Common signal assisted RSMA ISAC system sensing method

Abstract

The invention provides a public signal assisted RSMA ISAC system sensing method. The method comprises the following steps: transmitting a sensing signal, a public signal and a private signal through a base station; obtaining a covariance matrix of the transmitted signal by accumulating the transmitted beam forming vectors of the common signal and the sensing signal; constructing a cross-correlation function of any two sensing target directions; traversing the cross-correlation function to obtain a sensing target angle corresponding to the peak value of the reflected signal; calculating the distance from the sensing target to the base station according to the time delay of back-and-forth propagation of the target transmitting signal; calculating the position of the sensing target relative to the base station according to the sensing target angle and distance; according to the invention, the common signal is incorporated into the sensing signal to improve the sensing performance, so that the sensing capability of the RSMA ISAC system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of synaesthesia integration, and in particular to a common signal-assisted RSMA ISAC system perception method. Background Art

[0002] Integrated Communication and Perception (ISAC), one of the core technologies of sixth-generation (6G) networks, simultaneously implements communication and perception functions by sharing spectrum, hardware, and signal processing, thus providing multidimensional capabilities for the future intelligent society. Rate-Splitting Multiple Access (RSMA) systems employ a hybrid approach combining information segmentation and non-orthogonal transmission to enhance multi-user communication performance. The transmitter (TX) decomposes the signal into public and private components. At the receiver (RX), the public message is first decoded, followed by the private message using Successive Interference Cancellation (SIC), cleverly mitigating and exploiting interference. RSMA systems employ more flexible resource allocation schemes and signal decoding methods, further improving spectrum efficiency, system capacity, interference tolerance, and communication fairness. However, perception accuracy needs to be improved. Summary of the Invention

[0003] In response to the needs of the prior art, the present invention provides a common signal-assisted RSMA ISAC system perception method, aiming to enhance the perception accuracy of the system.

[0004] A common signal-assisted RSMA ISAC system perception method includes the following steps:

[0005] Step 1: Decompose the communication signal and the perception signal to be transmitted through rate division multiple access and reorganize them into perception signal, public signal and private signal;

[0006] Step 2: Transmitting sensing signals, public signals, and private signals through the base station;

[0007] Step 3: Obtain the covariance matrix of the transmitted signal by accumulating the transmit beamforming vectors of the common signal and the perception signal ;

[0008] Step 4: Any two perceived target directions and The cross-correlation function is defined as , , among which, among which, represents the receiving array steering vector associated with the k-th sensing target, and belongs to k;

[0009] Step 5: Traverse the cross-correlation function to obtain the perceived target angle corresponding to the peak of the reflected signal ; and confirm the transmission signal corresponding to the reflected signal, which is recorded as the target transmission signal;

[0010] Step 6: Calculate the distance from the target to the base station based on the round-trip propagation time delay τ of the target transmission signal ;in, is the estimated sequence of time delay τ { } perform weighted averaging, where c is the speed of light;

[0011] Step 7: Based on the perceived target angle and distance Calculate the position of the sensing target relative to the base station.

[0012] Further: the covariance matrix of the transmitted signal , represents the transmit beamforming vector of the common signal, represents the transmit beamforming vector of the sensing signal.

[0013] Further: The phase relationship is represented by the steering vector , is the direction when receiving the kth target signal, and They represent the antenna spacing and the wavelength of the incident information on the antenna respectively.

[0014] Further: The base station transmission form is expressed as , then, the perception signal for , public signal for , private signal for ;in, represents the power allocation parameter of the i-th user, represents the base station transmission power, w i represents the beamforming vector, Represents the signal assigned to The weight of 、 、 、 are power allocation parameters corresponding to the transmitted signals one by one.

[0015] Further: ;in, is the fading parameter The associated coefficient of variation.

[0016] The beneficial effects of the present invention are as follows: the common signal is incorporated into the perception signal to improve the perception performance, and the target direction is estimated through the covariance, cross-correlation function and spatial spectrum function, the angle range is traversed, and the distance of the target is estimated according to the time delay of the peak of the reflected signal, so as to calculate the target position and improve the perception capability of the RSMA ISAC system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flow chart of the present invention;

[0018] Figure 2 This is a schematic diagram of the synaesthesia integration network in the present invention;

[0019] Figure 3 The signal processing process of the rate division multiple access synaesthesia integrated system of the present invention;

[0020] Figure 4 The relationship between the probability of detection (PoD) and the probability of false alarm (PoFA) is described;

[0021] Figure 5 The variation of the detection probability (PoD) of the base station with the signal-to-noise ratio (SNR) is shown. DETAILED DESCRIPTION

[0022] The present invention will be described in detail below with reference to the accompanying drawings. The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention. The directional terms such as left, center, right, top, and bottom in the embodiments of the present invention are merely relative concepts or are based on the normal use state of the product, and should not be considered as restrictive.

[0023] A common signal-assisted RSMA ISAC system perception method, such as Figure 1 、 Figure 2 and Figure 3 As shown, the following steps are included:

[0024] Step 1: Decompose the communication signal and the perception signal to be transmitted through rate division multiple access and reorganize them into perception signal, public signal and private signal;

[0025] Step 2: The base station transmits the sensing signal, public signal and private signal; the base station transmission form is expressed as , then, the perception signal for , public signal for , private signal for ;in, represents the power allocation parameter of the i-th user, represents the base station transmission power, w i represents the beamforming vector, Represents the signal assigned to The weight of 、 、 、 are the power allocation parameters corresponding to the transmitted signals one by one;

[0026] Step 3: Obtain the covariance matrix of the transmitted signal by accumulating the transmit beamforming vectors of the common signal and the perception signal ; Covariance matrix of the transmitted signal , represents the transmit beamforming vector of the common signal, Representation matrix The conjugate transpose of represents the transmit beamforming vector of the sensing signal, Representation matrix The conjugate transpose of

[0027] Step 4: Any two perceived target directions and The cross-correlation function is defined as , ,in, represents the receiving array steering vector associated with the kth sensing target (T1~Tk), and Belongs to K, Representation matrix The conjugate transpose of ; wherein, the reflected signals are received by several antennas on the base station, and an angle function is constructed to estimate the direction of the perceived target through the phase relationship between the reflected signals received by different antennas, wherein the peak value of the reflected signal corresponds to the target direction of the reflected signal; the phase relationship is represented by the steering vector , is the direction when receiving the kth target signal, and Represent the antenna spacing and the wavelength of the antenna incident information respectively;

[0028] Step 5: Traverse the cross-correlation function to obtain the perceived target angle corresponding to the peak of the reflected signal ; and confirm the transmission signal corresponding to the reflected signal, recorded as the target transmission signal; wherein the cross-correlation function is measured by the steering vector The degree of match with the received signal: Only when the steering vector aligns with the incident direction of the received signal can the steering vector maximize signal energy extraction, thereby achieving a peak in the cross-correlation function output. The mathematical uniqueness of the extreme value of the inner product of the steering vector theoretically guarantees that the cross-correlation function has a unique maximum value in the target direction. Therefore, the peak position directly corresponds to the target direction of the reflected signal.

[0029] Step 6: Calculate the distance from the target to the base station based on the round-trip propagation time delay τ of the target transmission signal ;in, is the estimated sequence of time delay τ { } to perform weighted average, ;in, is the fading parameter The relevant deviation coefficient, the fading parameter is the parameter related to the intensity and phase changes of the signal caused by environmental factors during the propagation process, and c is the speed of light;

[0030] Step 7: Based on the perceived target angle and distance Calculate the position of the sensing target relative to the base station.

[0031] The core metric for detecting signal system performance is the probability of detection (PoD), which is the probability that a base station successfully detects the presence of a target. In contrast, the probability of false alarm (PoFA) refers to the probability that a base station incorrectly declares the presence of a target when the target is actually not within the sensing range. Specifically, both PoFA and PoD can be mathematically modeled as a binary detection problem, with H0 representing the null hypothesis of "target not present" and H1 representing the alternative hypothesis of "target present."

[0032] The null hypothesis H0 and the alternative hypothesis H1 in the rate-division multiple access synaesthesia integrated system can be expressed as: ,

[0033] As can be seen from the formula, the signal power received by the RSMA ISAC system at the base station is a non-central chi-square distributed random variable with 3 degrees of freedom (DoFs) under the assumption H0 (target does not exist) and 5 DoFs under the assumption H1 (target exists); therefore, the false alarm probability of the RSMA ISAC system for target t is and detection probability It can be expressed as

[0034] Where ξ represents the detection threshold, Q (·, ·) represents the Marcum-Q function; represents the Gaussian additive white noise at the base station, middle, 、 、 , what do they mean respectively? Describes the response matrix of K targets, is the attenuation of the echo signal of the kth sensing target, is the direction when receiving the kth target signal, and are the receive and transmit array steering vectors associated with the kth target, and They are the Marcum-Q function with 3 degrees of freedom and the Marcum-Q function with 5 degrees of freedom, respectively. The degrees of freedom are specific parameters of the Marcum-Q function;

[0035] Therefore, detection probability is a key indicator for measuring perception performance. It indicates the probability that the system correctly detects the target signal and directly reflects the perception system's ability to identify the target signal. A higher detection probability means that the system can more accurately capture the target signal in a complex environment, effectively reducing missed detections and false detections, and thus reflecting higher perception performance. Figure 4 As shown in Figure 2, the perception performance of the base station is characterized. The area under the curve (AUC) is positively correlated with the perception performance. The larger the AUC value, the stronger the target detection capability. It can be seen that the perception performance of the RSMA ISAC system assisted by the public signal is better than that of the NOMA ISAC system. Figure 5 As shown in Figure 3, under the same signal-to-noise ratio, the detection probability of the common signal-assisted RSMA ISAC system is greater than that of the NOMA ISAC system. Therefore, the common signal-assisted RSMA ISAC system exhibits excellent detection performance through the synergistic combination of common signals and perception signals.

[0036] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A common signal-assisted RSMA ISAC system perception method, characterized by: The following steps are involved: Step 1: Decompose the communication signal and the perception signal to be transmitted through rate division multiple access and reorganize them into perception signal, public signal and private signal; Step 2: Transmitting sensing signals, public signals, and private signals through the base station; Step 3: Obtain the covariance matrix of the transmitted signal by accumulating the transmit beamforming vectors of the common signal and the perception signal ; Step 4: Any two perceived target directions and The cross-correlation function is defined as , ,in, represents the receiving array steering vector associated with the k-th sensing target, and belongs to k; Step 5: Traverse the cross-correlation function to obtain the perceived target angle corresponding to the peak of the reflected signal ; and confirm the transmission signal corresponding to the reflected signal, which is recorded as the target transmission signal; Step 6: Calculate the distance from the target to the base station based on the round-trip propagation time delay τ of the target transmission signal ;in, is the estimated sequence of time delay τ { } perform weighted averaging, where c is the speed of light; Step 7: Perceive the target angle and distance Calculate the position of the sensing target relative to the base station.

2. The common signal-assisted RSMA ISAC system perception method according to claim 1, characterized in that: Covariance matrix of the transmitted signal , represents the transmit beamforming vector of the common signal, represents the transmit beamforming vector of the sensing signal.

3. The common signal-assisted RSMA ISAC system perception method according to claim 1, characterized in that: , is the direction when receiving the kth target signal, and They represent the antenna spacing and the wavelength of the incident information on the antenna respectively.

4. The common signal-assisted RSMA ISAC system perception method according to claim 1, characterized in that: The base station transmission form is expressed as , then, the perception signal for , public signal for , private signal for ;in, represents the power allocation parameter of the i-th user, represents the base station transmission power, w i represents the beamforming vector, Represents the signal assigned to The weight of 、 、 、 are power allocation parameters corresponding to the transmitted signals one by one.

5. The common signal-assisted RSMA ISAC system perception method according to claim 1, characterized in that: ;in, is the fading parameter The associated coefficient of variation.

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