Non-integer multiple sampling rate conversion method and device for wireless broadband communication system

Abstract

The embodiment of the invention provides a non-integral multiple sampling rate conversion method and device for a wireless broadband communication system. The method comprises the steps of performing calculation according to an input signal sampling rate and a target output signal sampling rate, and determining a target number of parallel Farrow filters; a least square method is adopted to optimize each Farrow filter, so that each Farrow filter has the same target order number; adopting a Lagrange interpolation method to determine a fractional interval of each Farrow filter; a Farrow filter with the target order is constructed, and the target number is instantiated; and adding the outputs of the target number of Farrow filters to obtain a target signal with the target output signal sampling rate. According to the technical scheme provided by the embodiment of the invention, the resource consumption of the non-integer multiple sampling rate conversion filter can be reduced on the basis of ensuring the signal quality.

Description

Technical Field

[0001] This application relates to the field of wireless communication technologies, and in particular, to a method and apparatus for non-integer sampling rate conversion in a wireless broadband communication system. Background Art

[0002] With the continuous development and complexity of wireless broadband communication systems, the requirements for signal processing are increasing day by day. In practical applications, it is often necessary to perform interpolation or decimation operations on signals, which inevitably involves the conversion of signal sampling rates. Especially in the fields of wireless communication, audio processing, video processing, etc., there is usually a non-integer multiple relationship between the sampling rates of signals.

[0003] In current technical solutions, common methods for implementing non-integer sampling rate conversion include linear interpolation, Lagrange interpolation, and parabolic interpolation, etc. These methods can meet the requirements of signal sampling rate conversion to a certain extent, but when dealing with high-order filters, especially in the hardware implementation process such as FPGA (Field-Programmable Gate Array), there will be a problem of huge resource consumption. The design and implementation of high-order filters require a large amount of logic resources and storage resources, which not only increases the hardware cost but also limits the scalability and flexibility of the system. Therefore, how to reduce the resource consumption of non-integer sampling rate conversion filters on the basis of ensuring signal quality has become an urgent technical problem to be solved. Summary of the Invention

[0004] Embodiments of this application provide a method and apparatus for non-integer sampling rate conversion in a wireless broadband communication system, which can, at least to a certain extent, reduce the resource consumption of non-integer sampling rate conversion filters on the basis of ensuring signal quality.

[0005] Other features and advantages of this application will become apparent through the following detailed description, or be learned in part through the practice of this application.

[0006] According to one aspect of the embodiments of this application, a method for non-integer sampling rate conversion in a wireless broadband communication system is provided, including:

[0007] Calculating according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters;

[0008] Optimizing each of the Farrow filters by using the least squares method so that each of the Farrow filters has the same target order;

[0009] Determining the fractional interval of each of the Farrow filters by using the Lagrange interpolation method;

[0010] Construct a Farrow filter with the target order and instantiate a target number of them;

[0011] Add the outputs of the target number of the Farrow filters to obtain a target signal with the target output signal sampling rate.

[0012] According to one aspect of the embodiments of the present application, there is provided a non-integer sampling rate conversion device for a wireless broadband communication system, including:

[0013] A first determination module, configured to calculate according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters;

[0014] An optimization module, configured to optimize each of the Farrow filters by using the least squares method so that each of the Farrow filters has the same target order;

[0015] A second determination module, configured to determine the fractional interval of each of the Farrow filters by using the Lagrange interpolation method;

[0016] A construction module, configured to construct a Farrow filter with the target order and instantiate a target number of them;

[0017] A processing module, configured to add the outputs of the target number of the Farrow filters to obtain a target signal with the target output signal sampling rate.

[0018] According to one aspect of the embodiments of the present application, there is provided a computer-readable medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the non-integer sampling rate conversion method for a wireless broadband communication system as described in the above embodiments.

[0019] According to one aspect of the embodiments of the present application, there is provided an electronic device, including: one or more processors; a storage device, configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the non-integer sampling rate conversion method for a wireless broadband communication system as described in the above embodiments.

[0020] According to one aspect of the embodiments of the present application, a computer program product or a computer program is provided. The computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the non-integer multiple sampling rate conversion method for a wireless broadband communication system provided in the above embodiments.

[0021] In the technical solutions provided by some embodiments of the present application, by calculating according to the input signal sampling rate and the target output signal sampling rate, the target number of parallel Farrow filters is determined, and the least squares method is used to optimize each Farrow filter so that each Farrow filter has the same target order. Then, the Lagrange interpolation method is used to determine the fractional interval of each Farrow filter, and then a Farrow filter with the target order is constructed and instantiated by the target number. Then, the outputs of the target number of Farrow filters are added together to obtain a target signal with the target output signal sampling rate.

[0022] Thus, a high-order non-integer multiple sampling rate conversion filter is split into multiple parallel Farrow filters. Each Farrow filter is optimized to the same order according to the least squares method, and the corresponding filter coefficients are calculated respectively, and different fractional intervals are configured. In this way, only one order of Farrow filter needs to be designed, and efficient sampling rate conversion can be achieved by instantiating multiple ones. It can not only significantly reduce resource consumption and improve the overall efficiency of the system, but also maintain the integrity and accuracy of the signal.

[0023] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The accompanying drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and are used together with the specification to explain the principles of the present application. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0025] Figure 1 A flowchart showing a non-integer multiple sampling rate conversion method for a wireless broadband communication system according to an embodiment of the present application;

[0026] Figure 2 A schematic structural diagram of a Farrow filter according to an embodiment of the present application;

[0027] Figure 3 Shows a schematic diagram of a non-integer multiple sampling rate conversion architecture according to an embodiment of the present application;

[0028] Figure 4 Shows a block diagram of a non-integer multiple sampling rate conversion device for a wireless broadband communication system according to an embodiment of the present application;

[0029] Figure 5 Shows a schematic structural diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application. Detailed implementation manners

[0030] Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in various forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art.

[0031] In addition, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of the embodiments of the present application. However, those skilled in the art will realize that the technical solutions of the present application can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be used. In other cases, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the present application.

[0032] The block diagrams shown in the drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0033] The flowcharts shown in the drawings are only illustrative and do not necessarily include all the content and operations / steps, nor do they necessarily have to be executed in the described order. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to the actual situation.

[0034] Figure 1 Shows a schematic flowchart of a non-integer multiple sampling rate conversion method for a wireless broadband communication system according to an embodiment of the present application.

[0035] It should be noted that this method can be applied to a terminal device or a server. Among them, the terminal device can include, but is not limited to, one or more of a smart phone, a tablet computer, a portable computer, and a desktop computer; the server can be a physical server or a cloud server.

[0036] As Figure 1 shown, the non-integer multiple sampling rate conversion method for a wireless broadband communication system at least includes steps S110 to S150, which are introduced in detail as follows (hereinafter, taking the application of this method to a terminal device as an example for description, hereinafter referred to as "terminal" for short):

[0037] In step S110, calculate according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters.

[0038] Among them, the input signal sampling rate can be the sampling frequency of the input signal, and the target output signal sampling rate can be the sampling frequency of the desired output signal. For example, the input signal sampling rate f in of a wireless base station is 122.88 MSps, the signal bandwidth is 70 MHz. In order to reduce the sampling rate of the Xicani IQ signal so as to improve the transmission efficiency of CPRI or eCPRI, it is necessary to reduce the input signal sampling rate to 92.16 MSps (i.e., the target output signal sampling rate, f out ).

[0039] The Farrow filter can be a variable fraction delay filter, which can dynamically adjust the delay according to the input signal and the required output sampling rate to achieve accurate sampling rate conversion.

[0040] In some embodiments of the present application, calculating according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters includes:

[0041] Divide the input signal sampling rate by the target output signal sampling rate to obtain a corresponding ratio value;

[0042] According to the ratio value, determine the target number of parallel Farrow filters according to a predetermined rule, and the target number is an integer greater than or equal to the ratio value.

[0043] In this embodiment, the ratio R between the input signal sampling rate f in and the target output signal sampling rate f out can be calculated first, R = f in / f out , for example, the input sampling rate f in = 122.88 MSps, and the target output signal sampling rate f out= 92.16 MSps. Then the corresponding ratio R = f in / f out = 122.88 / 92.16 = 4 / 3.

[0044] Next, according to this ratio R, following a predetermined rule, determine the target number N of Farrow filters to be used in parallel. It should be noted that this target number N is an integer greater than or equal to this ratio. In one example, this target number N can be the smallest integer greater than or equal to the ratio R. For example, if R ≈ 1.3333, then the target number N can be taken as N = 2. In other examples, considering the balance between resources and performance, more filters can reduce the complexity and resource consumption of each filter. It should be understood that more filters can reduce the complexity and resource consumption of each filter, but will increase the complexity of the system and the control logic. Therefore, based on the smallest integer greater than or equal to the ratio R, a predetermined value can be added to obtain the target number N. For example, if the ratio R ≈ 1.333, then the target number N can be taken as N = 4, and so on.

[0045] In this way, by splitting a high-order filter into multiple parallel low-order Farrow filters, the complexity and resource consumption of each filter can be significantly reduced, the overall efficiency of the system can be improved, and the selection of the target number can be adjusted according to specific resource and performance requirements, making the system design more flexible.

[0046] Please continue to refer to Figure 1 , in step S120, use the least squares method to optimize each of the Farrow filters so that each of the Farrow filters has the same target order.

[0047] In this embodiment, it should be understood that the least squares method can be used to find a set of parameters to minimize the sum of the squares of the errors between the model output and the actual data. In this way, the terminal can use this least squares method to calculate to obtain a target order so that each Farrow filter can achieve the best frequency response and the smallest error at the same order, improving the signal quality.

[0048] In step S130, use the Lagrange interpolation method to determine the fractional interval of each of the Farrow filters.

[0049] In this embodiment, the fractional interval can be the delay ratio of the output sampling points relative to the input sampling points, which is a number between 0 and 1, indicating the position of the current output sampling point between two adjacent input sampling points. The fractional interval enables the filter to generate accurate output sampling points in non-integer multiple sampling rate conversions. By inserting a virtual sampling point between two adjacent input sampling points, the fractional interval can achieve precise delay control. And through precise delay adjustment, the fractional interval can reduce signal distortion caused by sampling rate conversion and improve the quality of the output signal. This is particularly important in audio, video, and communication systems. Specifically, the terminal can use the Lagrange interpolation method to determine a fractional interval for each Farrow filter. That is to say, the fractional intervals of different Farrow filters can be the same or different.

[0050] In one embodiment, the terminal can solve according to the following formula to obtain the fractional interval u of each Farrow filter n , n = 0, 1, 2…, N - 1:

[0051]

[0052] where

[0053] In the above formula, y(mT2) is the signal at the new sampling rate T2, and x(kT1) is the signal at the original sampling rate T1. The result of is to use the linear interpolation coefficient c i to fit a new signal x~(mT2), and then perform an accumulation operation with the fractional interval u m .

[0054] Please continue to refer to Figure 1 , in step S140, construct a Farrow filter with the target order and instantiate the target number of them.

[0055] In this embodiment, as Figure 2 shown, a general-purpose Farrow filter with the target order can be constructed, and then instantiated according to the target number obtained from the foregoing calculation, so as to obtain the non-integer multiple sampling rate conversion architecture as shown in Figure 3 .

[0056] Specifically, Figure 2 shows 's implementation structure, where For the sake of convenience of explanation, the expression of y(mT2) can be simply expressed as: Figure 2 In, c lwhere [[ID=]] represents the interpolation coefficient and u represents the fractional interval. After multiplication and accumulation, a new signal y(n) is obtained.

[0057] In step S150, the outputs of the target number of the Farrow filters are added together to obtain a target signal having the target output signal sampling rate.

[0058] In this embodiment, according to the Figure 3 shown architecture, the outputs of the target number of Farrow filters can be added together, that is, a target signal (i.e., y(Nk)) having the target output signal sampling rate can be obtained. Specifically, in Figure 3 , Farrow0,…,Farrow N-1 represents N Farrow filters, and Z -1 represents delaying the input signal x(k) by one beat, and u0,…,u N-1 represents the corresponding fractional interval of each Farrow filter. After the input signal x(k) passes through each Farrow filter, the corresponding sum of accumulations can obtain a new signal y(Nk).

[0059] Thus, based on the Figure 1 shown embodiment, by calculating according to the input signal sampling rate and the target output signal sampling rate, the target number of parallel Farrow filters is determined, and the least squares method is used to optimize each Farrow filter so that each Farrow filter has the same target order. Then, the Lagrange interpolation method is used to determine the fractional interval of each Farrow filter, and then a Farrow filter with the target order is constructed and instantiated with the target number. Then, the outputs of the target number of Farrow filters are added together to obtain a target signal having the target output signal sampling rate.

[0060] Therefore, the high-order non-integer multiple sampling rate conversion filter is split into multiple parallel Farrow filters. Each Farrow filter is optimized to the same order according to the least squares method, and the corresponding filter coefficients are calculated respectively, and different fractional intervals are configured. In this way, only one order of Farrow filter needs to be designed, and high-efficient sampling rate conversion can be achieved by instantiating multiple ones. It can not only significantly reduce resource consumption and improve the overall efficiency of the system, but also maintain the integrity and accuracy of the signal.

[0061] The following introduces the device embodiment of the present application, which can be used to execute the non-integer multiple sampling rate conversion method for a wireless broadband communication system in the above embodiments of the present application. For details not disclosed in the device embodiment of the present application, please refer to the embodiments of the non-integer multiple sampling rate conversion method for a wireless broadband communication system in the above of the present application.

[0062] Figure 4 The block diagram of a non-integer sampling rate conversion device for a wireless broadband communication system according to an embodiment of the present application is shown.

[0063] Referring to Figure 4 As shown, a non-integer sampling rate conversion device for a wireless broadband communication system according to an embodiment of the present application includes:

[0064] A first determination module for calculating according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters;

[0065] An optimization module for optimizing each of the Farrow filters by using the least squares method so that each of the Farrow filters has the same target order;

[0066] A second determination module for determining the fractional interval of each of the Farrow filters by using the Lagrange interpolation method;

[0067] A construction module for constructing a Farrow filter with the target order and instantiating the target number of them;

[0068] A processing module for adding the outputs of the target number of the Farrow filters to obtain a target signal with the target output signal sampling rate.

[0069] Figure 5 The structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0070] It should be noted that Figure 5 The computer system of the electronic device shown is only an example and should not bring any limitation to the functions and usage scope of the embodiments of the present application.

[0071] As Figure 5 shown, the computer system includes a central processing unit (CPU) 501, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 502 or the program loaded from the storage section 508 into the random access memory (RAM) 503, such as executing the method described in the above embodiments. In the RAM 503, various programs and data required for system operation are also stored. The CPU 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0072] The following components are connected to the I / O interface 505: an input section 506 including a keyboard, a mouse, etc.; an output section 507 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 508 including a hard disk, etc.; and a communication section 509 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 509 performs communication processing via a network such as the Internet. The drive 510 is also connected to the I / O interface 505 as needed. A removable medium 511, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is mounted on the drive 510 as needed so that a computer program read therefrom is installed into the storage section 508 as needed.

[0073] Specifically, according to an embodiment of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 509, and / or installed from the removable medium 511. When the computer program is executed by the central processing unit (CPU) 501, various functions defined in the system of the present application are executed.

[0074] It should be noted that the computer-readable medium shown in the embodiments of the present application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium can be transmitted by any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0075] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present application. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown can actually be executed substantially in parallel, and they can sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0076] The units involved in the embodiments described in this application can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the unit itself.

[0077] As another aspect, the present application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by an electronic device, the electronic device implements the methods described in the above embodiments.

[0078] It should be noted that although several modules or units of a device for action execution are mentioned in the above detailed description, such a division is not mandatory. In fact, according to the embodiments of the present application, the features and functions of the two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0079] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented in software or in a manner combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of the present application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the methods according to the embodiments of the present application.

[0080] After considering the specification and practicing the embodiments disclosed herein, those skilled in the art will readily conceive of other embodiments of the present application. The present application is intended to cover any variations, uses, or adaptations of the present application, which follow the general principles of the present application and include well-known common general knowledge or conventional technical means in the technical field not disclosed in the present application.

[0081] It should be understood that the present application is not limited to the exact structures described above and shown in the drawings, and various modifications and changes can be made without departing from its scope. The scope of the present application is only limited by the appended claims.

Claims

1. A non-integer sampling rate conversion method for a wireless broadband communication system, characterized in that: include: Calculate the target number of parallel Farrow filters based on the input signal sampling rate and the target output signal sampling rate; Using the least square method to optimize each of the Farrow filters so that each of the Farrow filters has the same target order; Using Lagrange interpolation method, determine the fractional interval of each Farrow filter; Construct a Farrow filter with the target order and instantiate the target number of filters; The outputs of the target number of Farrow filters are added together to obtain a target signal having the target output signal sampling rate.

2. The method according to claim 1, characterized in that The target number of parallel Farrow filters is determined by calculating the input signal sampling rate and the target output signal sampling rate, including: Divide the input signal sampling rate by the target output signal sampling rate to obtain the corresponding ratio; According to the ratio, a target number of parallel Farrow filters is determined according to a predetermined rule, and the target number is an integer greater than or equal to the ratio.

3. The method according to claim 1, characterized in that The Lagrange interpolation method is used to determine the fractional interval of each Farrow filter, including: Solve according to the following formula to obtain the fractional interval u of each Farrow filter: m , n=0,1,2…,N-1: in, In the above formula, y(mT2) is the signal at the new sampling rate T2, and x(kT1) is the signal at the original sampling rate T1.

4. A non-integer sampling rate conversion device for a wireless broadband communication system, characterized in that: include: A first determination module is used to calculate according to the input signal sampling rate and the target output signal sampling rate to determine the target number of parallel Farrow filters; An optimization module, used for optimizing each of the Farrow filters by using the least square method so that each of the Farrow filters has the same target order; A second determination module is used to determine the fractional interval of each Farrow filter by using Lagrange interpolation method; A construction module, used to construct a Farrow filter with the target order and instantiate a target number of filters; A processing module is used to add the outputs of the target number of Farrow filters to obtain a target signal with the target output signal sampling rate.

5. A computer readable medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the non-integer sampling rate conversion method for a wireless broadband communication system according to any one of claims 1 to 3 is implemented.

6. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the one or more processors to implement the non-integer sampling rate conversion method for a wireless broadband communication system as described in any one of claims 1 to 3.

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