing a system user communication rate function and a radar estimation rate function of the sensing target distance includes: Obtain the sensing echo in the previous sensing period; wherein, the previous sensing period is a plurality of pulse repetition intervals T before the current period m ; By observing the sensing echo in the previous sensing period by the radar, model the fluctuation process of the target parameters, and calculate the radar estimation rate; introduce the radar estimation rate sensing performance index to measure the sensing mutual information; Based on the signal model of the Semi-NOMA-based ISAC system, establish the system user communication rate function and the radar estimation rate function of the perceived target distance ; Denote the signal-to-interference ratio in the pure communication area; Denote the signal-to-interference ratio in the ISAC area, Denote the pulse repetition interval, is the pulse duration, is the duty cycle, and the Cramer-Rao lower bound CRLB of the target distance R is ; the variance of the target parameter fluctuation process based on the Nakagami-m distribution is .

4. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 3, characterized in that The modeling of the fluctuation process of the target parameters and the calculation of the radar estimation rate include: Model the fluctuation process of the target parameters, and the modeling process follows the Nakagami-m distribution; Radar estimated rate As shown in the following formula: ； Among them, represents the desired power.

5. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 4, wherein In S4, calculating the Cramér-Rao lower bound of the target distance includes: Calculate the Cramer-Rao lower bound R as shown in the following formula: ； Among them, represents the square of the data duration; represents the square of the speed of light.

6. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 5, wherein In S4, calculating the communication outage probability in the ISAC area includes: Calculate the communication interruption probability of the ISAC area according to the following formula : ； Among them, Pr represents the probability symbol; represents the signal-to-interference ratio threshold.

7. The integrated communication and sensing method based on partial non-orthogonal multiple access according to claim 6, characterized in that Based on the target distance estimation and the communication outage probability in the ISAC area, constructing a system total rate objective function for trade-off between communication rate and radar estimation rate, optimizing the objective function and obtaining the optimal solution includes: Formulate a system optimization problem, where the system optimization problem is the total system rate that balances the communication rate and the radar estimation rate ; Among them, the total system rate that balances the communication rate and the radar estimation rate consists of: the communication rate in the pure communication area is , the communication rate in the ISAC area is , and the radar estimation rate of the target distance is ; Transform the system optimization problem into the following optimization problem: ； Where, α represents the frequency band ratio of the pure communication area; N represents the total number of subcarriers in the system; ɛ represents the frequency band ratio of the ISAC area; η represents the frequency band ratio of the pure sensing area; α + ɛ + η ≤ 1 represents that the total frequency band ratio of the entire system is less than or equal to 1; Use the sequential convex programming algorithm (SCP) to solve the optimization problem.

8. A communication and sensing integrated device based on partial non-orthogonal multiple access, the communication and sensing integrated device based on partial non-orthogonal multiple access is used to implement the communication and sensing integrated method based on partial non-orthogonal multiple access according to any one of claims 1-7, characterized in that, The device includes: An ISAC system construction module for constructing an ISAC system based on Semi-NOMA; the ISAC system includes at least one physical resource block (PRB) in a 5G frame; the ISAC system is divided into a pure communication area, an ISAC area, and a pure sensing area; A system signal model construction module for constructing an ISAC system signal model based on the ISAC system; A radar estimation rate module for taking the radar estimation rate as a sensing performance index and establishing a system user communication rate function and a radar estimation rate function of the sensing target distance based on the ISAC system signal model based on Semi-NOMA; A parameter calculation module for calculating the Cramer-Rao lower bound of the target distance; calculating the communication outage probability of the ISAC area; An optimization and solution module for constructing a system total rate objective function that balances the communication rate and the radar estimation rate based on the Cramer-Rao lower bound of the target distance and the communication outage probability of the ISAC area, optimizing the objective function, and obtaining the optimal solution to complete communication and sensing integration based on partial non-orthogonal multiple access.

9. A communication and sensing integrated device based on partial non-orthogonal multiple access, characterized in that, The communication and sensing integration device based on partial non-orthogonal multiple access includes: A processor; A memory, on which computer-readable instructions are stored, and when the computer-readable instructions are executed by the processor, the method described in any one of claims 1 to 7 is implemented.

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