Iterative channel estimation and compensation method, device, apparatus, medium and product

Abstract

This invention relates to the field of wireless communication technology, providing an iterative channel estimation and compensation method, apparatus, device, medium, and product. The method includes: S100, sampling the output signal of the link to be estimated to obtain a baseband signal; S200, estimating the IQ imbalance parameters and equalization coefficients based on the baseband signal, and using the IQ imbalance parameters and equalization coefficients to compensate for non-ideal channels. Specifically, an iterative feedback correction strategy is used when estimating the IQ imbalance parameters, and an asymptotic optimization strategy for the equalization order is used when estimating the equalization coefficients. This invention achieves non-ideal channel parameter estimation through inter-module parameter iterative feedback and equalizer order asymptotic optimization strategy, and finally designs a corresponding channel compensation filter to achieve comprehensive compensation for channel distortion, solving the reception difficulties and loop lock-out problems caused by non-ideal channel characteristics of broadband high-order signals.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and more specifically, to an iterative channel estimation and compensation method, apparatus, device, medium, and product, which can estimate and compensate for non-ideal channel characteristics in broadband communication systems, and is applicable to communication scenarios with non-ideal channel characteristics, such as satellite communication, wireless communication, and fiber optic communication. Background Technology

[0002] With the continuous advancement of communication and aerospace technologies, humanity's exploration and utilization of space is accelerating, and space activities are showing a trend of rapid development. Various types of spacecraft are distributed in Earth's low and medium orbits, carrying increasingly diverse services and generating ever-larger volumes of data. To improve data transmission rates, high-order modulation and broadband transmission technologies are widely adopted. However, when signals are transmitted through the radio frequency links of transmitters, channels, and receivers, they are inevitably affected by various non-ideal characteristics, leading to severe distortion of the received signal.

[0003] For broadband high-order signals, this distortion is particularly fatal. It not only directly degrades demodulation performance, but more seriously, it can cause the receiver synchronization loop (such as the carrier recovery loop and timing recovery loop) to fail to lock correctly, leading to the failure of the entire receiver link. Therefore, accurately estimating and compensating for the linear and nonlinear impairments introduced by the channel before signal demodulation is crucial to ensuring reliable reception of high-order modulation systems.

[0004] Existing channel compensation methods mostly address single channel distortion factors or use fixed-order equalizers for inter-symbol interference cancellation, which are difficult to adapt to the complex distortion characteristics of broadband high-order signals, resulting in poor compensation performance. Therefore, there is an urgent need for a multi-dimensional, iteratively optimized channel estimation and compensation method that can simultaneously solve multiple channel distortion problems such as IQ imbalance and inter-symbol interference, adapt to the transmission requirements of broadband high-order signals, and ensure the signal demodulation performance and loop locking stability at the receiver. Summary of the Invention

[0005] This invention aims to provide an iterative channel estimation and compensation method, apparatus, device, medium, and product. Through a strategy of inter-module parameter iterative feedback and equalizer order progressive optimization, it achieves non-ideal channel parameter estimation. Finally, it designs a corresponding channel compensation filter to achieve comprehensive compensation for channel distortion, solving the reception difficulties and loop lockout problems of broadband high-order signals caused by non-ideal channel characteristics.

[0006] In a first aspect, the present invention provides an iterative channel estimation and compensation method, comprising: S100, sample the output signal of the channel link to be estimated to obtain the baseband signal; S200, based on baseband signal The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

[0007] In a preferred embodiment, step S100 includes: S101, Input the standard signal into the channel link to be estimated; S102, Sample the output signal of the channel link to be estimated to obtain sampled data; S103 extracts a valid signal segment from the sampled data and converts the valid signal into a baseband signal. .

[0008] In a preferred embodiment, step S200 includes: S201, based on baseband signal An iterative feedback correction strategy is employed to estimate the IQ imbalance parameters, and these parameters are then used to evaluate the baseband signal. IQ imbalance compensation is performed to obtain the signal. ; S202, based on signal The equilibrium parameters are estimated using a strategy of asymptotic optimization of the equilibrium order. S203 uses the final IQ imbalance parameter and equalization coefficient to complete the compensation of the non-ideal channel.

[0009] In a preferred embodiment, step S201 includes: Based on baseband signal The first set of IQ imbalance parameters was calculated. ,in, For the first group of IQ amplitude imbalance parameters, The first set of IQ phase imbalance parameters; using the first set of IQ imbalance parameters For baseband signals IQ imbalance compensation is performed to obtain the signal. ; For signals A preliminary equalization signal is obtained by using a lower equalization order for initial equalization. ; Based on the preliminary equalization signal Calculate the second set of IQ imbalance parameters. ,in, For the second group of IQ amplitude imbalance parameters, The second set of IQ phase imbalance parameters; using the second set of IQ imbalance parameters For the first set of IQ imbalance parameters After making corrections, the final IQ imbalance parameters are obtained. ,in, For the final IQ magnitude imbalance parameter, The final IQ phase imbalance parameter; using the final IQ imbalance parameter For baseband signals IQ imbalance compensation is performed to obtain the signal. .

[0010] In a preferred embodiment, step S202 includes: For signal Using the initial equilibrium algorithm and a lower equilibrium order Perform initial equilibrium to obtain the initial equilibrium coefficients. ; Increase the equilibrium order to A more accurate equalization algorithm is adopted, and the initial equalization coefficient is used. Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signal Filtering is performed to obtain the signal. And calculate its error vector magnitude. ; Increase the equalizer order again to With the balance coefficient Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signal Filtering is performed to obtain the signal. And calculate its error vector magnitude. ; Comparison error vector magnitude and If the difference between the two If the value is less than a preset threshold, the balance coefficient iteration is considered complete, and the balance coefficient is selected. As the final equilibrium coefficient If the difference between the two If it exceeds the preset threshold, then the balance coefficient will be used. As an initial value, the equalization order is increased and the iteration continues until the error vector magnitude of two adjacent iterations is reached. The performance is comparable.

[0011] In a preferred embodiment, step S203 includes: Based on the calculated final IQ imbalance parameters ( , and equilibrium coefficient Construct a complete channel compensation filter; The received real-time signals are then processed sequentially through IQ imbalance compensation and equalization filtering in the channel compensation filter to complete the compensation for the non-ideal channel.

[0012] Secondly, the present invention provides an iterative channel estimation and compensation apparatus, characterized in that it includes: The signal acquisition module is used to sample the output signal of the channel link to be estimated to obtain the baseband signal; Estimation and compensation module, used for baseband signal-based estimation and compensation. The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

[0013] Thirdly, the present invention provides an electronic device, comprising: At least one processor; and a memory communicatively connected to said at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the instructions stored in the memory to perform the above-described method.

[0014] Fourthly, the present invention provides a computer-readable storage medium for storing instructions that, when executed, cause the above-described method to be implemented.

[0015] Fifthly, the present invention provides a computer program product that, when invoked by a computer, causes the computer to execute the above-described method.

[0016] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: 1. This invention completes the compensation for IQ imbalance and channel non-ideal characteristics in stages, and specifically solves the problem of multiple channel distortions of broadband signals, avoiding the performance bottleneck caused by single compensation; 2. The IQ imbalance compensation of the present invention adopts an iterative feedback correction mechanism, which greatly improves the IQ compensation accuracy and adapts to the high sensitivity requirements of broadband high-order signals; 3. This invention employs a progressive equalization strategy, starting with a low-order initial estimate and gradually increasing the order while refining it using a better algorithm. This method avoids the slow convergence and local optima problems that may result from directly using high-order equalizers, and can automatically determine the optimal equalizer order through EVM performance comparison, balancing compensation accuracy and computational complexity, and avoiding the hardware implementation pressure caused by excessively high orders. 4. The integrated channel compensation filter designed in this invention can be directly embedded in the signal processing link of the receiving device, effectively solving the problems of difficulty in receiving broadband high-order signals and loop lockout, and improving receiving performance. Attached Figure Description

[0017] Figure 1 The present invention provides an overall flowchart of an iterative channel estimation and compensation method according to an embodiment of the present invention.

[0018] Figure 2 A detailed flowchart of an iterative channel estimation and compensation method is provided for an embodiment of the present invention.

[0019] Figure 3 This is a flowchart of IQ imbalance estimation and compensation in an embodiment of the present invention.

[0020] Figure 4 This is a flowchart of the equilibrium coefficient estimation in an embodiment of the present invention.

[0021] Figure 5 This is a diagram illustrating the 32APSK signal sampled by the receiver in an embodiment of the present invention.

[0022] Figure 6 This is a diagram illustrating the 32APSK signal after IQ imbalance compensation in an embodiment of the present invention.

[0023] Figure 7 This is a diagram illustrating the 32APSK signal after channel compensation in an embodiment of the present invention.

[0024] Figure 8 This is a schematic diagram of an iterative channel estimation and compensation device provided in an embodiment of the present invention.

[0025] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0026] 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 embodiments of the present invention, and not all embodiments. 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.

[0027] Therefore, the following detailed description of the embodiments of the 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 invention without inventive effort are within the scope of protection of the invention.

[0028] like Figures 1-4 As shown, this embodiment of the invention provides an iterative channel estimation and compensation method, including: S100: Sample the output signal of the channel link to be estimated to obtain the baseband signal.

[0029] S101, Input the standard signal into the channel link to be estimated; S102, Sample the output signal of the channel link to be estimated to obtain sampled data; S103 extracts a valid signal segment from the sampled data and converts the valid signal into a baseband signal. .

[0030] S200, based on baseband signal The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

[0031] S201, based on baseband signal An iterative feedback correction strategy is employed to estimate the IQ imbalance parameters, and these parameters are then used to evaluate the baseband signal. IQ imbalance compensation is performed to obtain the signal. .like Figure 3 As shown, it specifically includes: Based on baseband signal The first set of IQ imbalance parameters was calculated. ,in, For the first group of IQ amplitude imbalance parameters, This is the first set of IQ phase imbalance parameters. Using the first set of IQ imbalance parameters... For baseband signals IQ imbalance compensation is performed to obtain the signal. For the signal A preliminary equalization signal is obtained by using a lower equalization order for initial equalization. .

[0032] Based on the preliminary equalization signal Calculate the second set of IQ imbalance parameters. ,in, For the second group of IQ amplitude imbalance parameters, This is the second set of IQ phase imbalance parameters. Using the second set of IQ imbalance parameters... For the first set of IQ imbalance parameters After making corrections, the final IQ imbalance parameters are obtained. ,in, For the final IQ magnitude imbalance parameter, The final IQ phase imbalance parameters. Using the final IQ imbalance parameters. For baseband signals IQ imbalance compensation is performed to obtain the signal. .

[0033] S202, based on signal The equilibrium parameters are estimated using a strategy of asymptotic optimization of the equilibrium order. For example... Figure 4 As shown, it specifically includes: For signal Using the initial equilibrium algorithm and a lower equilibrium order Perform initial equilibrium to obtain the initial equilibrium coefficients. .

[0034] Increase the equilibrium order to ( > ), and adopt a more accurate equalization algorithm, and use the initial equalization coefficient. Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signal Filtering is performed to obtain the signal. And calculate its error vector magnitude. .

[0035] Increase the equalizer order again to ( > ), with balance coefficient Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signal Filtering is performed to obtain the signal. And calculate its error vector magnitude. .

[0036] Comparison error vector magnitude and If the difference between the two If the value is less than a preset threshold, the balance coefficient iteration is considered complete, and the balance coefficient is selected. (The equilibrium coefficient from the previous iteration) is used as the final equilibrium coefficient. If the difference between the two Greater than the preset threshold (i.e.) Significantly greater than Then, the equilibrium coefficient is used. As an initial value, the equalization order is increased and the iteration continues until the error vector magnitude of two adjacent iterations is reached. The performance is comparable.

[0037] S203 uses the final IQ imbalance parameter and equalization coefficient to complete the compensation of the non-ideal channel.

[0038] Based on the calculated final IQ imbalance parameters ( , and equilibrium coefficient A complete channel compensation filter is constructed. Subsequent received real-time signals are then sequentially processed through the IQ imbalance compensation and equalization filtering sections of the channel compensation filter to compensate for the non-ideal channel.

[0039] Taking a 32APSK receiver system with IQ imbalance and non-ideal characteristics as an example, the specific implementation of the above iterative channel estimation and compensation method is described in detail.

[0040] S100 samples the output signal of the channel link to be estimated to obtain the baseband signal. The transmitter sends a 32APSK standard signal, which is input to the channel link to be estimated. The channel link typically includes down-converters, filters, low-noise amplifiers, and other equipment. The output signal of the channel link to be estimated is connected to the receiver. A valid signal is buffered after the sampling module in the receiver, and then converted into a baseband signal by the digital down-conversion module. ,like Figure 5 As shown in the figure. The sampling rate of the sampling module is consistent with the operating sampling rate of the receiver.

[0041] S200, based on baseband signal The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

[0042] S201, based on baseband signal An iterative feedback correction strategy is employed to estimate the IQ imbalance parameters, and these parameters are then used to evaluate the baseband signal. IQ imbalance compensation is performed to obtain the signal. .

[0043] a) First estimation: based on baseband signal The first set of IQ imbalance parameters was calculated. ,in, For the first group of IQ amplitude imbalance parameters, This is the first set of IQ phase imbalance parameters. Using the first set of IQ imbalance parameters... For baseband signals IQ imbalance compensation is performed to obtain the signal. For the signal A preliminary equalization signal was obtained by using a CMA equalizer with an equalization order of 5. .

[0044] b) Second estimation: based on the preliminary equalization signal Calculate the second set of IQ imbalance parameters. ,in, For the second group of IQ amplitude imbalance parameters, These are the second set of IQ phase imbalance parameters.

[0045] c) Calculate the final parameters: using the second set of IQ imbalance parameters For the first set of IQ imbalance parameters After making corrections, the final IQ imbalance parameters are obtained. ,in, For the final IQ magnitude imbalance parameter, The final IQ phase imbalance parameters. Using the final IQ imbalance parameters. For baseband signals IQ imbalance compensation is performed to obtain the signal. ,like Figure 6 As shown.

[0046] S202, based on signal The equilibrium parameters are estimated using a strategy of asymptotic optimization of the equilibrium order.

[0047] a) Initial equalization: for the signal Initial equalization was performed using a CMA equalizer with an equalization order of 5 to obtain the initial equalization coefficients. .

[0048] b) Increase the equilibrium order to 7 and use the LMS algorithm (Least Mean Square Algorithm) with the initial equilibrium coefficients. Initialize the coefficients (padding them with zeros to order 7) to obtain the equilibrium coefficients. Use the balance coefficient For signal Filtering is performed to obtain the signal. Use the following formula to analyze the signal. Calculate the magnitude of the error vector .

[0049]

[0050] in, for The corresponding ideal signal, For signal The k One data point, N For signal The total number of data.

[0051] c) Increase the order to 9, using the equalization factor Initialize the coefficients (padding them with zeros to order 9) to obtain the equilibrium coefficients. Use the balance coefficient For signal Filtering is performed to obtain the signal. For the signal Calculate the magnitude of the error vector .

[0052] d) If Therefore, increasing the filter order improves the equalization performance. Thus, the equalization coefficients... Using the initial values ​​(zero-padding at order 11), recalculate the equilibrium coefficients. The equilibrium coefficients are then obtained. Use the balance coefficient For signal Filtering is performed to obtain the signal. For the signal Calculate the magnitude of the error vector .

[0053] e) If increasing the filter order does not improve the equalization performance, then the previous equalization coefficients should be used. As the final equilibrium coefficient .

[0054] S203 uses the final IQ imbalance parameter and equalization coefficient to complete the compensation of the non-ideal channel.

[0055] Based on the calculated final IQ imbalance parameters ( , and equilibrium coefficient A complete channel compensation filter is constructed in the receiver. The filter parameters are configurable, allowing for recalculation when the receiver link changes. Subsequent received real-time signals undergo IQ imbalance compensation and equalization filtering sequentially to compensate for the non-ideal channel. Figure 7 As shown.

[0056] Based on the same technological concept, such as Figure 8 As shown, embodiments of the present invention also provide an iterative channel estimation and compensation apparatus, comprising: The signal acquisition module is used to sample the output signal of the channel link to be estimated to obtain the baseband signal; Estimation and compensation module, used for baseband signal-based estimation and compensation. The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

[0057] The specific working principles of each functional module in the above-mentioned device can be referred to the description in the foregoing method embodiments, and will not be repeated here.

[0058] Based on the same technical concept, embodiments of the present invention also provide an electronic device that can implement the iterative channel estimation and compensation method flow provided in the above embodiments of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic devices. Figure 9 As shown, the electronic device may include: At least one processor and a memory connected to the at least one processor. In this embodiment of the invention, the specific connection medium between the processor and the memory is not limited. Figure 9 The example used is the connection between the processor and memory via a bus. The bus... Figure 9 The connections between other components are indicated by thick lines and are for illustrative purposes only, not as limiting information. Buses can be divided into address buses, data buses, control buses, etc., but for ease of representation, [the specific bus type is not shown here]. Figure 9 The processor is represented by a single thick line, but this does not imply that there is only one bus or one type of bus. Alternatively, a processor can also be called a controller; there are no restrictions on the name.

[0059] In this embodiment of the invention, the memory stores instructions that can be executed by at least one processor. By executing the instructions stored in the memory, at least one processor can execute an iterative channel estimation and compensation method as described above.

[0060] The processor is the control center of the device. It can connect to various parts of the control device through various interfaces and lines. By running or executing instructions stored in memory and calling data stored in memory, it can monitor the device's various functions and process data, thereby enabling overall monitoring of the device.

[0061] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor, wherein the application processor primarily handles the operating system, user interface, and applications, while the modem processor primarily handles wireless communication. It is understood that the modem processor may also not be integrated into the processor. In some embodiments, the processor and memory may be implemented on the same chip; in some embodiments, they may also be implemented separately on separate chips.

[0062] The processor can be a general-purpose processor, such as a CPU, digital signal processor, application-specific integrated circuit, field-programmable gate array or other programmable logic device, discrete gate or transistor logic device, or discrete hardware component, capable of implementing or executing the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the iterative channel estimation and compensation method disclosed in the embodiments of this invention can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0063] Memory, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. Memory can include at least one type of storage medium, such as flash memory, hard disk, multimedia cards, card-type memory, random access memory (RAM), static random access memory (SRAM), programmable read-only memory (PROM), read-only memory (ROM), and electrically erasable programmable read-only memory (EPROM). Only memory (EEPROM), magnetic storage, magnetic disks, optical disks, etc. A memory is any other medium capable of carrying or storing desired program code in the form of instructions or data structures, and accessible by a computer, but is not limited thereto. The memory in embodiments of this invention can also be a circuit or any other device capable of performing storage functions for storing program instructions and / or data.

[0064] By designing and programming the processor, the code corresponding to the iterative channel estimation and compensation method described in the foregoing embodiments can be embedded into the chip, enabling the chip to execute the steps of the method described in the foregoing embodiments during runtime. How to design and program the processor is a technique well-known to those skilled in the art and will not be elaborated upon here.

[0065] Based on the same inventive concept, embodiments of the present invention also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform an iterative channel estimation and compensation method described above.

[0066] In some alternative embodiments, the present invention also provides that various aspects of an iterative channel estimation and compensation method can also be implemented as a program product comprising program code that, when the program product is run on a device, causes the control device to perform the steps in an iterative channel estimation and compensation method according to various exemplary embodiments of the present invention as described above.

[0067] It should be noted that although several units or sub-units of the apparatus have been mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to embodiments of the invention, the features and functions of two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. Furthermore, although the operation of the method of the invention is described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0068] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can be implemented in one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs) containing computer-usable program code. The form of a computer program product implemented on ROM, optical memory, etc.

[0069] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a server, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0070] Program code for performing the operations of this invention can be written using any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0071] In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0072] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0073] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0074] 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.

Claims

1. An iterative channel estimation and compensation method, characterized in that, include: S100, sample the output signal of the channel link to be estimated to obtain the baseband signal; S200, based on baseband signal The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

2. The iterative channel estimation and compensation method according to claim 1, characterized in that, Step S100 includes: S101, Input the standard signal into the channel link to be estimated; S102, Sample the output signal of the channel link to be estimated to obtain sampled data; S103 extracts a valid signal segment from the sampled data and converts the valid signal into a baseband signal. .

3. The iterative channel estimation and compensation method according to claim 1, characterized in that, Step S200 includes: S201, based on baseband signal An iterative feedback correction strategy is employed to estimate the IQ imbalance parameters, and these parameters are then used to evaluate the baseband signal. IQ imbalance compensation is performed to obtain the signal. ; S202, based on signal The equilibrium parameters are estimated using a strategy of asymptotic optimization of the equilibrium order. S203 uses the final IQ imbalance parameter and equalization coefficient to complete the compensation of the non-ideal channel.

4. The iterative channel estimation and compensation method according to claim 3, characterized in that, Step S201 includes: Based on baseband signal The first set of IQ imbalance parameters was calculated. ,in, For the first group of IQ amplitude imbalance parameters, The first set of IQ phase imbalance parameters; using the first set of IQ imbalance parameters For baseband signals IQ imbalance compensation is performed to obtain the signal. ; For signals A preliminary equalization signal is obtained by using a lower equalization order for initial equalization. ; Based on the preliminary equalization signal Calculate the second set of IQ imbalance parameters. ,in, For the second group of IQ amplitude imbalance parameters, The second set of IQ phase imbalance parameters; using the second set of IQ imbalance parameters For the first set of IQ imbalance parameters After making corrections, the final IQ imbalance parameters are obtained. ,in, For the final IQ magnitude imbalance parameter, The final IQ phase imbalance parameter; using the final IQ imbalance parameter For baseband signals IQ imbalance compensation is performed to obtain the signal. .

5. The iterative channel estimation and compensation method according to claim 3, characterized in that, Step S202 includes: For signals Using the initial equilibrium algorithm and a lower equilibrium order Perform initial equilibrium to obtain the initial equilibrium coefficients. ; Increase the equilibrium order to A more accurate equalization algorithm is adopted, and the initial equalization coefficient is used. Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signals Filtering is performed to obtain the signal. And calculate its error vector magnitude. ; Increase the equalizer order again to With the balance coefficient Iterative calculations are performed using the initial value for the signal. To achieve equilibrium, obtain the equilibrium coefficient. Use the balance coefficient For signals Filtering is performed to obtain the signal. And calculate its error vector magnitude. ; Comparison error vector magnitude and If the difference between the two If the value is less than a preset threshold, the balance coefficient iteration is considered complete, and the balance coefficient is selected. As the final equilibrium coefficient If the difference between the two If it exceeds the preset threshold, then the balance coefficient will be used. As an initial value, the equalization order is increased and the iteration continues until the error vector magnitude of two adjacent iterations is reached. The performance is comparable.

6. The iterative channel estimation and compensation method according to claim 3, characterized in that, Step S203 includes: Based on the calculated final IQ imbalance parameters ( , and equilibrium coefficient Construct a complete channel compensation filter; The received real-time signals are then processed sequentially through IQ imbalance compensation and equalization filtering in the channel compensation filter to complete the compensation for the non-ideal channel.

7. An iterative channel estimation and compensation device, characterized in that, include: The signal acquisition module is used to sample the output signal of the channel link to be estimated to obtain the baseband signal; Estimation and compensation module for baseband signal The IQ imbalance parameters and equalization coefficients are estimated, and the compensation for the non-ideal channel is completed using the IQ imbalance parameters and equalization coefficients. Specifically, an iterative feedback correction strategy is adopted when estimating the IQ imbalance parameters, and an asymptotic optimization strategy of the equalization order is adopted when estimating the equalization coefficients.

8. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions executable by the at least one processor, which executes the instructions stored in the memory to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store instructions that, when executed, cause the method as described in any one of claims 1-6 to be implemented.

10. A computer program product, characterized in that, When the computer program product is invoked by a computer, it causes the computer to perform the method as described in any one of claims 1-6.

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