ISAC sequence generation method and device
By designing a sequence phase using a cubic function to generate an ISAC sequence set, the limitations of single-user applicability and multi-user ambiguity range in existing technologies are solved. This achieves a pin-shaped ambiguity function with a larger ambiguity range, improving sensing accuracy and communication reliability.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-20
- Publication Date
- 2026-03-27
AI Technical Summary
Existing technologies face limitations in designing ISAC sequences, including insufficient applicability in single-user scenarios and limited ambiguity range in multi-user scenarios, resulting in limited communication and sensing performance.
A cubic function is used to design the sequence phase, generating a pin-shaped fuzzy function sequence set with a larger fuzzy region. The sequence set is defined by an odd length and positive integers. Each sequence element is composed of a cubic polynomial with a root of unity. The coefficients are dynamically adjusted to achieve a constant fuzzy function value for the sequence set within the fuzzy region.
It significantly improves perception accuracy and communication reliability, and supports low mutual interference and high-resolution target detection in multi-user scenarios.
Smart Images
Figure CN121750142A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of integrated communication and sensing technology, and more specifically, to an ISAC sequence generation method and apparatus. Background Technology
[0002] In the field of Integrated Communication and Sensing (ISAC) technology, current research focuses on designing signal sequences that can simultaneously optimize communication and sensing performance. The ambiguity function, as a key indicator for evaluating the time-frequency characteristics of a signal, ideally should possess a thumbtack-like characteristic—a sharp peak at the origin and zero sidelobes—to achieve high-resolution target detection and accurate measurement. However, existing technologies face significant challenges in designing such sequence sets: on the one hand, while traditional sequences possess excellent autocorrelation and a thumbtack-like ambiguity function, they are only suitable for single-user scenarios and cannot meet the needs of multi-user communication or collaborative sensing; on the other hand, while sequence set designs based on quadratic functions can be extended to multiple users, their ambiguity region is limited, for example, covering only a small area in the time-delay-Doppler plane. This leads to high sidelobes in the ambiguity function once the parameters exceed this range, thereby reducing the system's interference suppression capability and measurement accuracy. These shortcomings highlight the deficiencies of existing technologies in terms of ambiguity region size and multi-user compatibility.
[0003] Therefore, there is an urgent need for an I SAC sequence generation method and apparatus to solve the above-mentioned technical problems. Summary of the Invention
[0004] The purpose of this invention is to provide an ISAC sequence generation method and apparatus to improve the aforementioned problems. To achieve the above objective, the technical solution adopted by this invention is as follows:
[0005] Firstly, this application provides a method for generating I SAC sequences, including:
[0006] Obtain the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N;
[0007] Based on the sequence length N and the sequence set size M, sequence generation processing is performed to obtain the sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth primitive root of unity ω. N The exponential function.
[0008] Secondly, this application also provides an ISAC sequence generation apparatus, characterized in that it comprises:
[0009] The acquisition unit is used to acquire the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N;
[0010] The processing unit is used to perform sequence generation processing based on the sequence length N and the sequence set size M to obtain the sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth primitive root of unity ω. N The exponential function.
[0011] The beneficial effects of this invention are as follows:
[0012] This invention utilizes cubic functions to design sequence phases, generating a pin-shaped fuzzy function sequence set with a larger fuzzy region. Specifically, the method defines the sequence set based on odd length and positive integers. The elements of each sequence consist of a cubic polynomial modulo the root of unity. The polynomial's form is dynamically adjusted based on whether it is divisible by 3. In this way, the sequence set achieves a constant fuzzy function value within the fuzzy region, thereby significantly improving sensing accuracy and communication reliability.
[0013] The sequence set in this application has a pinhead-like ambiguity function. In communications, the designed sequence can be used as a pilot sequence for multi-user channel estimation or synchronization; in radar, the designed sequence set can be used for target sensing.
[0014] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description
[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 This is a schematic diagram of the self-fuzzy function of each sequence in the ISAC sequence generation method described in this embodiment of the invention;
[0017] Figure 2 This is a schematic diagram of the mutual ambiguity function between every two sequences in the ISAC sequence generation method described in this embodiment of the invention;
[0018] Figure 3 This is a schematic diagram of the I SAC sequence generation method described in an embodiment of the present invention;
[0019] Figure 4 This is a schematic diagram of the I SAC sequence generation device described in an embodiment of the present invention.
[0020] In the diagram: 701, acquisition unit; 702, processing unit. Detailed Implementation
[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.
[0022] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.
[0023] Example 1:
[0024] This embodiment provides a method for generating ISAC sequences.
[0025] See Figure 1 , Figure 2 and Figure 3 The figure shows that the method includes steps S1 and S2.
[0026] Step S1: Obtain the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N;
[0027] It is understandable that obtaining the sequence length N and sequence set size M is a fundamental step in sequence design, where N is constrained to be an odd number and M is a positive integer with M ≤ N. This parameter setting stems from the optimization requirements of the communication-sensing integrated system for the mathematical properties of signal sequences. By choosing an odd number N, the phase symmetry problem that may be introduced by even lengths can be avoided, thereby enhancing the randomness of sequence elements and the peak sharpness of the fuzzy function. The constraint of M ≤ N ensures that the sequence set size matches the sequence length, preventing resource waste and improving scalability in multi-user scenarios. This method obtains N and M through parameter determination processing (such as numerical optimization based on system bandwidth or target resolution requirements), and utilizes the number theory properties of odd numbers (such as simplifying modular arithmetic and unit root calculation) to provide a stable mathematical foundation for the subsequent construction of cubic polynomial sequences.
[0028] Step S2: Based on the sequence length N and the sequence set size M, perform sequence generation processing to obtain the sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth primitive root of unity ω. N The exponential function.
[0029] It is understandable that this step achieves signal waveform design through a unique phase encoding architecture. This step uses a piecewise defined cubic polynomial as the phase generation function, dynamically selecting the operation mode based on the numerical characteristics of the sequence length: when the sequence length is divisible by 3, a cubic term coefficient adjustment strategy is adopted, setting the cubic term coefficient to a / 3; when it is not divisible, the standard cubic term structure is retained. This adaptive mechanism effectively overcomes the phase folding problem during modular arithmetic, ensuring that the generated sequence exhibits uniform distribution characteristics in the complex plane. The parameter configuration system includes three core dimensions: the primary parameter 'a' must satisfy the condition that its greatest common divisor with the sequence length is 1. This requirement ensures the ergodicity of the phase sequence and avoids correlation peak degradation caused by periodic repetition; the secondary parameter 'b' is used to adjust the quadratic phase component, which can optimize the local autocorrelation characteristics of the sequence; and the user identification parameter 'c' achieves uniform division of user resources through a floor function, ensuring the orthogonality basis in multi-user scenarios. This three-dimensional parameter space design gives the sequence set great flexibility, allowing parameter combinations to be adjusted according to different application scenarios.
[0030] Among them, the sequence set Each sequence u i =(u i (0),u i (1),…,u i (N-1)), whose elements are defined as:
[0031]
[0032] Among them, u i (n) represents the nth sequence element. This indicates that parameters a and b are integers chosen from the residue class ring modulo N, and gcd(a,N)=1, meaning that the greatest common divisor of parameter a and sequence length N is 1. Indicates not greater than The largest integer (rounded down), N represents the sequence length, M represents the size of the sequence set, and c i Let represent the parameter of the first-order term, i represent the index number, and N≡0 (mod 3) means that N is divisible by 3. This indicates that it is not divisible by 3.
[0033] Step S2 includes step S21.
[0034] Step S21: Set the exponential function as a cubic polynomial in n. When N is divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, with the coefficient of the cubic term being a divided by 3, the coefficient of the quadratic term being b, and the coefficient of the linear term being c. i .
[0035] It's understandable that when N is a multiple of 3, directly using 'a' as the coefficient of the cubic term might lead to discontinuities or periodic overlaps in phase calculations under modulo N operations. Adjusting the coefficient to a / 3 effectively avoids this phenomenon, ensuring a uniform distribution of sequence elements in the complex plane. This treatment aligns with the requirement that parameter 'a' must be coprime with N, jointly guaranteeing the pseudo-randomness of the generated sequence. Simultaneously, the polynomial retains the coefficients of the quadratic term 'b' and the linear term 'c'. i This forms a complete cubic phase structure. The quadratic coefficient b is responsible for fine-tuning the local correlation properties of the sequence, while the linear coefficient c... i It then carries the user identification function, and achieves orthogonal allocation among multiple users through floor division. This collaborative design ensures that the generated sequence set can guarantee the excellent self-fuzzy function characteristics of individual sequences, while achieving low mutual interference between sequences.
[0036] Step S2 further includes step S22.
[0037] Step S22: Set the exponential function as a cubic polynomial in n. When N is not divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, with coefficients a for the cubic term, b for the quadratic term, and c for the linear term. i .
[0038] It's understandable that the approach differs from the previous method of adjusting the cubic term coefficient to a / 3 when N is divisible by 3. Here, the original parameter a is used directly. The fundamental reason for this is to avoid reversibility conflicts in modulo-N operations. When N and 3 are coprime, the value 3 has a multiplicative inverse in modulo-N operations, thus ensuring that the cubic operation with a coefficient as a can still traverse enough phase points, maintaining the pseudo-random nature of the sequence. Parameter b, as the quadratic term coefficient, continues to play a role in fine-tuning the local autocorrelation of the sequence in this mode. And parameter c... i It strictly carries out the user identification function to ensure that there is sufficient phase difference between different sequences to achieve low mutual interference.
[0039] Step S2 further includes step S23.
[0040] Step S23: Set the coefficients a of the cubic term and b of the quadratic term to integers, and the greatest common factor of a and N is 1, c i It equals i multiplied by N divided by M and rounded down.
[0041] Understandably, this step transforms abstract mathematical constraints into engineering-feasible parameter configuration schemes, enabling the generated sequence set to simultaneously possess ideal autocorrelation characteristics, controllable mutual interference levels, and flexible system scalability, thus providing a reliable signal waveform foundation for the integrated communication and sensing system. This parameterized design method ensures optimal performance while endowing the system with the ability to adapt to different scenarios.
[0042] After step S2, steps S3 and S4 are also included.
[0043] Step S3: According to the sequence set After fuzzy function calculation, the self-fuzzy function of each sequence and the mutual fuzzy function between sequence pairs are obtained;
[0044] It is understandable that when the input in this step uses the cubic phase sequence generated by this invention, the ambiguity function calculation process can automatically highlight its flattening characteristics within a specific time-delay-Doppler region. For self-ambiguity function calculation, the system verifies the sharp main lobe characteristics of a single sequence near the origin by comparing the correlation between the sequence and its own time-delay / frequency-shift version. This step, through calculation, can clearly quantify the sequence's performance on two key indicators: target detection accuracy (reflected by the main lobe width of the self-ambiguity function) and multi-user interference suppression (reflected by the sidelobe level of the mutual ambiguity function). Figure 1 and Figure 2 The calculation results shown intuitively demonstrate the effectiveness of this processing procedure.
[0045] The formula for calculating the fuzzy function is as follows:
[0046]
[0047] Where AF represents the fuzzy function, u i and u j Represents a sequence set In the given sequence, (τ,v) represents the time delay and Doppler shift, N represents the sequence length, M represents the size of the sequence set, p represents the smallest prime factor of N, and i and j represent the sequence indices. Indicates not greater than The largest integer (i.e., rounded down).
[0048] Step S4: Based on the self-ambiguity function and the mutual ambiguity function, determine the time delay range from -p to p and the Doppler range from [value missing]. arrive If p is the smallest prime factor of N, then the sequence set is obtained. Rectangular region on the time-delay-Doppler plane The conclusion is that the pin-shaped characteristic has a constant fuzzy function value.
[0049] Understandably, this step establishes an automated performance verification mechanism. Its uniqueness lies in introducing a dual-judgment logic: first, verifying whether the target region boundary is defined by the mathematical essential characteristics of the sequence length N (i.e., its smallest prime factor p); second, confirming whether the fuzzy function within this region exhibits ideal flatness. This judgment method is not a simple numerical comparison, but rather innovatively links number theory characteristics (smallest prime factor p) with signal processing performance (fuzzy function value).
[0050] Example 2:
[0051] like Figure 2 As shown, this embodiment provides an ISAC sequence generation device, see [link to documentation]. Figure 2 The device includes an acquisition unit 701 and a processing unit 702.
[0052] The acquisition unit 701 is used to acquire the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N;
[0053] Processing unit 702 is used to perform sequence generation processing based on the sequence length N and the sequence set size M to obtain a sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth primitive root of unity ω. N The exponential function.
[0054] It should be noted that the specific manner in which each module performs its operation in the apparatus described in the above embodiments has been described in detail in the embodiments of the method, and will not be elaborated here.
[0055] Example 3:
[0056] Corresponding to the above method embodiments, this embodiment is a specific example. First, determine the sequence length N = 25, M = 5, and define a sequence set:
[0057]
[0058] Each sequence u i =(u i (0),u i (1),…,u i (24)), whose elements are defined as:
[0059]
[0060] We can obtain:
[0061]
[0062] Then sequence set A thumbtack-like fuzzy function was implemented within the fuzzy region (-5,5)×(-5,5).
[0063] The amplitudes of the periodic ambiguity functions of sequences u0 and u1 are as follows: Figure 1 and Figure 2 As shown.
[0064] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.
[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.
Claims
1. A method for generating ISAC sequences, characterized in that, include: Obtain the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N; Based on the sequence length N and the sequence set size M, sequence generation processing is performed to obtain the sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth-order primitive root of unity ω. N The exponential function.
2. The ISAC sequence generation method according to claim 1, characterized in that, Based on the sequence length N and the sequence set size M, sequence generation processing is performed to obtain the sequence set. Following that, it also includes: According to the sequence set After fuzzy function calculation, the self-fuzzy function of each sequence and the mutual fuzzy function between sequence pairs are obtained; Based on the self-ambiguity function and the mutual ambiguity function, it is determined that the time delay range is from -p to p and the Doppler range is... arrive If p is the smallest prime factor of N, then the sequence set is obtained. Rectangular region on the time-delay-Doppler plane The conclusion is that the pin-shaped characteristic has a constant fuzzy function value.
3. The ISAC sequence generation method according to claim 1, characterized in that... Sequence element u i The value of (n) is the root of unity modulo N, ω. N Exponential functions include: The exponential function is set as a cubic polynomial in n. When N is divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, with the coefficient of the cubic term being a divided by 3, the coefficient of the quadratic term being b, and the coefficient of the linear term being c. i .
4. The ISAC sequence generation method according to claim 1, characterized in that... Sequence element u i The value of (n) is the root of unity modulo N, ω. N The exponential function also includes: The exponential function is set as a cubic polynomial in n. When N is not divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, with coefficients a for the cubic term, b for the quadratic term, and c for the linear term. i .
5. The ISAC sequence generation method according to any one of claims 3 or 4, characterized in that... Sequence element u i The value of (n) is the root of unity modulo N, ω. N The exponential function also includes: Set the coefficients of the cubic term 'a' and the quadratic term 'b' to integers, and ensure that the greatest common factor of 'a' and 'N' is 1. i It equals i multiplied by N divided by M and rounded down.
6. An ISAC sequence generation device, characterized in that, include: The acquisition unit is used to acquire the sequence length N and the sequence set size M, where N is an odd number, M is a positive integer, and M≤N; The processing unit is used to perform sequence generation processing based on the sequence length N and the sequence set size M to obtain the sequence set. sequence set It contains M sequences, each sequence u i The length is N, and the sequence element u i The value of (n) is the Nth-order primitive root of unity ω. N The exponential function.
7. The ISAC sequence generation apparatus according to claim 6, characterized in that, Following the processing unit, the system further includes: A computing unit, configured to calculate based on the sequence set After fuzzy function calculation, the self-fuzzy function of each sequence and the mutual fuzzy function between sequence pairs are obtained; The judgment unit is used to determine, based on the self-ambiguity function and the mutual ambiguity function, the time delay range from -p to p and the Doppler range from [value missing]. arrive If p is the smallest prime factor of N, then the sequence set is obtained. Rectangular region on the time-delay-Doppler plane The conclusion is that the pin-shaped characteristic has a constant fuzzy function value.
8. The ISAC sequence generation apparatus according to claim 6, characterized in that, The processing unit includes: The first processing subunit is configured to set the exponential function as a cubic polynomial in n, wherein when N is divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, and the coefficient of the cubic term is a divided by 3, the coefficient of the quadratic term is b, and the coefficient of the linear term is c. i .
9. The ISAC sequence generation apparatus according to claim 6, characterized in that, The processing unit further includes: The second processing subunit is used to set the exponential function as a cubic polynomial in n. When N is not divisible by 3, the polynomial contains cubic, quadratic, and linear terms of n, with coefficients a for the cubic term, b for the quadratic term, and c for the linear term. i .
10. The ISAC sequence generation apparatus according to any one of claims 8 or 9, characterized in that, The processing unit further includes: The third processing subunit is used to set the coefficients of the cubic term 'a' and the quadratic term 'b' to integers, where the greatest common factor of 'a' and 'N' is 1, and c i It equals i multiplied by N divided by M and rounded down.