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

Abstract

The invention discloses a signal-to-noise ratio estimation method based on interference reconstruction and cancellation, which belongs to the technical field of wireless communication, and comprises the following steps: S1, carrying out interference detection on a signal to be detected, and determining whether an interference signal exists in a current signal or not; s2, if it is detected that no interference signal exists in the current signal, signal-to-noise ratio estimation is directly carried out on the current signal; and S3, if the current signal is detected to have an interference signal, performing interference reconstruction and cancellation on the current signal to obtain a signal after interference elimination, taking the signal after interference elimination as a signal to be detected, executing S1 again until the current signal is detected to have no interference signal, and performing signal-to-noise ratio estimation on the current signal to obtain a signal-to-noise ratio estimation result. According to the invention, high-precision signal-to-noise ratio estimation under the interference condition can be realized, and the channel quality evaluation performance under the interference condition is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless communications, and in particular to a signal-to-noise ratio estimation method based on interference reconstruction and cancellation. Background Art

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

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

[0004] In actual OFDM wireless communication systems, the signal-to-noise ratio estimation algorithm based on the preamble symbol is a widely used method. An OFDM symbol with a repetitive structure is used as the preamble symbol, that is, 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 the additive white Gaussian noise (AWGN) channel, the received signal can be expressed as r(n) = s(n) + w(n), where w(k) represents 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] Among them, 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] So the signal-to-noise ratio estimate can be obtained as

[0009] The above method can obtain good signal-to-noise ratio estimation performance in both AWGN channels and fading channels, but the signal-to-noise ratio estimation performance will deteriorate sharply when there are interference signals in the channel. This will lead to the failure of traditional adaptive coding modulation, channel decoding and other mechanisms under interference conditions. Summary of the invention

[0010] The present invention provides a signal-to-noise ratio estimation method based on interference reconstruction and cancellation to solve the technical problem that the signal-to-noise ratio estimation performance of a traditional signal-to-noise ratio estimation algorithm cannot meet the requirements when an interference signal exists in a channel.

[0011] In order to solve the above technical problems, the present invention provides the following technical solutions:

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

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

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

[0015] S3, if it is detected that the current signal has an interference signal, then perform interference reconstruction and cancellation on it to obtain a signal after the interference is eliminated, and use the signal after the interference is eliminated as the signal to be detected, and execute S1 again until it is detected that the current signal does not have an interference signal, and then estimate the signal-to-noise ratio to obtain a signal-to-noise ratio estimation result.

[0016] Further, the interference detection is performed on the signal to be detected to determine whether there is an interference signal in the current signal, including:

[0017] Pad zeros at the end of the data of the signal to be detected r(n), 0≤n≤N-1 to a length of N FFT , N represents the length of the signal to be detected; the new length is N FFT The receiving sequence Right now:

[0018]

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

[0020] right Make N FFT Point fast Fourier transform operation, get R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k) = |R(k)| 2 ; Among them, 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, it is determined that there is an interference signal at frequency index k. At this time, J is updated to J = {k|P(k) ≥ T}. At the same time, Q is updated to

[0023] 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, determine that there is no interference signal in the signal to be detected; otherwise, determine that there is an interference signal in the signal to be detected.

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

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

[0026]

[0027] Among them, |Q| represents the number of elements in Q;

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

[0029] Furthermore, if it is detected that the current signal has an interference signal, interference reconstruction and cancellation are performed on it, including:

[0030] If an interference signal is detected in the current signal, the continuous k values ​​in J are merged into a subset, so that J is written as the union of multiple subsets, that is, J = J1∪J2∪…∪J m Among them, J l represents the lth subset, l = 1, 2, 3, ..., m; m represents the number of subsets, and 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] Estimating interference signal parameters for each single-tone interference signal;

[0032] According to 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] Further, the estimating interference signal parameters for each single-tone interference signal includes:

[0035] For the lth single-tone interference signal, its energy estimation value is Then the power estimation value corresponding to the lth single-tone interference signal is Among them, J l represents the lth subset, 1≤l≤m;

[0036] For the lth single-tone interference signal, find the set {P(k)|k∈J l}The frequency index corresponding to the peak Then the frequency estimate corresponding to the lth single-tone interference signal is

[0037] For the lth single-tone interference signal, the corresponding phase estimate is in, express The corresponding fast Fourier transform operation result.

[0038] Furthermore, the interference signal reconstruction and interference cancellation are performed according to the estimated interference signal parameters, and the formula is:

[0039]

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

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

[0042] The signal-to-noise ratio estimation algorithm based on the leading symbol is used to estimate the signal-to-noise ratio of the current signal to obtain the signal power estimation value. and noise power estimate And finally get the signal-to-noise ratio

[0043] On the other hand, the present invention further provides an electronic device, comprising a processor and a memory; wherein the memory stores at least one instruction, and the instruction is loaded and executed by the processor to implement the above method.

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

[0045] The beneficial effects brought about by the technical solution provided by the present invention include at least:

[0046] The present invention aims at the problem of signal-to-noise ratio estimation in OFDM system under single-tone and multi-tone interference conditions, and provides a signal-to-noise ratio estimation method based on interference reconstruction and cancellation. The method first estimates interference signal parameters, then performs interference reconstruction and interference cancellation, and finally uses the traditional method to estimate the signal-to-noise ratio, which can significantly improve the signal-to-noise ratio estimation performance under interference conditions, thereby improving the channel quality assessment performance under interference conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0048] Figure 1 It is a flow chart of a signal-to-noise ratio estimation method based on interference reconstruction and cancellation provided by the present invention;

[0049] Figure 2 is the power spectrum and interference detection threshold during the first iterative detection provided by the second embodiment of the present invention;

[0050] Figure 3 is the power spectrum and interference detection threshold during the second iterative detection provided by the second embodiment of the present invention;

[0051] Figure 4 is the power spectrum and interference detection threshold during the third iterative detection provided by the second embodiment of the present invention;

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

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

[0054] Figure 7 It is a system block diagram of an electronic device provided by a fourth embodiment of the present invention. DETAILED DESCRIPTION

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

[0056] First of all, it should be noted that in the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "exemplarily" is intended to present the concept in a concrete way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0057] First embodiment

[0058] In view of the problem of signal-to-noise ratio estimation in the presence of single-tone or multi-tone interference in an OFDM system, this embodiment provides a signal-to-noise ratio estimation method based on interference reconstruction and cancellation, and its execution process is as follows: Figure 1 As shown, the iterative detection and elimination method is first used to accurately estimate the amplitude, frequency, phase and other parameters of the interference signal, then reconstruct the interference signal and perform interference cancellation, and finally perform signal-to-noise ratio estimation based on the traditional method. This effectively solves the problem of OFDM system signal-to-noise ratio estimation under single-tone and multi-tone interference conditions. The method can be implemented by an electronic device, which can be a terminal or a server. It includes the following steps:

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

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

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

[0062]

[0063] Among them, N FFT is a preset value; N represents the length of the signal to be detected;

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

[0065] S13, for receiving sequence Make N FFT The point fast Fourier transform (FFT) operation is performed to obtain R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k) = |R(k)| 2 ;

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

[0067] S141, calculate the average signal power The formula is as follows:

[0068]

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

[0070] S142, obtain the interference signal decision threshold Among them, η>1.

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

[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, and S2 is executed at this time. The signal-to-noise ratio can be directly estimated using equations (1) and (2); otherwise, it is determined that there is an interference signal in the signal, and S3 is executed at this time.

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

[0074] S3, if it is detected that the current signal has an interference signal, then reconstruct and cancel the interference to obtain a signal after the interference is eliminated, and use the signal after the interference is eliminated as the signal to be detected, and execute S1 again until it is detected that the current signal does not have an interference signal, and estimate the signal-to-noise ratio to obtain a signal-to-noise ratio estimation result;

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

[0076] S31, merge the consecutive k values ​​in set J into a subset, so that J can be written as the union of multiple subsets, that is, J = J1∪J2∪…∪J m Among them, J l represents the lth subset, l = 1, 2, 3, ..., m; m represents the number of subsets, and the k value in each subset represents the frequency index corresponding to a single-tone interference signal, so it can be determined that there are currently m single-tone interference signals;

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

[0078] For the lth (1≤l≤m) interference signal, its energy estimation value is Then the power estimation value corresponding to the lth interference signal is Among them, J l represents the lth subset, 1≤l≤m;

[0079] For the lth interference signal, find the set {P(k)|k∈J l}The frequency index corresponding to the peak Then the frequency estimate corresponding to the lth interference signal is

[0080] For the lth interference signal, the corresponding phase estimate is in, express The corresponding fast Fourier transform operation result.

[0081] S33, performing interference signal reconstruction and interference cancellation according to the estimated interference signal parameters, the formula is:

[0082]

[0083] S34, using the updated received signal r(n), go to S1 to re-detect and estimate the interference signal until the interference signal is completely eliminated; in this way, an iterative interference detection and suppression method can be used to obtain a 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 the interference reconstruction and cancellation are completed, the signal power estimation value is obtained using equations (1) and (2): and noise power estimate And finally get the signal-to-noise ratio

[0085] In summary, for the problem of signal-to-noise ratio estimation in OFDM systems under single-tone and multi-tone interference conditions, this embodiment provides a signal-to-noise ratio estimation method based on interference reconstruction and cancellation, which first estimates interference signal parameters, then performs interference reconstruction and interference cancellation, and finally uses traditional methods to estimate the signal-to-noise ratio, which can significantly improve the signal-to-noise ratio estimation performance under interference conditions. Improve the channel quality assessment performance under interference conditions.

[0086] Second embodiment

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

[0088] Assume that in an OFDM system, the training symbol s(n) used for signal-to-noise ratio estimation has a length of N=256, consists of two Zad-off Chu sequences of length 128, and there is a single-tone interference signal The received signal can then be expressed as r(n)=s(n)+s J (n)+w(n), the jammer to signal ratio (JSR) can be expressed as JSR=P J / P s In this embodiment, JSR = 5dB, the normalized frequency deviation f J =0.17, initial phase

[0089] Using the received signal r(n), the steps for implementing interference reconstruction and cancellation in the first iteration are as follows:

[0090] Step 1: For the received leading symbol r(n), 0≤n≤255, fill the end of the data with zeros to obtain a length of N. FFT =4096 receiving sequence as follows:

[0091]

[0092] Step 2: Initialize the interference signal frequency set J to be an empty set Φ, and the non-interference signal frequency set to be 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] And take parameter η = 15 to get the interference signal decision threshold

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

[0098] Step 6: If J is an empty set, it is determined that there is no interference signal, and the signal-to-noise ratio is estimated directly 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∪...∪J m , where m represents the number of subsets, so it can be determined that there are currently m single-tone interference signals; in this example, the set J is composed of continuous k values, and there is no need to divide J into subsets, and it is determined that there is currently 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: For the detected single-tone interference signal, estimate the interference signal power as

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

[0102] Step 7.3: For the lth interference signal, estimate the phase value of the signal

[0103] Step 8: Reconstruct the interference signal and cancel the interference according to the parameters estimated in step 7, and obtain the signal after interference cancellation:

[0104] Step 9: Using the updated received signal r(n), go to step 1 to start the next iterative detection. Here we give an example. Figure 2 to Figure 4 The corresponding relationship between the signal power spectrum and the interference detection threshold during the three iterations is given. The received signal of the case shown completes 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, use equations (1) and (2) to obtain the signal power estimate: and noise power estimate And finally get the signal-to-noise ratio

[0106] Third embodiment

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

[0108] Assume that in an OFDM system, the training symbol s(n) used for signal-to-noise ratio estimation has a length of N=256 and is composed of two Zad-off Chu sequences of length 128. When there is a multi-tone interference signal, the received signal can be expressed as r(n)=s(n)+s J (n)+w(n), where represents the power of the lth single-tone interference signal, represents the frequency of the lth single-tone interference signal, The initial phase of the lth single-tone interference signal. In this embodiment, the number of multi-tone interference is m=2, and the JSR is 5dB. The normalized frequency deviation Initial Phase

[0109] Using the received signal r(n), the steps for implementing interference reconstruction and cancellation in the first iteration are as follows:

[0110] Step 1: For the received leading symbol r(n), 0≤n≤255, fill the end of the data with zeros to obtain a length of N. FFT =4096 receiving sequence as follows:

[0111]

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

[0113] 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 ;

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

[0115]

[0116] And take parameter η = 15 to get the interference signal decision threshold

[0117] Step 5: Compare P(k) and the decision threshold T. If P(k) ≥ T, it is determined that there is an interference signal at the frequency index k, that is, J = {k|P(k) ≥ T}; at the same time, the frequency set without interference signal can be updated as

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

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

[0122] Step 7.3: For the lth interference signal, estimate the phase value of the signal

[0123] Step 8: Reconstruct the interference signal and cancel the interference according to the parameters estimated in step 7, and obtain the signal after interference cancellation:

[0124] Step 9: Using the updated received signal r(n), go to step 1 to start the next iterative detection;

[0125] Step 10: Based on the received signal r(n) after interference reconstruction and cancellation, use equations (1) and (2) to obtain the signal power estimate: and noise power estimate And finally get 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, and the instruction is loaded and executed by the processor to implement the method of the first embodiment. In addition, 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] Next, combine Figure 7 The following is a detailed introduction to the various components of the electronic device:

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

[0130] In a specific implementation, as an embodiment, the processor may include one or more CPUs, such as Figure 7 The CPU0 and CPU1 shown in the figure are, of course, only exemplary.

[0131] The memory is used to store the software program for executing the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can refer to the above method embodiment and will not be repeated here.

[0132] Optionally, the memory may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory may be integrated with the processor or exist independently and accessed through the interface circuit ( Figure 7 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0133] The transceiver may include a receiver and a transmitter ( Figure 7 The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function. The transceiver can be integrated with the processor or exist independently and communicate with the electronic device through the interface circuit ( Figure 7 (not shown) is coupled to the processor, which is not specifically limited in this embodiment of the present invention.

[0134] In addition, it should be noted that Figure 7 The structure of the electronic device shown in the figure does not constitute a limitation on the device, and the actual device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In addition, the technical effects achieved by the electronic device when executing the method of the first embodiment above can refer to the technical effects described in the first embodiment above, so they are not repeated here.

[0135] Fifth embodiment

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

[0137] In addition, it should be noted that the present invention can be provided as a method, an apparatus or a computer program product. Therefore, the embodiment of the present invention can be in the form of a full or partial hardware embodiment, a full or partial software embodiment or an embodiment combining software and hardware. Moreover, when implemented using software, the embodiment of the present invention can be in the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center containing one or more available media sets. The available medium may be a magnetic medium (eg, a floppy disk, a hard disk, a magnetic tape), an optical medium (eg, a DVD), or a semiconductor medium. The semiconductor medium may be a solid state hard disk.

[0138] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0139] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable terminal device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0140] It should also be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. The terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements. In addition, the term "and / or" is only an association relationship describing the associated objects, indicating that there can be three relationships, for example, A and / or B, which can represent: A exists alone, A and B exist at the same time, and B exists alone, wherein A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding. "At least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can be represented by: a, b, c, ab, ac, bc or abc, where a, b, c can be single or plural.

[0141] In addition, it can be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean 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 appreciate that the units and algorithm steps of each example 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 performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0143] In several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of functional modules / units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point, the coupling or direct coupling or communication connection between each other shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or it may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0144] If the method is implemented in the form of 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 the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0145] Finally, it should be noted that the above is only a preferred embodiment of the present invention. It should be pointed out that although the preferred embodiment of the present invention has been described, for ordinary technicians in this technical field, once the basic creative concept of the present invention is known, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as the protection scope of the present invention. Therefore, the attached claims are intended to be interpreted as including the preferred embodiment and all changes and modifications that fall 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, performing interference detection on the signal to be detected to determine whether there is an interference signal on the current signal; S2, if it is detected that there is no interference signal in the current signal, the signal-to-noise ratio is directly estimated; S3, if it is detected that the current signal has an interference signal, then reconstruct and cancel the interference to obtain a signal after the interference is eliminated, and use the signal after the interference is eliminated as the signal to be detected, and execute S1 again until it is detected that the current signal does not have an interference signal, and then estimate the signal-to-noise ratio to obtain a signal-to-noise ratio estimation result.

2. The method for estimating a signal-to-noise ratio based on interference reconstruction and cancellation according to claim 1, characterized in that: The interference detection of the signal to be detected to determine whether there is an interference signal in the current signal includes: Add zeros to the end of the data of the signal to be detected r(n), 0≤n≤N-1, where N represents the length of the signal to be detected; the new length is N FFT The receiving sequence Right now: Initialize the interference signal frequency set J to an empty set Φ, and the non-interference signal frequency set Q = {k|0≤k≤N FFT -1}; where k represents the frequency index; right Make N FFT Point fast Fourier transform operation, get R(k), 0≤k≤N FFT -1, and calculate the power spectrum P(k) = |R(k)| 2 ; Among them, 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, it is determined that there is an interference signal at frequency index k. At this time, J is updated to J = {k|P(k) ≥ T}. At the same time, Q is updated to 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, determine that there is no interference signal in the signal to be detected; otherwise, determine that there is an interference signal in the signal to be detected.

3. The signal-to-noise ratio estimation method based on interference reconstruction and cancellation as claimed in claim 2, characterized in that: The determining of the interference signal decision threshold T comprises: Calculate the average power of the signal The formula is as follows: Among them, |Q| represents the number of elements in Q; Based on average power Get the interference signal decision threshold Wherein, η is a preset value greater than 1.

4. The method for estimating a signal-to-noise ratio based on interference reconstruction and cancellation according to claim 2, characterized in that: If it is detected that there is an interference signal in the current signal, then interference reconstruction and cancellation are performed on it, including: If an interference signal is detected in the current signal, the continuous k values ​​in J are merged into a subset, so that J is written as the union of multiple subsets, that is, J = J1∪J2∪…∪J m Among them, J l represents the lth subset, l = 1, 2, 3, ..., m; m represents the number of subsets, and 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; Estimating interference signal parameters for each single-tone interference signal; According to the estimated interference signal parameters, interference signal reconstruction and interference cancellation are performed.

5. The method for estimating a signal-to-noise ratio based on interference reconstruction and cancellation according to claim 4, characterized in that: The interference signal parameters include: interference signal power, interference signal frequency and interference signal phase.

6. The method for estimating a signal-to-noise ratio based on interference reconstruction and cancellation according to claim 5, characterized in that: The step of estimating interference signal parameters for each single-tone interference signal comprises: For the lth single-tone interference signal, its energy estimation value is Then the power estimation value corresponding to the lth single-tone interference signal is Among them, J l represents the lth subset, 1≤l≤m; For the lth single-tone interference signal, find the set {P(k)|k∈J l }The frequency index corresponding to the peak Then the frequency estimate corresponding to the lth single-tone interference signal is For the lth single-tone interference signal, the corresponding phase estimate is in, express The corresponding fast Fourier transform operation result.

7. The signal-to-noise ratio estimation method based on interference reconstruction and cancellation according to claim 6, characterized in that: The interference signal reconstruction and interference cancellation are performed according to the estimated interference signal parameters, and the formula is: Wherein, r(n)′ represents the signal after interference elimination; r(n) represents the signal to be detected; n=0, 1, 2,…, N-1.

8. The signal-to-noise ratio estimation method based on interference reconstruction and cancellation according to any one of claims 1 to 7, characterized in that: The signal-to-noise ratio estimation comprises: The signal-to-noise ratio estimation algorithm based on the leading symbol is used to estimate the signal-to-noise ratio of the current signal to obtain the signal power estimation value. and noise power estimate And finally get the signal-to-noise ratio

Images