A signal-to-noise ratio estimation method based on interference reconstruction and cancellation

Abstract

This invention discloses a signal-to-noise ratio (SNR) estimation method based on interference reconstruction and cancellation, belonging to the field of wireless communication technology. The method includes: S1, performing interference detection on the signal to be detected to determine whether interference exists in the current signal; S2, if no interference is detected, directly estimating the SNR; S3, if interference is detected, performing interference reconstruction and cancellation to obtain a signal without interference, using this signal as the signal to be detected, and repeating S1 until no interference is detected in the current signal, then estimating the SNR to obtain the SNR estimation result. This invention can achieve high-precision SNR estimation under interference conditions, improving channel quality assessment performance under interference conditions.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a signal-to-noise ratio estimation method based on interference reconstruction and cancellation. Background Technology

[0002] Orthogonal frequency division multiplexing (OFDM) is a multi-carrier modulation technique widely used in wireless communication systems. By distributing high-speed data streams across multiple orthogonal subcarriers for parallel transmission, it effectively combats multipath effects, improves spectral efficiency, and reduces inter-symbol interference. Therefore, it is widely used in mobile communications (4G LTE, 5G NR), WiFi, WiMax, DVB-T / DVB-T2, etc.

[0003] Signal-to-noise ratio (SNR) is an important indicator of channel quality and can be used for transmission power control, optimization of coding and modulation schemes, and auxiliary soft decoding algorithms. Accurate SNR estimation is an important prerequisite and foundation for improving the reliability and transmission efficiency of OFDM communication systems.

[0004] In practical OFDM wireless communication systems, signal-to-noise ratio (SNR) estimation algorithms based on preamble symbols are widely used. OFDM symbols with a repetitive structure are used as preamble symbols, i.e., s(n) = s(n + N / 2), where N represents the length of the OFDM symbol and n = 0, 1, 2, ..., N / 2-1. After transmission through an additive white Gaussian noise (AWGN) channel, the received signal can be expressed as r(n) = s(n) + w(n), where w(k) represents a signal with a mean of 0 and a variance of σ. 2 Gaussian white noise. The signal power of the received symbol can be estimated as:

[0005]

[0006] Where, r I (n) and r Q (n) represent the real and imaginary parts of the received signal r(n), respectively. The noise power of the received signal can be estimated using the following formula:

[0007]

[0008] Therefore, the signal-to-noise ratio estimate can be obtained as follows:

[0009] The above methods achieve good signal-to-noise ratio (SNR) estimation performance in both AWGN and fading channels. However, the SNR estimation performance deteriorates sharply when interference signals are present in the channel. This leads to the failure of traditional adaptive coding modulation and channel decoding mechanisms under interference conditions. Summary of the Invention

[0010] This invention provides a signal-to-noise ratio (SNR) estimation method based on interference reconstruction and cancellation, in order to solve the technical problem that the SNR estimation performance of traditional SNR estimation algorithms cannot meet the requirements when there are interference signals in the channel.

[0011] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0012] On the one hand, the present invention provides a signal-to-noise ratio estimation method based on interference reconstruction and cancellation, including:

[0013] S1, perform interference detection on the signal to be detected to determine whether there is interference in the current signal;

[0014] S2, If no interference signal is detected in the current signal, the signal-to-noise ratio is directly estimated;

[0015] S3. If interference is detected in the current signal, the interference is reconstructed and canceled to obtain the signal after interference elimination. The signal after interference elimination is used as the signal to be detected. S1 is executed again until interference is detected in the current signal. Then, the signal-to-noise ratio is estimated to obtain the signal-to-noise ratio estimation result.

[0016] Furthermore, the step of performing interference detection on the signal to be detected to determine whether there is interference in the current signal includes:

[0017] Pad the end of the data in the signal r(n) to be detected, where 0≤n≤N-1, to a length of N. FFT N represents the length of the signal to be detected; the new length is obtained as N FFT Received sequence Right now:

[0018]

[0019] Initialize the interference signal frequency set J as an empty set Φ, and the interference-free signal frequency set Q = {k | 0 ≤ k ≤ N}. FFT -1}; where k represents the frequency index;

[0020] right As N FFT Point Fast Fourier Transform operation yields R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k)=|R(k)| 2 ; where NFFT express Length;

[0021] Determine the interference signal decision threshold T;

[0022] Compare P(k) with the interference signal decision threshold T. If P(k) ≥ T, then an interference signal is determined to exist at frequency index k. In this case, J is updated to J = {k|P(k) ≥ T}; simultaneously, Q is updated to...

[0023] After determining whether there is interference signal at each frequency index, it is determined whether J is an empty set. If J is an empty set, it is determined that there is no interference signal in the signal to be detected; otherwise, it is determined that there is interference signal in the signal to be detected.

[0024] Further, determining the interference signal decision threshold T includes:

[0025] Calculate the average power of the signal The formula is as follows:

[0026]

[0027] Where |Q| represents the number of elements in Q;

[0028] Based on average power Obtain the interference signal decision threshold Where η is a preset value greater than 1.

[0029] Furthermore, if interference is detected in the current signal, the interference reconstruction and cancellation are performed, including:

[0030] If interference is detected in the current signal, consecutive k values ​​in J are merged into a subset, thus J is written as the union of multiple subsets, i.e., J = J1∪J2∪…∪J m ; among which, J l Let l represent the l-th subset, l = 1, 2, 3, ..., m; m represents the number of subsets. The k value in each subset represents the frequency index corresponding to a single-tone interference signal, that is, the number of single-tone interference signals is m.

[0031] For each single-tone interference signal, the interference signal parameters are estimated separately.

[0032] Based on the estimated interference signal parameters, interference signal reconstruction and interference cancellation are performed.

[0033] Furthermore, the interference signal parameters include: interference signal power, interference signal frequency, and interference signal phase.

[0034] Furthermore, the step of estimating the interference signal parameters for each single-tone interference signal includes:

[0035] For the l-th single-tone interference signal, its energy estimate is... Then the power estimate corresponding to the l-th single-tone interference signal Among them, J l Let l represent the l-th subset, 1≤l≤m;

[0036] For the l-th single-tone interference signal, find the set {P(k)|k∈J}. l Frequency index corresponding to the peak value in} Then the frequency estimate corresponding to the l-th single-tone interference signal

[0037] For the l-th single-tone interference signal, its corresponding phase estimate value in, express The result of the Fast Fourier Transform operation at the corresponding location.

[0038] Furthermore, the interference signal reconstruction and interference cancellation are performed based on the estimated interference signal parameters, using the following formula:

[0039]

[0040] Where r(n)′ represents the signal after interference is eliminated; r(n) represents the signal to be detected; n=0,1,2,…,N-1.

[0041] Furthermore, the signal-to-noise ratio estimation includes:

[0042] A signal-to-noise ratio (SNR) estimation algorithm based on the preamble symbol is used to estimate the SNR of the current signal, resulting in an estimated signal power value. and noise power estimates And finally obtain the signal-to-noise ratio.

[0043] In another aspect, the present invention also provides an electronic device comprising a processor and a memory; wherein the memory stores at least one instruction, which is loaded and executed by the processor to implement the above-described method.

[0044] In another aspect, the present invention also provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the above method.

[0045] The beneficial effects of the technical solution provided by this invention include at least the following:

[0046] This invention addresses the signal-to-noise ratio (SNR) estimation problem in OFDM systems under single-tone and multi-tone interference conditions. It provides an SNR estimation method based on interference reconstruction and cancellation. This method first estimates the interference signal parameters, then performs interference reconstruction and cancellation, and finally uses traditional methods for SNR estimation. This significantly improves the SNR estimation performance under interference conditions, thereby enhancing channel quality assessment performance under interference. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating the signal-to-noise ratio estimation method based on interference reconstruction and cancellation provided by the present invention.

[0049] Figure 2 The power spectrum and interference detection threshold during the first iteration detection provided in the second embodiment of the present invention;

[0050] Figure 3 The second embodiment of the present invention provides the power spectrum and interference detection threshold during the second iteration detection;

[0051] Figure 4 The power spectrum and interference detection threshold during the third iteration detection provided in the second embodiment of the present invention;

[0052] Figure 5 This is a schematic diagram showing the performance comparison between the signal-to-noise ratio estimation result based on interference estimation and cancellation provided in the second embodiment of the present invention and the traditional method;

[0053] Figure 6 This is a schematic diagram showing the performance comparison between the signal-to-noise ratio estimation result based on interference estimation and cancellation provided in the third embodiment of the present invention and the traditional method;

[0054] Figure 7 This is a system block diagram of the electronic device provided in the fourth embodiment of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0056] First, it should be noted that in the embodiments of the present invention, the words "exemplarily," "for example," etc., are used to indicate that they are examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the term "exemplarily" is intended to present the concept in a specific manner. Furthermore, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either one or the other.

[0057] First Embodiment

[0058] To address the signal-to-noise ratio (SNR) estimation problem in OFDM systems under single-tone or multi-tone interference conditions, this embodiment provides an SNR estimation method based on interference reconstruction and cancellation, the execution flow of which is as follows: Figure 1 As shown, this method first utilizes an iterative detection and cancellation approach to accurately estimate parameters such as amplitude, frequency, and phase of the interference signal. Then, the interference signal is reconstructed and interference cancellation is performed. Finally, signal-to-noise ratio (SNR) estimation is conducted based on traditional methods. This effectively solves the SNR estimation problem of OFDM systems under single-tone and multi-tone interference conditions. This method can be implemented by an electronic device, which can be a terminal or a server. It includes the following steps:

[0059] S1, perform interference detection on the signal to be detected to determine whether there is interference in the current signal;

[0060] Specifically, the implementation process of S1 above is as follows:

[0061] S11, for the received preamble symbol r(n), 0≤n≤N-1, a new received sequence is obtained by padding the data with zeros at the end. as follows:

[0062]

[0063] Where, N FFT This is a preset value; N represents the length of the signal to be detected.

[0064] S12, Initialize the interference signal frequency set J as an empty set Φ, and the interference-free signal frequency set Q = {k|0≤k≤N}. FFT -1}; where k represents the frequency index;

[0065] S13, for the received sequence As N FFT Point Fast Fourier Transform (FFT) operation yields R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k)=|R(k)| 2 ;

[0066] S14, determine the interference signal decision threshold T; specifically including:

[0067] S141, Calculate the average power of the signal. The formula is as follows:

[0068]

[0069] Where |Q| represents the number of elements in set Q;

[0070] S142, Obtain the interference signal decision threshold. Where η > 1.

[0071] S15, compare P(k) with the interference signal decision threshold T. If P(k) ≥ T, then it is determined that there is an interference signal at frequency index k, i.e., J = {k|P(k) ≥ T}; at the same time, set Q can be updated to

[0072] S16. After determining whether there is an interference signal at each frequency index, determine whether J is an empty set. If J is an empty set, it is determined that there is no interference signal in the signal. At this time, execute S2 and directly use equation (1) and equation (2) to estimate the signal-to-noise ratio. Otherwise, it is determined that there is an interference signal in the signal. At this time, execute S3.

[0073] S2, If no interference signal is detected in the current signal, the signal-to-noise ratio is directly estimated;

[0074] S3, if interference is detected in the current signal, the interference is reconstructed and canceled to obtain the signal after interference elimination. The signal after interference elimination is used as the signal to be detected. S1 is executed again until interference is detected in the current signal. Then the signal-to-noise ratio is estimated to obtain the signal-to-noise ratio estimation result.

[0075] Specifically, the implementation process of S3 above includes:

[0076] S31, merge consecutive k values ​​in set J into a subset. This allows J to be written as the union of multiple subsets, i.e., J = J1∪J2∪…∪J m ; among which, J l Let l represent the l-th subset, l = 1, 2, 3, ..., m; m represents the number of subsets. The k value in each subset represents the frequency index corresponding to a single-tone interference signal. Thus, it can be determined that there are currently m single-tone interference signals.

[0077] S32, perform interference signal parameter estimation for each of the m detected interference signals; wherein, the interference signal parameters include: interference signal power, interference signal frequency, and interference signal phase;

[0078] For the l-th (1≤l≤m) interference signal, its energy estimate is... Then the power estimate corresponding to the l-th interference signal Among them, J l Let l represent the l-th subset, 1≤l≤m;

[0079] For the l-th interference signal, find the set {P(k)|k∈J} l Frequency index corresponding to the peak value in} Then the frequency estimate corresponding to the l-th interference signal

[0080] For the l-th interference signal, its corresponding phase estimate value in, express The result of the Fast Fourier Transform operation at the corresponding location.

[0081] S33, based on the estimated interference signal parameters, performs interference signal reconstruction and interference cancellation, using the following formula:

[0082]

[0083] S34, using the updated received signal r(n), return to S1 to re-detect and estimate the interference signal until the interference signal is completely eliminated; thus, the iterative interference detection and suppression method can be used to obtain the signal after the interference is completely eliminated, and then S35 can be executed to estimate the signal-to-noise ratio.

[0084] S35, based on the received signal r(n) after interference reconstruction and cancellation, the signal power estimate is obtained using equations (1) and (2). and noise power estimates And finally obtain the signal-to-noise ratio.

[0085] In summary, this embodiment addresses the signal-to-noise ratio (SNR) estimation problem in OFDM systems under single-tone and multi-tone interference conditions. It provides an SNR estimation method based on interference reconstruction and cancellation. First, interference signal parameters are estimated; then, interference reconstruction and cancellation are performed; finally, traditional methods are used for SNR estimation. This significantly improves SNR estimation performance under interference conditions and enhances channel quality assessment performance under such conditions.

[0086] Second Embodiment

[0087] This embodiment uses a specific application example to illustrate the implementation process and effects of the method of the present invention.

[0088] Suppose that in a certain OFDM system, the training symbols s(n) used for signal-to-noise ratio estimation have a length of N = 256, consisting of two Zad-off Chu sequences of length 128, and there exists a single-tone interference signal. Therefore, the received signal can be expressed as r(n) = s(n) + s J The jammer-to-signal ratio (JSR) can be expressed as JSR = P(n) + w(n). J / P s In this embodiment, JSR = 5dB, and the normalized frequency offset f J =0.17, initial phase

[0089] The steps for reconstructing and canceling interference in the first iteration using the received signal r(n) are as follows:

[0090] Step 1: For the received preamble r(n), 0≤n≤255, obtain a length of N by padding the data with zeros at the end. FFT =4096 received sequence as follows:

[0091]

[0092] Step 2: Initialize the interference signal frequency set J as an empty set Φ, and the interference-free signal frequency set as Q = {k|0≤k≤4095};

[0093] Step 3: Receive sequence Perform a 4096-point Fast Fourier Transform (FFT) operation to obtain R(k), 0 ≤ k ≤ 4095, and calculate the power spectrum P(k) = |R(k)|. 2 ;

[0094] Step 4: Calculate the average signal power.

[0095]

[0096] The interference signal decision threshold is obtained by taking parameter η = 15.

[0097] Step 5: Compare P(k) with the decision threshold T. If P(k) ≥ T, then it is determined that there is an interference signal at frequency index k, i.e., J = {k|P(k) ≥ T}; at the same time, the frequency set without interference signals can be updated to...

[0098] Step 6: If J is an empty set, then there is no interference signal in the determination, and the signal-to-noise ratio is directly estimated using equations (1) and (2); otherwise, the consecutive k values ​​in set J are merged into a subset, so that J can be written as the union of multiple subsets, such as J = J1∪J2∪...∪J m , where m represents the number of subsets, so it can be determined that there are m single-tone interference signals; in this example, set J consists of continuous k values, so there is no need to partition J into subsets, and it can be determined that there is 1 single-tone interference signal.

[0099] Step 7: Estimate the frequency, amplitude, and phase of all m interference signals detected in Step 6. The specific steps are as follows:

[0100] Step 7.1: Estimate the power of the detected single-tone interference signal.

[0101] Step 7.2: For the detected single-tone interference signal, find the frequency index corresponding to the peak value in the set {P(k)|k∈J}. The normalized frequency estimate of the interference signal is

[0102] Step 7.3: For the l-th interference signal, estimate the phase value of the signal.

[0103] Step 8: Reconstruct and cancel the interference signal based on the parameters estimated in Step 7 to obtain the interference-cancelled signal.

[0104] Step 9: Using the updated received signal r(n), proceed to Step 1 to begin the next iteration of detection. Here we provide an example. Figures 2-4 The correspondence between the power spectrum of the signal and the interference detection threshold during the three iterations is given. In the case shown, the received signal completed the reconstruction and cancellation of the interference signal after three iterations.

[0105] Step 10: Based on the received signal r(n) after interference reconstruction and cancellation, obtain the signal power estimate using equations (1) and (2). and noise power estimates And finally obtain the signal-to-noise ratio.

[0106] Third Embodiment

[0107] This embodiment uses another specific application example to illustrate the implementation process and effects of the method of the present invention.

[0108] Suppose that in an OFDM system, the training symbols s(n) used for signal-to-noise ratio estimation have a length of N = 256, consisting of two Zad-off Chu sequences of length 128. When multi-tone interference is present, the received signal can be expressed as r(n) = s(n) + s J (n)+w(n), where, This represents the power of the l-th single-tone interference signal. The frequency of the l-th monotone interference signal is represented by . The initial phase of the l-th single-tone interference signal. In this embodiment, the number of multi-tone interferences is m=2, and the JSR is 5dB, with normalized frequency offset. initial phase

[0109] The steps for reconstructing and canceling interference in the first iteration using the received signal r(n) are as follows:

[0110] Step 1: For the received preamble r(n), 0≤n≤255, obtain a length of N by padding the data with zeros at the end. FFT =4096 received sequence as follows:

[0111]

[0112] Step 2: Initialize the interference signal frequency set J as an empty set Φ, and the interference-free signal frequency set as Q = {k|0≤k≤4095};

[0113] Step 3: Receive sequence Perform a 4096-point Fast Fourier Transform (FFT) to obtain R(k), 0 ≤ k ≤ 4095, and calculate the power spectrum P(k) = |R(k)|. 2 ;

[0114] Step 4: Calculate the average signal power.

[0115]

[0116] The interference signal decision threshold is obtained by taking parameter η = 15.

[0117] Step 5: Compare P(k) with the decision threshold T. If P(k) ≥ T, then an interference signal is determined to exist at frequency index k, i.e., J = {k | P(k) ≥ T}; simultaneously, the frequency set without interference signals can be updated to...

[0118] Step 6: If J is an empty set, then there is no interference signal in the determination, and the signal-to-noise ratio is directly estimated using equations (1) and (2); otherwise, the continuous k values ​​in set J are merged into a subset, so that J can be written as the union of multiple subsets, such as J = J1∪J2, and thus it can be determined that there are 2 single-tone interference signals.

[0119] Step 7: Estimate the frequency, amplitude, and phase of the two interference signals detected in Step 6. The specific steps are as follows:

[0120] Step 7.1: For the detected interference signals, estimate the power of the l-th (l=1,2) interference signal.

[0121] Step 7.2: For the detected l-th (l=1,2) single-tone interference signal, find the set J respectively. l Frequency index corresponding to mid-peak value The normalized frequency estimate of the interference signal is

[0122] Step 7.3: For the l-th interference signal, estimate the phase value of the signal.

[0123] Step 8: Reconstruct and cancel the interference signal based on the parameters estimated in Step 7 to obtain the interference-cancelled signal.

[0124] Step 9: Using the updated received signal r(n), proceed to Step 1 to begin the next iteration of detection;

[0125] Step 10: Based on the received signal r(n) after interference reconstruction and cancellation, obtain the signal power estimate using equations (1) and (2). and noise power estimates And finally obtain the signal-to-noise ratio.

[0126] Fourth embodiment

[0127] This embodiment provides an electronic device, such as... Figure 7 As shown, the electronic device includes a processor and a memory; wherein the processor and the memory can be connected via a communication bus; the memory stores at least one instruction, which is loaded and executed by the processor to implement the method of the first embodiment described above. Furthermore, the electronic device may also include a transceiver, the processor and the transceiver can be connected via a communication bus, and the transceiver is used to communicate with other devices.

[0128] Below, in conjunction with Figure 7 A detailed introduction to each component of this electronic device is provided below:

[0129] The processor is the control center of the electronic device. The electronic device may include multiple processors, each of which can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). The term "processor" can refer to a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), other general-purpose processors, application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), one or more field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor can perform various functions of the electronic device by running or executing software programs stored in memory and by calling data stored in memory.

[0130] In a specific implementation, as one example, the processor may include one or more CPUs, for example... Figure 7 CPU0 and CPU1 shown are, of course, merely illustrative examples.

[0131] The memory is used to store the software program that executes the solution of the present invention, and the processor controls its execution. For specific implementation methods, please refer to the above method embodiments, which will not be repeated here.

[0132] Optionally, the memory may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or 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 not limited thereto. The memory may be integrated with the processor or may exist independently, and may be accessed through the interface circuit of the electronic device (…). Figure 7 (Not shown in the image) is coupled to the processor; however, this embodiment of the invention does not impose specific limitations on this.

[0133] The transceiver may include a receiver and a transmitter. Figure 7 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the transmitting function. The transceiver can be integrated with the processor or exist independently, and is connected through the interface circuit of the electronic device (…). Figure 7 (Not shown in the image) is coupled to the processor, and this embodiment of the invention does not specifically limit this.

[0134] In addition, it should be noted that, Figure 7 The structure of the electronic device shown is not intended to limit the device. Actual devices may include more or fewer components than shown, or combine certain components, or have different component arrangements. Furthermore, the technical effects achieved by this electronic device when performing the method of the first embodiment described above can be referenced to the technical effects described in the first embodiment; therefore, they will not be repeated here.

[0135] Fifth embodiment

[0136] This embodiment provides a computer-readable storage medium storing at least one instruction, which is loaded and executed by a processor to implement the method of the first embodiment described above. The computer-readable storage medium may be a ROM, random access memory, CD-ROM, magnetic tape, floppy disk, or optical data storage device, etc. The instruction stored therein can be loaded and executed by a processor in a terminal.

[0137] Furthermore, it should be noted that the present invention can be provided as a method, apparatus, or computer program product. Therefore, embodiments of the present invention can take the form of a completely or partially hardware embodiment, a completely or partially software embodiment, or an embodiment combining software and hardware aspects. Moreover, when implemented in software, embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any usable medium accessible to a computer or a data storage device such as a server or data center containing one or more sets of usable media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive (SSD).

[0138] Embodiments of the present invention are described with reference to flowchart illustrations and / or block diagrams of methods, terminal devices (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, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0139] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing terminal device to operate 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 1The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing terminal equipment to cause a series of operational steps to be performed on the computer or other programmable terminal equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable terminal 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.

[0140] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or terminal device. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or terminal device that includes said element. Furthermore, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone, where A and B can be singular or plural. Additionally, the character " / " in this text generally indicates an "or" relationship between the preceding and following objects, but it can also indicate an "AND / OR" relationship. Please refer to the context for specific interpretations. "At least one" refers to one or more items, while "more than" refers to two or more items. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or multiple items. For example, at least one of a, b, or c can be represented as: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0141] Furthermore, it is understood that in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0142] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0143] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of functional modules / units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be through some interfaces; indirect couplings or communication connections between devices or units may be electrical, mechanical, or other forms. Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs. Additionally, the functional units in the various embodiments of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0144] If the method is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0145] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention. It should be pointed out that although preferred embodiments of the present invention have been described, those skilled in the art, once they understand the basic inventive concept of the present invention, can make several improvements and modifications without departing from the principles described herein. These improvements and modifications should also be considered within the scope of protection of the present invention. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

Claims

1. A signal-to-noise ratio estimation method based on interference reconstruction and cancellation, characterized in that, include: S1, perform interference detection on the signal to be detected to determine whether there is interference in the current signal; S2, If no interference signal is detected in the current signal, the signal-to-noise ratio is directly estimated; S3, if interference is detected in the current signal, the interference is reconstructed and canceled to obtain the signal after interference elimination. The signal after interference elimination is used as the signal to be detected. S1 is executed again until interference is detected in the current signal. Then the signal-to-noise ratio is estimated to obtain the signal-to-noise ratio estimation result. The interference detection of the signal to be detected, to determine whether there is interference in the current signal, includes: End the data of the signal r(n) to be detected, where 0 ≤ n ≤ N-1, with zeros padded to the end, and N represents the length of the signal to be detected; thus obtaining a new length of N. FFT Received sequence Right now: Initialize the interference signal frequency set J as an empty set Φ, and the interference-free signal frequency set Q = {k | 0 ≤ k ≤ N}. FFT -1}; where k represents the frequency index; right As N FFT Point Fast Fourier Transform operation yields R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k)=|R(k)| 2 ; where N FFT express Length; Determine the interference signal decision threshold T; Compare P(k) with the interference signal decision threshold T. If P(k) ≥ T, then an interference signal is determined to exist at frequency index k. In this case, J is updated to J = {k | P(k) ≥ T}; simultaneously, Q is updated to Q = {k | 0 ≤ k ≤ N}. FFT -1 and After determining whether there is an interference signal at each frequency index, it is determined whether J is an empty set. If J is an empty set, it is determined that there is no interference signal in the signal to be detected; otherwise, it is determined that there is an interference signal in the signal to be detected. The determination of the interference signal decision threshold T includes: Calculate the average power of the signal The formula is as follows: Where |Q| represents the number of elements in Q; Based on average power Obtain the interference signal decision threshold Where η is a preset value greater than 1; If interference is detected in the current signal, interference reconstruction and cancellation are performed, including: If interference is detected in the current signal, consecutive k values ​​in J are merged into a subset, thus J is written as the union of multiple subsets, i.e., J = J1∪J2∪…∪J m ; among which, J l Let l represent the l-th subset, l = 1, 2, 3, ..., m; m represents the number of subsets. The k value in each subset represents the frequency index corresponding to a single-tone interference signal, that is, the number of single-tone interference signals is m. For each single-tone interference signal, the interference signal parameters are estimated separately. Based on the estimated interference signal parameters, the interference signal is reconstructed and the interference is canceled. The step of estimating the interference signal parameters for each single-tone interference signal includes: For the l-th single-tone interference signal, its energy estimate is... Then the power estimate corresponding to the l-th single-tone interference signal Among them, J l Let l represent the l-th subset, 1≤l≤m; For the l-th single-tone interference signal, find the set {P(k)|k∈J}. l Frequency index corresponding to the peak value in} Then the frequency estimate corresponding to the l-th single-tone interference signal For the l-th single-tone interference signal, its corresponding phase estimate value in, express The corresponding Fast Fourier Transform result; The interference signal reconstruction and cancellation are performed based on the estimated interference signal parameters, using the following formula: Where r(n)′ represents the signal after interference is eliminated; r(n) represents the signal to be detected; n=0,1,2,…,N-1.

2. The signal-to-noise ratio estimation method based on interference reconstruction and cancellation as described in claim 1, characterized in that, The signal-to-noise ratio estimation includes: A signal-to-noise ratio (SNR) estimation algorithm based on the preamble symbol is used to estimate the SNR of the current signal, resulting in an estimated signal power value. and noise power estimates And finally obtain the signal-to-noise ratio.

Images