ISAC method, device and network based on orthogonal multi-carrier FSCM signal

Abstract

The present invention discloses an ISAC method, device, and network based on orthogonal multi-carrier FSCM signals. For any ISAC device in the ISAC network, the following steps are implemented: (1) frequency-shift chirp modulation is performed on the communication symbols of a data stream to generate and transmit an orthogonal multi-carrier FSCM signal; (2) echo signals reflected from each target in a multi-target scenario are received and processed to achieve real-time detection of the target; the echo signals reflected from the targets are orthogonal multi-carrier FSCM signals; and (3) orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network are received, and the received signals are demultiplexed and demodulated to achieve communication between the ISAC devices. The present invention achieves the integration of communication and perception without sacrificing communication and perception performance.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to an ISAC method, device and network based on orthogonal multi-carrier FSCM signals. Background Art

[0002] With the explosive growth of wireless communication devices, the global communications industry is facing an increasingly urgent need for wireless spectrum. This makes the discovery of additional spectrum resources even more urgent. To alleviate this conflict, in future B5G and 6G scenarios, communication systems will need to explore the feasibility of coexisting with other electronic devices in the same frequency band.

[0003] Traditional multiplexing methods separate communication and radar sensing, such as (1) radar-centric design and (2) communication-centric design. Radar-centric design is to implement communication functions in radar systems, generally by embedding information into FMCW radar signals. However, the communication symbol rate of FMCW signals corresponds to its chirp rate, which is usually an order of magnitude lower than the symbol rate achieved by dedicated communication systems with the same bandwidth. Many communication-centric designs use IEEE 802.11 signals, and OFDM signals that comply with IEEE 802.11 are also used to implement sensing functions in vehicle networks. However, the randomness of communication data will lead to a high peak-to-average power ratio and random autocorrelation characteristics, thereby reducing the system's sensing accuracy. Exploring communication and sensing in higher frequency bands, such as millimeter wave bands, will make the hardware equipment expensive, and its sensing distance will decrease due to the influence of wavelength. Summary of the Invention

[0004] The present invention provides an ISAC method, device and network based on orthogonal multi-carrier FSCM signals, which realizes the integration of communication and perception without losing communication and perception performance.

[0005] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0006] An ISAC method based on orthogonal multi-carrier FSCM signals, for any ISAC device in an ISAC network:

[0007] (1) Perform frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmit it;

[0008] (2) Receive and process the echo signals reflected by each target in a multi-target scenario to achieve real-time detection of the target; the echo signals reflected by the target are orthogonal multi-carrier FSCM signals.

[0009] (3) Receive orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplex and demodulate the received signals to achieve communication between ISAC devices.

[0010] Furthermore, when frequency-shift chirp modulation is performed on the communication symbols, different spreading factors are used for modulation in each channel of the transmitter.

[0011] Furthermore, the method of using different spreading factors for modulation is:

[0012] Add a carrier frequency offset f to the subcarrier FSCM signal offset , f offset It is given by the following definition:

[0013]

[0014] Where B is the bandwidth, SF is the spreading factor, that is, the number of modulation bits per communication symbol, t s is the cycle time of each communication symbol, S is the communication symbol;

[0015] Folding time As the dividing line, a communication symbol S is represented as two parts, which can be expressed as follows:

[0016]

[0017] Where k is the slope of frequency change; x T (t) is the FSCM signal at the transmitting end obtained by embedding the communication symbol S;

[0018] The discrete form of the FSCM signal obtained by sampling the embedded communication symbol S is shown as follows:

[0019]

[0020] Where n is the sampling sequence, f s is the sampling frequency, using single bandwidth; N1={0,...,n fold -1}, N2={n fold ,...,2 SF -1}, and n fold =t fold ·f s .

[0021] Furthermore, each ISAC device transmits and receives signals using a MIMO antenna, and each ISAC device is provided with multiple transmitting antennas and multiple receiving antennas, each antenna corresponding to multiple different spreading factors.

[0022] Furthermore, the echo signal processing includes demultiplexing the received orthogonal multi-carrier FSCM signal. The demultiplexing of the received orthogonal multi-carrier FSCM signal specifically includes:

[0023] Assume that the received orthogonal multi-carrier FSCM signal is expressed as:

[0024] Y=A(θ)x+v

[0025] where v is a variable with covariance R z Additive zero-mean temporal white noise;

[0026] First, the corresponding reference signal g is generated in each channel of the receiver according to the corresponding spreading factor SF i (t), the reference signal is in the form of carrier frequency offset f offset FSCM signal is 0;

[0027] Then, in each channel, the received orthogonal multi-carrier FSCM signal Y(t) is compared with the reference signal g i (t) and extract the FSCM subcarrier x corresponding to each channel. R，i (t):

[0028]

[0029] The covariance matrix of the extracted received signal subcarrier is expressed as:

[0030]

[0031] Where R Y，i and R N Represent the covariance matrices of the received signal and the noise signal respectively;

[0032] Assuming that the noise signal is continuous, the covariance matrix R is decomposed to obtain M eigenvalues ​​of R in descending order, and R is transformed into the following formula:

[0033]

[0034] Λ in the formula S is the K eigenvalues ​​η1, η2, η3, ..., η of the matrix R. K The diagonal matrix composed of S is the signal subspace composed of K corresponding eigenvectors; n is a diagonal matrix consisting of MK eigenvalues, Y n It is a subspace composed of eigenvectors corresponding to MK eigenvalues.

[0035] Furthermore, the echo signal processing further includes performing target detection using the obtained subcarriers, specifically:

[0036] First, select the FSCM subcarrier with the largest spreading factor SF corresponding to the channel and set the sampling frequency f s Set to be equal to the bandwidth B corresponding to the spreading factor SF of the channel, that is, f s =B, then the sampled FSCM discrete signal is:

[0037]

[0038] in, is the maximum spreading factor.SF max FSCM discrete signal within the channel, φ represents the received FSCM discrete signal Y i [n] is the phase, k is the slope of frequency change, n is the sampling sequence, N1 = {0, ..., n fold -1}, N2={n fold ,...,2 SF -1}, N is the union of N1 and N2, and n fold =t fold ·f s , f s is the sampling frequency, t fold is the folding time represented by the FSCM symbol in two parts, B is the bandwidth, S is the communication symbol in the data stream; n′ is the delay of the signal in discrete time;

[0039] Then, a standard chirp signal with the same slope is mixed with the FSCM subcarrier to obtain the intermediate frequency signal f IF (t):

[0040]

[0041] Where T[n] represents the standard chirp signal with slope k0, * represents the conjugate operation, and the intermediate frequency f IF =-k0n′; φ′ is the phase of the intermediate frequency signal obtained by mixing the received signal with the reference signal;

[0042] Finally, the CZT algorithm is used to calculate f IF (t) is processed to complete the estimation of the distance and speed of the target; and the arrival angle is estimated by using the MUSIC algorithm and the spectrum peak search method, which is expressed as:

[0043]

[0044] Among them, θ MUSICrepresents the estimated arrival angle, and A(θ) represents the transmit-receive matrix, which is the product of the transposed transmit steering matrix and the receive steering matrix.

[0045] Furthermore, the received signal is demultiplexed and demodulated. The demodulation is to demodulate the FSCM subcarriers in each channel separately. Specifically, based on the principle of coherent demodulation, a down-chirp signal with the same spreading factor value as the modulated signal is used as a reference signal for demodulation. The demodulation operation in the i-th channel is shown as follows:

[0046]

[0047] in, represents the discrete reference signal x ref，i The conjugate form of [n], the communication symbol S corresponds to the maximum value sequence number after the FFT operation.

[0048] An ISAC device based on orthogonal multi-carrier FSCM signals includes a transmitter and a receiver;

[0049] The transmitter performs frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmits it;

[0050] The receiver receives and processes the echo signals reflected by each target in a multi-target scene to achieve real-time detection of the target; wherein the echo signals reflected by the target are orthogonal multi-carrier FSCM signals,

[0051] The receiver also receives orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplexes and demodulates the received signals to achieve communication between ISAC devices.

[0052] Furthermore, the ISAC device is used to implement the ISAC method based on orthogonal multi-carrier FSCM signals described in any of the above technical solutions.

[0053] An ISAC network based on orthogonal multi-carrier FSCM signals comprises a plurality of ISAC devices based on orthogonal multi-carrier FSCM signals as described in any one of the above items.

[0054] Beneficial effects

[0055] The present invention proposes a new integrated communication and perception method, device and network, which realizes high-precision perception of environmental targets and communication between different devices without losing any performance of communication or perception.

[0056] (1) A low sampling rate method is proposed, that is, the sampling frequency is set to be equal to the bandwidth B corresponding to the SF of the channel, that is, f s=B, mathematically simplifying the FSCM signal into a standard chirp signal carrying the communication symbol S. This operation eliminates the false alarm problem that occurs when the FSCM signal is directly mixed and sensed, reduces computational complexity, and improves the system's perception accuracy.

[0057] (2) By applying fractional Fourier transform, the communication rate is greatly improved by constructing orthogonal multi-carrier FSCM signals while ensuring the sensing accuracy of the system.

[0058] (3) Combining MIMO technology and using orthogonal FSCM signals, the system reliability and ability to combat multipath fading are improved through fractional Fourier domain multiplexing without increasing the antenna radiation power, and the antenna pattern design of the system is made more flexible. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 Communication and perception integrated network;

[0060] Figure 2 The time domain and time-frequency domain of the FSCM signal after mixing it directly with the reference signal;

[0061] Figure 3 Comparison of target detection results before and after eliminating false alarm problems;

[0062] Figure 4 Time-frequency domain of orthogonal multi-carrier FSCM signals.

[0063] Figure 5 Orthogonal multi-carrier FSCM signal frame format;

[0064] Figure 6 Signal reception model of array antenna;

[0065] Figure 7 ISAC equipment orthogonal multi-carrier FSCM signal demultiplexing process;

[0066] Figure 8 ISAC equipment - target perception process;

[0067] Figure 9 Frequency shift chirp demodulation process in ISAC device II;

[0068] Figure 10 Perception results of orthogonal four-carrier FSCM signals;

[0069] Figure 11 Communication bit error rate of orthogonal four-carrier FSCM signal under different signal-to-noise ratio conditions; DETAILED DESCRIPTION

[0070] The following is a detailed description of an embodiment of the present invention. This embodiment is based on the technical solution of the present invention, provides a detailed implementation method and a specific operation process, and further explains the technical solution of the present invention.

[0071] Example 1

[0072] This embodiment provides an ISAC method based on orthogonal multi-carrier FSCM signals, which is applied to Figure 1 The integrated communication and perception network shown above has the following characteristics for any ISAC device in the ISAC network:

[0073] (1) Perform frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmit it;

[0074] (2) Receive and process the echo signals reflected by each target in a multi-target scenario to achieve real-time detection of the target; the echo signals reflected by the target are orthogonal multi-carrier FSCM signals.

[0075] (3) Receive orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplex and demodulate the received signals to achieve communication between ISAC devices.

[0076] Example 2

[0077] This embodiment provides an ISAC device based on orthogonal multi-carrier FSCM signals, including a transmitter and a receiver;

[0078] The transmitter performs frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmits it;

[0079] The receiver receives and processes the echo signals reflected by each target in a multi-target scene to achieve real-time detection of the target; wherein the echo signals reflected by the target are orthogonal multi-carrier FSCM signals,

[0080] The receiver also receives orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplexes and demodulates the received signals to achieve communication between ISAC devices.

[0081] Example 3

[0082] This embodiment provides an ISAC network based on orthogonal multi-carrier FSCM signals, including the ISAC device described in the above embodiment 2.

[0083] The ISAC device described in any of the above embodiments can be improved on existing communication equipment or radar equipment. The required carrier frequency is 915 MHz, the maximum bandwidth is 51.2 MHz, two transmitting antennas and two receiving antennas are required, the orthogonal multi-carrier FSCM signal has a limited scanning time of 20 μs, and the spreading factor of each channel can be {4, 5, 6, 7, 8, 9, 10, 11, 12}. Figure 1 The ISAC network scenario shown includes multiple objects and two ISAC devices. Each ISAC device can serve as a transmitter or a receiver, and can achieve dual functions of communication and perception.

[0084] In this experimental scenario, it is assumed that ISAC device 1 transmits orthogonal multi-carrier FSCM signals and processes the echo signals of targets in the scene to achieve real-time detection of targets. ISAC device 2 receives the orthogonal multi-carrier FSCM signals, demultiplexes and demodulates the signals, and realizes communication between ISAC devices. Specifically:

[0085] Step 1: Construct orthogonal multi-carrier MIMO-FSCM waveform and frame format

[0086] Frequency shift chirp modulation (FSCM) is a long-distance, low-power communication modulation technology based on chirp signals. This modulation method encodes the communication symbol S in a chirp signal with a constant slope (chirp rate) by frequency offset. In FSCM technology, the symbol S is embedded in the chirp waveform by adding a carrier frequency offset (f) to the waveform. offset , f offset It is given by the following definition:

[0087]

[0088] Folding time As the dividing line, a FSCM symbol can be expressed as two parts, as shown in the following formula:

[0089]

[0090] The bandwidth B is

[0091]

[0092] SF is the spreading factor, that is, the number of modulation bits per symbol, usually takes values ​​of {4, 5, 6, 7, 8, 9, 10, 11}. offset is the carrier frequency, k is the slope of the frequency change, and the discrete form of the FSCM signal is shown as follows:

[0093]

[0094] Where n is the sampling sequence, f s is the sampling frequency, N1={0,…,v fold -1},N2={n fold ,…,2 sF -1}, and n fold =t fold ·f s Compared to traditional sinusoidal modulation, FSCM signals, which combine spread spectrum and frequency hopping properties, not only inherit the excellent characteristics of chirp signals but also have better anti-interception performance. They can simultaneously meet the dual functional requirements of communication and perception, making them suitable as the foundational waveform for ISAC systems. However, the communication rate of this waveform corresponds only to its chirp rate, which is typically an order of magnitude lower than the symbol rate achieved by communication systems with the same bandwidth.

[0095] Due to the phase discontinuity of the FSCM signal, directly mixing the FSCM signal with the reference signal will produce high-frequency components, resulting in false alarms. Furthermore, the carrier frequency offset (CFO) of the FSCM waveform is determined by the communication symbols and is random. Therefore, since the frequency range of the interference is unknown, it is difficult to set appropriate filtering parameters. To address this issue, by establishing and analyzing the FSCM signal model, when using a complex baseband structure and a sampling frequency lower than the Nyquist frequency (Nyquist is typically 2x bandwidth, while this embodiment uses 1x bandwidth), the FSCM mathematical model can be simplified to a chirp, eliminating the interference caused by frequency discontinuity. Figure 2 In the time domain and time-frequency domain after the FSCM signal is directly mixed with the reference signal, it can be seen that the signal is mixed with high-frequency components for a period of time. Figure 3 Comparison of target detection results before and after eliminating false alarm problems.

[0096] However, while FSCM signals have good autocorrelation and spectral characteristics, their communication efficiency is relatively low. Therefore, the concept of OFDM multicarrier multiplexing can be introduced to improve system communication efficiency. However, multicarrier technology requires orthogonality of subcarriers, so the core issue of FSCM multicarrier is how to select a suitable orthogonal basis and construct orthogonal subcarriers. To address this issue, the key to FSCM orthogonal multicarrier communication is to ensure that subcarriers do not interfere with each other, so it is necessary to construct orthogonal FSCM subcarrier signals. The following first uses the fractional Fourier transform (FrFT) to prove the orthogonality of FSCM waveforms in the time-frequency domain. Then, an FSCM orthogonal basis is constructed to establish an orthogonal multicarrier FSCM signal group. Figure 4 It is the time-frequency domain image of the orthogonal multi-carrier FSCM signal.

[0097] The FrFT can be viewed as a rotation of a vector by any angle in the time-frequency domain. N different frequency-modulated chirp signals can be viewed as a chirp base signal rotated by N angles in the α-u plane. The h-order fractional Fourier transform (FrFT) of a signal x(t) is defined as follows:

[0098]

[0099] Among them F h It is the FrFT operator, the rotation angle of the signal in the time-frequency domain K h (t,u) is the transform kernel of FrFT, defined as:

[0100]

[0101] Fractional Fourier transform can analyze and process signals in the fractional Fourier transform domain between the time domain and the frequency domain, breaking through the limitations of traditional Fourier analysis.

[0102] The FSCM signals with different slopes are obtained by constructing the above fractional Fourier transform. Then, autocorrelation is performed on any two FSCM signals with different slopes. The results are as follows:

[0103]

[0104] Among them, ψ p (t) and ψ q (t) represents any two FSCM signals with different slopes, Representative signal ψ q (t), it can be seen that the FSCM signals with different slopes are orthogonal to each other in the time-frequency domain.

[0105] In the method proposed by the present invention, first, the ISAC device uses frequency-shift chirp modulation to generate FSCM orthogonal subcarrier groups in each channel of the transmitter. Since the spreading factors in each channel are different and the pulse time is 20us, according to the formula:

[0106]

[0107] Therefore, the slope k of the FSCM subcarriers generated by each channel is different and they are orthogonal to each other.

[0108] Then, in the transmitter, the subcarriers of each channel are superimposed by an adder and transmitted. Figure 5 The constructed orthogonal multi-carrier FSCM signal frame format in the time-frequency domain is described, which includes three parts: preamble, data packet header, and payload. The preamble includes three parts: variable preamble, synchronization word, and frequency synchronization.

[0109] Previous research has shown that MIMO technology can increase system design freedom and enable more flexible antenna pattern design, thereby better enabling target distance, speed, and angle estimation under low signal-to-noise ratio conditions. MIMO technology can also improve channel capacity limits, enhancing system communication rates and reliability. Furthermore, the MIMO radar model and the MIMO communication model share many similarities in mathematical expression. Therefore, to further enhance the perception and communication performance of the ISAC system, a preferred embodiment of the present invention utilizes MIMO antennas in current communication devices and radar sensor equipment to further enhance the dual-function performance of communication and perception. The method of using MIMO antennas to transmit and receive orthogonal multi-carrier FSCM signals is referred to as the MIMO-FSCM method.

[0110] In the MIMO-FSCM method, the data stream of each branch channel is modulated by FSCM and transmitted through the corresponding antenna. Two carriers are superimposed on each antenna and then transmitted through the MIMO antenna. The corresponding FSCM signal spreading factors on each antenna are: {3 / 4}, {5 / 6}, {7 / 8}, and {9 / 10}. This method can achieve integrated eight-carrier FSCM sensing communication on four antennas. Because the transmitted signals between the antennas are orthogonal, it does not significantly affect the dual-function performance.

[0111] Assume that each array element transmits a mutually orthogonal signal x as shown below:

[0112]

[0113] where x i (n), i∈{1, 2, ..., N t} is the signal in the i-th transmitting antenna, N t is the number of transmitting antennas, then the echo signal of the target at azimuth angle θ0 is:

[0114]

[0115] In the above formula, represents the Kronecher product, ξ=E s η represents the amplitude of the signal received by each array element after passing through the matched filter, η is the transmission loss of the signal, and v represents N t N r dimensional received noise vector, N r is the number of receiving antennas. T (θ0) and α R (θ0) are the transmit steering vector and receive steering vector of the MIMO radar, respectively. The specific form is:

[0116]

[0117]

[0118] in, and It represents the spatial phase difference between the transmitting array elements and the receiving array elements, λ is the wavelength, d T is the distance between transmitting antenna elements, d R is the receiving antenna element spacing, then N of the MIMO array t N r The equivalent steering matrix is:

[0119]

[0120] That is, the output of the transmit and receive beam of the MIMO-FSCM sensing communication integrated system is: y = A H x+v, (·) H Represents the conjugate transpose of a vector.

[0121] Step 2: The receivers of ISAC device 1 and device 2 demultiplex the orthogonal multi-carrier MIMO-FSCM signal

[0122] The signal receiving model of the array antenna is as follows Figure 6 As shown in Figure 1, a uniform linear array consisting of four antenna elements is used to receive the signal.

[0123] After the ISAC device receives the orthogonal multi-carrier FSCM signal in the channel on the MIMO antenna, the signal is in the following form:

[0124] Y=A(θ)x+v

[0125] where v is a variable with covariance R z The additive zero-mean time white noise is then generated, and the FSCM orthogonal multi-carrier signal is demultiplexed using the FrFT method. The specific operation is as follows: first, the corresponding reference signal g is generated in each channel of the receiver according to the corresponding SF. i (t), the reference signal is in the form of carrier frequency offset f offset The FSCM signal is 0 and has the same slope as the subcarrier. Then, in each channel, the received orthogonal multi-carrier FSCM signal Y(t) is compared with the reference signal g i Conjugate multiplication of (t):

[0126]

[0127] The FSCM subcarrier corresponding to the channel SF can be extracted. The process is as follows Figure 7 shown.

[0128] The following covariance matrix is ​​used to evaluate the extracted subcarrier signal to prove the anti-interference performance of the received signal: the covariance matrix of the extracted received signal subcarrier can be expressed as:

[0129]

[0130] and R N Represent the covariance matrices of the received subcarrier signal and the noise signal respectively. Assuming that the noise signal is continuous, the covariance matrix R is decomposed into its own eigenvalues ​​in descending order, and R can be transformed into the following formula:

[0131]

[0132] Λ in the above formula S is the K eigenvalues ​​η1, η2, η3, ..., η of the matrix R. K The diagonal matrix composed of S Is the signal subspace composed of K corresponding eigenvectors. n is a diagonal matrix consisting of MK eigenvalues, Y n is the subspace consisting of eigenvectors corresponding to MK eigenvalues.

[0133] Step 3: ISAC device 1 performs high-precision target estimation in the radar channel;

[0134] After extracting the subcarriers, the ISAC device selects the FSCM subcarrier with the largest SF corresponding to the channel. Do the perception processing. Since the FSCM signal has the problem of phase discontinuity, directly using the radar processing algorithm to mix the FSCM with the reference signal will cause false alarm problems. In order to solve this problem, this method reduces the sampling frequency f s Set to be equal to the bandwidth B corresponding to the SF of the channel, that is, f s =B, then the FSCM discrete signal can be simplified as follows:

[0135]

[0136] Therefore, the FSCM signal can be simplified into a standard chirp signal from a mathematical form, and carries the communication symbol S. This operation can eliminate the false alarm problem caused by direct mixing of the FSCM signal and improve the perception accuracy of the system. Then, a standard chirp signal with the same slope is mixed with the FSCM subcarrier to obtain the intermediate frequency signal f IF (t):

[0137]

[0138] Where T* [n] represents the slope of the conjugate of the standard chirp signal, with an intermediate frequency of f IF =-k0n′, n′ is the delay of the signal in discrete time. Finally, the CZT algorithm is used to calculate f IF (t) is processed (refer to "Comparison of Spectral Analysis of ZFFT and Chirp-Z Transform Band Selection" published by Ding Kang et al.), and the range and velocity of the target can be estimated with high precision. The arrival angle is estimated by using the MUSIC algorithm (refer to "Performance of Modified MUSIC Algorithm for DOA Estimation of Correlated Signal Sources" published by He Zishu et al.) and the peak search method (i.e., finding the peak in the spectrum after CZT refinement, which is the frequency value corresponding to the target). Its expression is:

[0139]

[0140] Figure 8 Flowchart for processing target echo for device one.

[0141] This method uses a low sampling rate to reduce system computation time, improve operational speed, and eliminate false alarms caused by FSCM phase discontinuities. Furthermore, the high bandwidth of the FSCM signal with the largest SF ensures high-precision target distance perception.

[0142] Step 4: ISAC device 2 performs FSCM subcarrier demodulation in the communication channel to restore the communication information.

[0143] Step 4 and step 3 are carried out in two different devices respectively, and the order of the steps is not specific.

[0144] After the subcarrier demultiplexing operation in step 2, the ISAC device 2 obtains the FSCM subcarrier corresponding to the SF in each channel. Then, the FSCM is demodulated in each channel. The demodulation process is based on the concept of coherent demodulation, using the down-chirp signal with the same SF value as the modulation signal as the reference signal for demodulation, and its (CF0) is 0. The specific process is as follows: Figure 9 The demodulation operation in channel i is as follows:

[0145]

[0146] in represents the discrete reference signal x ref The conjugate form of [n], the communication symbol S corresponds to the maximum sequence number after the FFT operation, the specific process is as follows Figure 9 Compared with non-coherent demodulation, this algorithm has lower computational complexity.

[0147] The present invention proposes an ISAC method, device and network based on orthogonal multi-carrier FSCM signals, which solves the current spectrum congestion problem, not only realizes remote sensing, but also adopts a multi-carrier communication scheme to ensure communication reliability.

[0148] The Zedboard software radio is used for simulation experiments, and the parameters are shown in Table 1:

[0149] Table 1 Simulation experiment parameters

[0150]

[0151] The present invention adopts a low sampling rate method to eliminate the problem of false alarm when the FSCM signal is directly mixed, and reduces the calculation complexity. Figure 10 This is the perception result of the orthogonal four-carrier FSCM signal. When the highest spreading factor is 10, the perception error can be as low as 10cm.

[0152] The present invention applies fractional Fourier transform and proposes an orthogonal multi-carrier MIMO-FSCM signal group, which greatly improves the communication rate and has high communication reliability. When the spreading factor is {3 / 4, 5 / 6, 7 / 8, 9 / 10}, the communication rate of the orthogonal multi-carrier MIMO-FSCM signal group can reach 89.2Mbps, and as the spreading factor increases, the communication rate will increase exponentially. When the signal-to-noise ratio is 0dB, the bit error rate can reach 10 -4 . Figure 11 is the communication bit error rate of the orthogonal four-carrier FSCM signal under different signal-to-noise ratio conditions.

[0153] The above embodiments are preferred embodiments of the present application. Ordinary technicians in this field can also make various changes or improvements on this basis. Without departing from the overall concept of the present application, these changes or improvements should fall within the scope of protection required by the present application.

[0154] Explanation of terms:

[0155] ISAC (Integrated Communication and Perception) refers to the integration of communication and perception devices into the same system, exploring trade-offs and mutual gains between them. In an ISAC system, communication and perception are no longer viewed as separate objectives, but rather co-designed for mutual benefit. This allows ISAC to significantly improve spectrum and energy efficiency while reducing hardware and signaling costs.

[0156] FMCW radar: Frequency-modulated continuous wave radar (FMCW radar) refers to a continuous wave radar whose transmission frequency is modulated by a specific signal, such as a weather radar. FMCW radar determines target distance by comparing the difference between the frequency of the echo signal at any given moment and the frequency of the transmitted signal at that moment. The distance is proportional to the frequency difference. The radial velocity and range of the target can be determined by processing the measured frequency difference. Compared to other range-finding and velocity-measuring radars, FMCW radars have a simpler structure. FMCW radars have extensive technical experience, require low peak transmit power, are easy to modulate, are low-cost, and have simple signal processing.

[0157] Chirp: A linear frequency modulation (LFM) signal is a modulated signal whose frequency varies linearly over time. It is also called a chirp signal. LFM technology is widely used in radar and sonar technology. It can be used to increase RF pulse width, extend communication range, and improve average transmit power while maintaining sufficient signal spectrum width and not reducing radar range resolution.

[0158] FSCM: Frequency-Shift Chirp Modulation (FSCM) is a modulation method that encodes information in a chirp signal with a constant chirp rate by shifting the frequency. FSCM signals are a long-range, low-power technology based on chirp signals and are widely used in IoT communications. Compared to traditional sinusoidal modulation methods, FSCM signals, with their spread spectrum and frequency hopping properties, not only inherit the excellent properties of chirp signals but also have better anti-interception performance.

[0159] LoRa: Long Range Radio (LRR) is a low-power wireless standard for local area networks. Its most significant feature is its ability to transmit data over longer distances while maintaining the same power consumption. Due to its long-range, low-power, and secure data transmission capabilities, it is now widely used in the Internet of Things (IoT) and public and private networks.

[0160] FrFT: Fractional Fourier transform, which means passing the signal through a fractional-order transform operator to rotate the signal by different angles in the time-frequency domain, thereby broadening the scope of signal processing.

[0161] MIMO: Multiple Input Multiple Output antennas.

Claims

1. An ISAC method based on orthogonal multi-carrier FSCM signals, characterized in that: For any ISAC device in the ISAC network: (1) Perform frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmit it; When frequency-shift chirp modulation is performed on communication symbols, different spreading factors are used for modulation in each channel of the transmitter; (2) Receive and process the echo signals reflected by each target in a multi-target scenario to achieve real-time detection of the target; the echo signals reflected by the target are orthogonal multi-carrier FSCM signals. (3) Receive orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplex and demodulate the received signals to achieve communication between ISAC devices.

2. The ISAC method according to claim 1, wherein: The modulation methods using different spreading factors are: Add a carrier frequency offset f to the subcarrier FSCM signal offset , f offset It is given by the following definition: Where B is the bandwidth, SF is the spreading factor, that is, the number of modulation bits per communication symbol, t s is the cycle time of each communication symbol, S is the communication symbol; Folding time As the dividing line, a communication symbol S is represented as two parts, which can be expressed as follows: Where k is the slope of frequency change; x T (t) is the FSCM signal at the transmitting end obtained by embedding the communication symbol S; Embed the x of the communication symbol S T (t) The discrete form of the FSCM signal obtained by sampling is shown as follows: Where n is the sampling sequence, f s is the sampling frequency, using single bandwidth; N1={0,…,n fold -1},N2={n fold ,…,2 SF -1}, and n fold =t fold ·f s .

3. The ISAC method according to claim 1, wherein: Each ISAC device transmits and receives signals using a MIMO antenna, and each ISAC device is equipped with multiple transmitting antennas and multiple receiving antennas, each antenna corresponding to multiple different spreading factors.

4. The ISAC method according to claim 1, wherein: The echo signal processing includes demultiplexing the received orthogonal multi-carrier FSCM signal. The demultiplexing of the received orthogonal multi-carrier FSCM signal includes: Assume that the received orthogonal multi-carrier FSCM signal is expressed as: Y=A(θ)X+v where v is a variable with covariance R z Additive zero-mean temporal white noise; First, the corresponding reference signal g is generated in each channel of the receiver according to the corresponding spreading factor SF i (t), the reference signal is in the form of carrier frequency offset f offset FSCM signal is 0; Then, in each channel, the received orthogonal multi-carrier FSCM signal Y(t) is compared with the reference signal g i (t) and extract the FSCM subcarrier x corresponding to each channel. R,i (t):

5. The ISAC method according to claim 4, wherein: The echo signal processing also includes target detection using the obtained subcarriers, specifically: First, select the FSCM subcarrier with the largest spreading factor SF corresponding to the channel and set the sampling frequency f s Set to be equal to the bandwidth B corresponding to the spreading factor SF of the channel, that is, f s =B, then the sampled FSCM discrete signal is: Among them, x Ri [n] is the FSCM discrete signal corresponding to each channel, φ represents the received FSCM discrete signal Y i [n] is the phase, k is the slope of frequency change, n is the sampling sequence, N1={0,…,n fold -1},N2={n fold ,…,2 SF -1}, N is the union of N1 and N2, and n foId =t foId ·f s , f s is the sampling frequency, t fold is the folding time represented by the FSCM symbol in two parts, B is the bandwidth, S is the communication symbol in the data stream; n' is the delay of the signal in discrete time; Then, a standard chirp signal with the same slope is mixed with the FSCM subcarrier to obtain the intermediate frequency signal f IF (t): Where T[n] indicates that the slope k0 is a standard chirp signal, * indicates conjugate operation, and the intermediate frequency f IF = -k0n'; φ' is the phase of the intermediate frequency signal obtained by mixing the received signal with the reference signal; Finally, the CZT algorithm is used to calculate f IF (t) is processed to complete the estimation of the distance and speed of the target; and the arrival angle is estimated by using the MUSIC algorithm and the spectrum peak search method, which is expressed as: Among them, θ MUSIC represents the estimated arrival angle, A(θ) represents the transmit-receive matrix, which is the product of the transposed transmit steering matrix and the receive steering matrix; Λ n It is a diagonal matrix consisting of the last MK eigenvalues ​​of the covariance matrix R of the received signal subcarriers in descending order.

6. The ISAC method according to claim 4, wherein: The received signal is demultiplexed and demodulated. The demodulation is to demodulate the FSCM subcarriers in each channel separately. Specifically, based on the principle of coherent demodulation, a down-chirp signal with the same spreading factor value as the modulated signal is used as the reference signal for demodulation. The demodulation operation in the i-th channel is shown as follows: in, represents the discrete reference signal x ref，i The conjugate form of [n], the communication symbol S corresponds to the maximum value sequence number after the FFT operation.

7. An ISAC device based on orthogonal multi-carrier FSCM signals, characterized in that: Includes transmitter and receiver; The transmitter performs frequency shift chirp modulation on the communication symbols of the data stream to generate an orthogonal multi-carrier FSCM signal and transmits it; When frequency-shift chirp modulation is performed on communication symbols, different spreading factors are used for modulation in each channel of the transmitter; The receiver receives and processes the echo signals reflected by each target in a multi-target scene to achieve real-time detection of the target; wherein the echo signals reflected by the target are orthogonal multi-carrier FSCM signals, The receiver also receives orthogonal multi-carrier FSCM signals transmitted by other ISAC devices in the ISAC network, and demultiplexes and demodulates the received signals to achieve communication between ISAC devices.

8. The ISAC device according to claim 7, wherein: Used to implement the ISAC method according to any one of claims 2 to 6.

9. An ISAC network system based on orthogonal multi-carrier FSCM signals, characterized in that: The method comprises several ISAC devices based on orthogonal multi-carrier FSCM signals as described in any one of claims 7 to 8.

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