Random access signal generation method and apparatus, and storage medium

Abstract

Disclosed are a random access signal generation method, apparatus, and device, a computer storage medium, a computer program product, and a computer program. The method comprises: performing cyclic shift and discrete Fourier transform on a ZC sequence to obtain a target sequence; determining the number N0 of points and an interpolation ratio α in inverse discrete Fourier transform operation; by performing, on the target sequence, inverse discrete Fourier transform operation in which the number of points is N0, generating a first random access signal corresponding to a sampling point of which a sampling point serial number k is an integer multiple of the interpolation ratio; and on the basis of the first random access signal, using a cubic spline interpolation algorithm to generate a second random access signal corresponding to a sampling point of which the sampling point serial number k is not an integer multiple of the interpolation ratio.

Description

A random access signal generation method, device and storage medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Chinese patent application No. 2023110162641 filed in China on August 14, 2023, the entire contents of which are incorporated herein by reference. Technical Field

[0003] The present disclosure relates to the field of mobile communication technologies, and in particular to a method, apparatus, device, computer storage medium, computer program product, and computer program for generating a random access signal. Background Art

[0004] PRACH (Physical Random Access Channel) has been widely used in cellular mobile communication systems, including WCDMA (Wideband Code Division Multiple Access), LTE (Long Term Evolution), and NR (New Radio). PRACH sends a preamble sequence to the base station to achieve uplink time synchronization and acquire uplink resources. The preamble sequence here is a cyclically shifted ZC (Zadoff-Chu) sequence, as follows: u,v (n) = x u ((n+C v )modL RA ) (1)

[0005] x u,v is the PRACH preamble sequence, x u is a ZC sequence, C v is the shift value, is the imaginary unit, L RA and u are the length and root index of the ZC sequence respectively. Without considering factors such as amplitude gain and transmission timing, the baseband signal of PRACH can be expressed as:

[0006] Where Δf RA is the subcarrier spacing. Assume the baseband sampling rate is f, and rewrite Equation (3) into discrete form:

[0007] Formula (5) is an N-point IDFT (Inverse Discrete Fourier Transform) operation.

[0008] In the latest NR standard (3GPP R17), L RA ∈{139,571,839,1151}. When L RA =139, Δf RA ={15,30,60,120}kHz; when L RA =571, Δf RA =30kHz; when L RA =839, Δf RA ∈{1.25,5}kHz; when L RA =1151, Δf RA = 15kHz. Since the sampling rate f of NR baseband signals is typically 122.88MHz, N∈{98304, 24576, 8192, 4096, 2048, 1024}. For hardware implementation, IDFT operations with very long number of points (98304, 24576, 8192, etc.) are too complex.

[0009] The existing implementation method is to first convert the large-point IDFT operation into a small-point IDFT operation, such as 256 points or 1024 points, and then perform "time domain interval zero insertion" and "frequency domain low-pass filtering" in succession to increase the time domain resolution of the signal.

[0010] Summary of the Invention

[0011] Therefore, the technical problem to be solved by the present disclosure is to overcome the cumbersome steps in the related technology and the need to fully optimize the low-pass filtering, otherwise it is easy to introduce certain errors.

[0012] To solve the above technical problems, the first embodiment of the present disclosure provides a method for generating a random access signal, including:

[0013] Perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence;

[0014] Determine the number of points N0 and interpolation factor α for the inverse discrete Fourier transform operation;

[0015] Generate a first random access signal corresponding to a sampling point whose sampling point number k is an integer multiple of the interpolation magnification by performing an inverse discrete Fourier transform operation with a number of points N0 on the target sequence;

[0016] A second random access signal corresponding to a sampling point whose sampling point sequence number k is not an integer multiple of the interpolation factor is generated according to the first random access signal using a cubic spline interpolation algorithm.

[0017] In some embodiments, performing cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence includes:

[0018] For the ZC sequence x u (i) Perform cyclic shift to obtain the leading sequence x u,v (n): x u,v (n) = x u ((n+C v )modL RA )

[0019] Among them, L RA and u are the length and root index of the ZC sequence respectively, C v is the shift value, is the imaginary unit, n=0,1,...,L RA -1;

[0020] Perform discrete Fourier transform on the leading sequence to obtain the target sequence y u,v (n):

[0021] In some embodiments, the calculation formula for generating the first random access signal s(k) corresponding to the sampling point whose sampling point number is an integer multiple of the interpolation magnification by performing an inverse discrete Fourier transform operation with a number of points N0 on the target sequence is:

[0022] Among them, y u,v (n) is the target sequence, is an imaginary unit, and N is the ratio of the baseband sampling rate to the subcarrier spacing.

[0023] In some embodiments, generating, based on the first random access signal, a second random access signal corresponding to a sampling point whose sampling point sequence number is not an integer multiple of the interpolation factor using a cubic spline interpolation algorithm includes:

[0024] In the interval [xα, (x+1)α], the first random access signal is equivalent to a cubic polynomial function s x (k): s(k)=s x (k) = a x +b x (k-xα)+c x (k-xα) 2 +d x (k-xα) 3k∈{xα+1,xα+2,…,(x+1)α-1},x=0,1,…,N0-2

[0025] Under the conditions of continuity at the breakpoint, continuity of the first-order derivative at the breakpoint, and continuity of the second-order derivative at the breakpoint, the coefficient a of the cubic polynomial function is x , b x , c x , d x Perform a solution to obtain the second random access signal.

[0026] In some embodiments, the coefficient a of the cubic polynomial function is satisfied under the conditions of continuity at the breakpoint, continuity of the first-order derivative at the breakpoint, and continuity of the second-order derivative at the breakpoint. x , b x , c x , d x Solving the problem to obtain the second random access signal includes:

[0027] When the conditions for continuity at the breakpoint are met: s x (xα)=s(xα) (a) s x ((x+1)α)=s((x+1)α) (b)

[0028] When the first-order derivative at the breakpoint is continuous: s′ x ((x+1)α)=s′ x+1 ((x+1)α) (c)

[0029] When the second-order derivative at the breakpoint is continuous: s″ x ((x+1)α)=s″ x+1 ((x+1)α) (d)

[0030] According to formula (a) (b) (c) (d), the coefficient a of the cubic polynomial function is x , b x , c x , d x Solve and get: a x =s(xα) (e)

[0031] Using the cyclic characteristics of the target sequence, cubic spline interpolation boundary conditions are established, and the coefficient c xSolve and calculate the coefficient a x , b x , d x .

[0032] In some embodiments, the target sequence is used to establish a cubic spline interpolation boundary condition, and the coefficient c x Solving includes:

[0033] According to the cyclic characteristics of the target sequence, we can obtain: s(α(x+N0))=s(α(x))

[0034] Where x is any integer;

[0035] Convert equation (g) into a matrix and vector The product of:

[0036] in:

[0037] Pair Vector Solve and get the coefficient c x The value of .

[0038] In some embodiments, the The inverse matrix of Pre-configured based on regularity.

[0039] A second aspect of the present disclosure provides a random access signal generating device, including:

[0040] The target sequence generation module is used to perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence;

[0041] The operation configuration module is used to determine the number of points N0 and the interpolation magnification α of the discrete Fourier inverse transform operation;

[0042] A small-point IDFT module is used to generate a first random access signal corresponding to a sampling point whose sampling point sequence number is an integer multiple of the interpolation magnification by performing an inverse discrete Fourier transform operation with a point number of N0 on the target sequence;

[0043] The cubic spline interpolation module is configured to generate, according to the first random access signal, a second random access signal corresponding to a sampling point whose sequence number is not an integer multiple of the interpolation factor by using a cubic spline interpolation algorithm.

[0044] A third aspect of the present disclosure provides a random access signal generating device, including:

[0045] memory for storing computer programs;

[0046] A processor is configured to implement the steps of the random access signal generation method described in any one of the embodiments of the first aspect when executing the computer program.

[0047] An embodiment of a fourth aspect of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the random access signal generation method described in any embodiment of the first aspect are implemented.

[0048] An embodiment of a fifth aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the random access signal generation method of any embodiment of the first aspect.

[0049] In a sixth aspect, the present disclosure provides a computer program, including computer program code. When the computer program code is executed on a computer, the computer executes the random access signal generation method according to any one of the first aspects. The technical solution provided by the present disclosure has the following advantages over related technologies:

[0050] The random access signal generation method provided in the embodiments of the present disclosure mainly targets the "large-scale IDFT" operation involved in the PRACH baseband signal, converting it into a combination of "small-scale IDFT" and "cubic spline interpolation". At the same time, the special properties of the random access preamble sequence are utilized to quickly obtain the polynomial coefficients of the interpolation function, which can significantly reduce the computational complexity. Compared with existing generation methods, it is simpler to implement and has higher fidelity. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to make the contents of the present disclosure more clearly understood, the present disclosure is further described in detail below based on specific embodiments of the present disclosure in conjunction with the accompanying drawings, wherein:

[0052] FIG1 is a flowchart of a method for generating a random access signal according to an embodiment of the present disclosure;

[0053] FIG2 is a structural block diagram of a random access signal generating apparatus provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0054] The core of this disclosure is to provide a method, apparatus, device and computer storage medium that are simpler to implement and have high fidelity.

[0055] In order to enable those skilled in the art to better understand the present disclosure, the present disclosure is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the embodiments described are only a portion of the embodiments of the present disclosure, and not all of them. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0056] Please refer to FIG1 , which is a flowchart of an implementation method of a random access signal generation method provided by an embodiment of the first aspect of the present disclosure; specifically, it includes the following steps S101 to S104 .

[0057] S101: Perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain a target sequence.

[0058] S102: Determine the number of points N0 and the interpolation magnification α for the inverse discrete Fourier transform operation.

[0059] S103: Generate a first random access signal corresponding to a sampling point whose sampling point sequence number is an integer multiple of the interpolation magnification by performing an inverse discrete Fourier transform operation with a number of points N0 on the target sequence.

[0060] S104: Generate, according to the first random access signal, a second random access signal corresponding to a sampling point whose sequence number is not an integer multiple of the interpolation factor by using a cubic spline interpolation algorithm.

[0061] Based on the above embodiment, this embodiment describes step S101:

[0062] For the ZC (Zadoff-Chu) sequence x u (i) Perform cyclic shift to obtain the leading sequence x u,v (n): x u,v (n) = x u ((n+C v )modL RA )

[0063] Among them, L RA and u are the length and root index of the ZC sequence respectively, C v is the shift value, is the imaginary unit, n=0,1,...,L RA -1;

[0064] Perform discrete Fourier transform on the leading sequence to obtain the target sequence y u,v (n):

[0065] Based on the above embodiment, this embodiment explains step S102:

[0066] Determine the number of points for IDFT operation represents an integer upward, n0 is the optimization coefficient, which is a non-negative integer. RA =839,Δf RA =1.25kHz and L RA =139,Δf RA =15kHz as an example, the parameter configuration is as follows:

[0067] When determining the number of IDFT operation points, it is necessary to balance complexity and fidelity. Generally speaking, the fewer IDFT points, the lower the computational complexity, but a larger interpolation factor is required to match, which will inevitably lead to an increase in error. We tend to set the tolerance for approximation error at 10 -3 This can be submerged in the DAC quantization while minimizing complexity. For use case 1, the IDFT number N0 = 4096 and the interpolation magnification α = 24x are suitable. For use case 2, the IDFT number N0 = 512 and the interpolation magnification α = 16x are suitable.

[0068] Based on the above embodiment, this embodiment explains step S103:

[0069] When the sampling point number k is an integer multiple of the interpolation magnification α, that is, k = xα, x = 0, 1, ..., N0-1:

[0070] It is obtained by using the inverse discrete Fourier transform operation of point N0.

[0071] Based on the above embodiment, this embodiment explains step S104:

[0072] When the sampling point number k is not an integer multiple of the interpolation magnification α, that is, k∈{xα+1,xα+2,…,(x+1)α-1},x=0,1,…,N0-2:

[0073] Assume that in each interval [xα,(x+1)α], s(k) can be independently approximated as a cubic polynomial function: s x (k) = a x +b x (k-xα)+c x (k-xα) 2 +d x (k-xα) 3

[0074] According to the three continuity conditions satisfied by the interpolation algorithm, namely, continuity at the breakpoint, continuity of the first-order derivative at the breakpoint, and continuity of the second-order derivative at the breakpoint, the coefficient a of the cubic polynomial function is x , b x , c x , d x Solve:

[0075] Continuous at the breakpoint, that is: s x (xα)=s(xα) (a) s x ((x+1)α)=s((x+1)α) (b)

[0076] The first-order derivative at the breakpoint is continuous, that is: s′ x ((x+1)α)=s′ x+1 ((x+1)α) (c)

[0077] The second-order derivative at the breakpoint is continuous, that is: s″ x ((x+1)α)=s″ x+1 ((x+1)α) (d)

[0078] The cubic polynomial function s x (k) Substitute (a)(b)(c)(d) to obtain: a x =s(xα) (e)

[0079] Based on the above embodiment, since the Zadoff-Chu sequence has a cyclic characteristic, the target sequence also has a cyclic characteristic. According to the cyclic characteristic of the target sequence, we can obtain: s(α(x+N0))=s(α(x))

[0080] And construct the following matrix-vector product:

[0081] in:

[0082] The coefficient a of the cubic polynomial function in each interval [xα, (x+1)α] x , b x , c x , d x , can be achieved through 's solution to obtain it.

[0083] vector All elements in are s(xα), data corresponding to x=0,1,...,N0-1, all obtained through step S103. It has significant characteristics: the main diagonal is all 4, the diagonal adjacent elements are 1, and the first row and last column, and the last row and first column are all 1. There is also an obvious pattern. Except for the areas near the diagonal, the last column of the first row, and the first column of the last row, the values ​​at other positions are approximately 0.

[0084] Since the matrix The simplicity and regularity of It can be directly configured in hardware. Since the matrix is ​​sparse and has obvious regularities, the storage resources occupied are extremely small.

[0085] In the disclosed embodiment, the "large-point IDFT operation" in the random access signal generation process is converted into "small-point IDFT operation + cubic spline interpolation". Compared with the existing "small-point IDFT operation + time domain interval interpolation 0 + frequency domain low-pass filtering" and other solutions, the implementation is simpler and the fidelity is higher; the cyclic characteristics of the ZC sequence are used to establish the cubic spline interpolation boundary conditions, avoiding operations such as "tailing extension" and avoiding excessive errors; in the process of implementing cubic spline interpolation, regularity judgment is used to avoid "matrix inversion", which can reduce the amount of calculation while maintaining signal fidelity.

[0086] Please refer to FIG2 , which is a structural block diagram of a random access signal generating device provided by an embodiment of the second aspect of the present disclosure. The specific device may include:

[0087] The target sequence generation module 100 is used to perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence;

[0088] The operation configuration module 200 is used to determine the number of points N0 and the interpolation magnification α of the inverse discrete Fourier transform operation;

[0089] The small-point IDFT module 300 is configured to generate a first random access signal corresponding to a sampling point whose sampling point sequence number is an integer multiple of the interpolation magnification by performing an inverse discrete Fourier transform operation with a point number of N0 on the target sequence;

[0090] The cubic spline interpolation module 400 is configured to generate, according to the first random access signal, a second random access signal corresponding to a sampling point whose sequence number is not an integer multiple of the interpolation factor by using a cubic spline interpolation algorithm.

[0091] The random access signal generating apparatus of this embodiment is used to implement the random access signal generating method of any of the embodiments of the first aspect described above. Therefore, the specific implementation of the random access signal generating apparatus can be found in the embodiment of the random access signal generating method described above. For example, the target sequence generating module 100, the operation configuration module 200, the small-point IDFT module 300, and the cubic spline interpolation module 400 are used to implement steps S101-S104 of the random access signal generating method described above. Therefore, the specific implementation of the apparatus can be referred to the description of the corresponding embodiments, and will not be repeated here.

[0092] An embodiment of a third aspect of the present disclosure provides a random access signal generating device, including: a memory for storing a computer program; and a processor for implementing the steps of the random access signal generating method of any one of the embodiments of the first aspect when executing the computer program.

[0093] An embodiment of a fourth aspect of the present disclosure provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the random access signal generation method of any embodiment of the first aspect are implemented.

[0094] An embodiment of a fifth aspect of the present disclosure provides a computer program product, including a computer program, which, when executed by a processor, implements the random access signal generation method of any embodiment of the first aspect.

[0095] An embodiment of a sixth aspect of the present disclosure provides a computer program, including computer program code. When the computer program code is run on a computer, the computer executes the random access signal generation method of any one of the embodiments of the first aspect above.

[0096] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Furthermore, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0097] The present application is described with reference to the flow chart and / or block diagram of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each flow process and / or box in the flow chart and / or block diagram and the combination of the flow process and / or box in the flow chart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processing machine or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for realizing the function specified in one flow chart flow or multiple flows and / or one box or multiple boxes of the block diagram.

[0098] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0099] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0100] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present disclosure.

[0101] It should be noted that the explanation of the random access signal generation method in the aforementioned embodiment is also applicable to the apparatus, device, readable storage medium, computer program product and computer program in the embodiments of the present disclosure, and will not be repeated here.

[0102] All embodiments of the present disclosure may be implemented individually or in combination with other embodiments, and are all considered to be within the scope of protection claimed by the present disclosure.

Claims

1. A random access signal generation method, comprising: Perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence; Determine the number of points N0 and the interpolation factor α of the discrete Fourier inverse transform operation; By performing an inverse discrete Fourier transform operation with a number of points N0 on the target sequence, a first random access signal corresponding to a sampling point whose sampling point number k is an integer multiple of the interpolation multiplier is generated; A second random access signal corresponding to a sampling point whose sampling point number k is not an integer multiple of the interpolation factor is generated according to the first random access signal by using a cubic spline interpolation algorithm.

2. The random access signal generation method according to claim 1, wherein the step of performing cyclic shift and discrete Fourier transform on the ZC sequence to obtain the target sequence comprises: For the ZC sequence x u (i) Perform cyclic shift to obtain the leading sequence x u,v (n): x u,v (n)=x u ((n+C v )modL RA ) Among them, L RA and u are the length and root index of the ZC sequence respectively, C v is the shift value, is an imaginary unit, n=0,1,...,L RA -1; Perform discrete Fourier transform on the leading sequence to obtain the target sequence y u,v (n):

3. The random access signal generation method according to claim 1 or 2, wherein the calculation formula for generating the first random access signal s(k) corresponding to the sampling point whose sampling point number is an integer multiple of the interpolation factor by performing an inverse discrete Fourier transform operation with a point number of N0 on the target sequence is: k=xα,x=0,1,...,N0-1 in, y u,v (n) is the target sequence, is an imaginary unit, and N is the ratio of the baseband sampling rate to the subcarrier spacing.

4. The random access signal generation method according to claim 3, wherein the generating, according to the first random access signal, a second random access signal corresponding to a sampling point whose sampling point number is not an integer multiple of the interpolation factor by using a cubic spline interpolation algorithm comprises: In the interval [xα, (x+1)α], the first random access signal is equivalent to a cubic polynomial function s x (k): s(k)=s x (k)=a x +b x (k-xα)+c x (k-xα) 2 +d x (k-xα) 3 k∈{xα+1,xα+2,…,(x+1)α-1},x=0,1,…,N0-2 Under the conditions of continuity at the breakpoint, continuity of the first-order derivative at the breakpoint, and continuity of the second-order derivative at the breakpoint, the coefficient a of the cubic polynomial function is x , b x , c x , d x A solution is performed to obtain the second random access signal.

5. The random access signal generation method according to claim 4, wherein the coefficient a of the cubic polynomial function is constant under the conditions that the first-order derivative at the breakpoint is continuous and the second-order derivative at the breakpoint is continuous. x , b x , c x , d x Solving the problem, obtaining the second random access signal includes: When the conditions for continuity at the breakpoint are met: s x (xα)=s(xα) (a) s x ((x+1)α)=s((x+1)α) (b) When the first-order derivative at the breakpoint is continuous: s′ x ((x+1)α)=s′ x+1 ((x+1)a) (c) When the second-order derivative at the breakpoint is continuous: s″ x ((x+1)α)=s″ x+1 ((x+1)a) (d) According to formula (a), (b), (c), (d), the coefficient a of the cubic polynomial function is x , b x , c x , d x Solving it, we get: a x =s(xα) (e) Using the cyclic characteristics of the target sequence, cubic spline interpolation boundary conditions are established, and the coefficient c x Solve and calculate the coefficient a x , b x , d x .

6. The random access signal generation method according to claim 5, wherein the cyclic characteristics of the target sequence are used to establish a cubic spline interpolation boundary condition, and the coefficient c x The solution includes: According to the cyclic characteristics of the target sequence, we obtain: s(α(x+N0))=s(α(x)) Where x is any integer; Convert equation (g) into a matrix and vector The product of: in: Pair Vector Solve and get the coefficient c x The value of .

7. The random access signal generation method according to claim 6, wherein the The inverse matrix Pre-configuration based on regularity.

8. A random access signal generating device, comprising: A target sequence generation module is used to perform cyclic shift and discrete Fourier transform on the ZC sequence to obtain a target sequence; An operation configuration module, used to determine the number of points N0 and the interpolation magnification α of the discrete Fourier inverse transform operation; The small-point IDFT module is used to generate a first random access signal corresponding to a sampling point whose sampling point sequence number is an integer multiple of the interpolation multiplier by performing an inverse discrete Fourier transform operation with a point number of N0 on the target sequence; The cubic spline interpolation module is used to generate, according to the first random access signal, a second random access signal corresponding to a sampling point whose sequence number is not an integer multiple of the interpolation ratio by using a cubic spline interpolation algorithm.

9. A random access signal generating device, comprising: Memory for storing computer programs; A processor, configured to implement the steps of the random access signal generation method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the random access signal generation method according to any one of claims 1 to 7 are implemented.

11. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the random access signal generation method according to any one of claims 1 to 7.

12. A computer program, comprising computer program codes, which, when executed on a computer, enable the computer to execute the random access signal generating method according to any one of claims 1 to 7.

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