WO2023246079A1 - Prach peak detection method, base station, communication system, and medium - Google Patents

Abstract

Embodiments of the present disclosure provide a PRACH peak detection method, a base station, a communication system, and a medium. The detection method is applied to the base station and comprises: acquiring and receiving a PRACH signal and generating a frequency domain power spectrum; acquiring network management configuration data of the base station, setting a first noise threshold, and setting a second noise threshold according to the first noise threshold; screening a second power sequence from the frequency domain power spectrum, and calculating second temporary noise according to the second power sequence; screening a second frequency domain power spectrum from the frequency domain power spectrum, and acquiring a difference between the second frequency domain power spectrum and the second temporary noise; determining whether the difference meets a preset noise confidence threshold, taking a power value which does not meet the noise confidence threshold in the frequency domain power spectrum as a third power sequence, and calculating average noise power; and setting a target peak detection threshold according to the average noise power and false alarm threshold information, and performing peak detection on the frequency domain power spectrum according to the target peak detection threshold.

Description

PRACH peak detection method, base station, communication system and medium

Cross-references to related applications

This disclosure claims priority to Chinese patent application CN202210711565.5 titled "Peak detection method, base station, communication system and medium for PRACH" submitted on June 22, 2022, the entire content of which is incorporated into this disclosure by reference.

Technical field

The present disclosure relates to the field of communication technology, and in particular, to a PRACH peak detection method, a base station, a communication system and a medium.

Background technique

With the development of mobile communication technology, many existing applications have high requirements for wireless connections and uplink synchronization, including smart homes, telemedicine and other tasks. As a key step in establishing wireless connections, the Physical Random Access Channel (PRACH) has attracted much attention. The access preamble peak detection algorithm in random access channels has always been a hot issue in wireless communications. Research on peak detection algorithms mainly includes setting detection thresholds and improving the effectiveness of detection algorithms in different scenarios.

In PRACH peak detection, the traditional random access peak detection algorithm usually uses the threshold judgment method. However, when the relevant peak energy leaks, it will affect other normal signals with small energy. If only the conventional threshold judgment method is used, it will Cause misjudgments, "false alarms" and "missed detections". For example, when multiple terminal devices initiate access on the same time slot, multiple terminal devices will use random access generated by the same or adjacent physical root sequences. Enter the preamble sequence. At this time, the autocorrelation peak of each ZC (Zadoff-chu) sequence in the time domain will leak to other sequences. Considering that the power of the terminal equipment is inconsistent, there is a gap in the peak energy of the receiving end, and the peak energy of some terminal equipment leaks. This will lead to an increase in the noise threshold. Using conventional noise estimation methods will cause "false alarms" or "missed detections" on peak signals near the noise threshold, ultimately affecting the success rate of terminal device access.

Contents of the invention

The main purpose of the embodiments of the present disclosure is to provide a PRACH peak detection method, base station, communication system and medium, aiming to improve the success rate of terminals accessing the base station through the physical random access channel.

Embodiments of the present disclosure provide a PRACH peak detection method, which is applied to a base station. The method includes:

Obtain the received PRACH signal and generate a frequency domain power spectrum according to the PRACH signal;

Obtain the network management configuration data of the base station, set a first noise threshold according to the network management configuration data and the frequency domain power spectrum, and set a second noise threshold according to the first noise threshold and the network management configuration data;

Filter out a second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum, and calculate a second temporary noise based on the second power sequence;

Filter out a second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum, and obtain the difference between the second frequency domain power spectrum and the second temporary noise;

Determine whether the difference meets a preset noise confidence threshold, and use the power value in the frequency domain power spectrum that does not meet the noise confidence threshold as a third power sequence, and according to the third power sequence and the The second power sequence calculates the average noise power;

A target peak detection threshold is set according to the average noise power and the false alarm threshold information, and peak detection is performed on the frequency domain power spectrum according to the target peak detection threshold.

Embodiments of the present disclosure also provide a base station, which includes a processor, a memory, a computer program stored on the memory and executable by the processor, and a computer program configured to implement communication between the processor and the memory. A data bus is connected to the communication, and when the computer program is executed by the processor, the peak detection method of PRACH according to any embodiment of the present disclosure is implemented.

An embodiment of the present disclosure also provides a wireless communication system, which at least includes the aforementioned base station.

Embodiments of the present disclosure also provide a storage medium for computer-readable storage. The storage medium stores one or more programs. The one or more programs can be executed by one or more processors to implement the following: The steps of any PRACH peak detection method provided in any embodiment of this disclosure.

Description of the drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are some embodiments of the present disclosure, which are of great significance to this field. Ordinary technicians can also obtain other drawings based on these drawings without exerting creative work.

Figure 1 is a schematic structural diagram of a wireless communication system provided by an embodiment of the present disclosure;

Figure 2 is a schematic flow chart of a PRACH peak detection method provided by an embodiment of the present disclosure;

Figure 3 is a schematic structural block diagram of a base station provided by an embodiment of the present disclosure.

Detailed ways

The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, rather than all of the embodiments. Based on the embodiments in this disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this disclosure.

The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all contents and operations/steps, nor are they necessarily performed in the order described. For example, some operations/steps can also be decomposed, combined or partially merged, so the actual order of execution may change according to actual conditions.

The terminology used in this disclosure is for the purpose of describing particular embodiments only and is not intended to limit the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms unless the context clearly dictates otherwise.

In 5G communication, PRACH (physical layer random access) is an important communication process of 5G. Specifically, in 5G communication, through PRACH, the terminal device can establish correct communication with the base station. The terminal device sends messages to the base station through the PRACH channel. PRACH signal. After receiving the PRACH signal, the base station determines whether the PRACH signal has preamble sequence information, and determines the location of the terminal device based on the index of the preamble sequence information. In 5G communications, PRACH transmits the ZC sequence, which has strong autocorrelation.

Commonly used algorithms use correlation peaks to determine whether preamble sequence information is sent, and use cyclically shifted ZC sequences to achieve the purpose of distinguishing different users. Therefore, the judgment of correlation peaks is crucial in the PRACH receiving end processing flow. A commonly used algorithm is to set an appropriate threshold. If the peak value is greater than the threshold, it is judged that there is leader sequence information. However, peak judgment is a very rigorous process, and unreasonable or imperfect threshold settings can lead to misjudgments. When the noise in the environment is relatively high, the correlation between the noise signal and the local sequence will also produce some larger correlation signals. If the judgment method is relatively single, it will cause misjudgment and false alarms. For example, when multiple terminal devices initiate access on the same time slot, multiple terminal devices will use random access preamble sequences generated by the same or adjacent physical root sequences. At this time, each ZC (Zadoff -chu) The peak value of sequence autocorrelation will leak to other sequences. Considering that the power of terminal equipment is inconsistent and there is a gap in the peak energy of the receiving end, the peak leakage of some terminal equipment will cause the noise threshold to be raised. The use of conventional noise estimation methods will cause the processing Peak signals near the noise threshold will cause "false alarms" or "missed detections", which ultimately affects the success rate of terminal device access.

Based on this, embodiments of the present disclosure provide a PRACH peak detection method, a base station, a communication system and a medium. The PRACH peak detection method is applied to the base station, aiming to improve the success of terminals accessing the base station through physical random access channels. Rate.

Some embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. The following embodiments and features in the embodiments may be combined with each other without conflict.

Please refer to FIG. 1 , which is a schematic diagram of an application scenario of the PRACH peak detection method provided by the present disclosure.

As shown in Figure 1, the wireless communication system 100 includes a base station 10 and a terminal device 20. When the terminal device 20 enters the coverage of the base station 10 for the first time or wants to establish a communication connection with the base station 20, it receives a broadcast notification issued by the base station 10. The terminal device 20 sends a PRACH signal to the base station 10 in response to the broadcast notification of the base station 10 . The base station 10 receives the PRACH signal sent by the terminal device 20 through the antenna provided on the base station 10, and preprocesses the received PRACH signal to obtain corresponding frequency domain data, and stores it in a preset storage area. The base station 10 obtains the corresponding frequency domain data from the preset storage area according to the preset data processing logic, and correlates the frequency domain data with the local ZC sequence of the base station 10 to obtain the frequency domain power spectrum, also called the energy map PDP, and then obtains the frequency domain power spectrum according to the frequency Perform two noise estimates on the domain power spectrum, and set the noise confidence threshold to filter the leakage of relevant peak energy, eliminate image interference, achieve accurate noise power calculation, determine the final peak detection threshold, and search for relevant peaks to determine whether there is a random access request. , detect the random preamble sequence information sent by the terminal device, that is, the preamble ID (Identity document, identity identification number) of the terminal device and the time offset TA to determine the uplink, thereby reducing "false alarms" and "missed detections" ”, improving the success rate of terminal equipment 20 accessing base station 10.

Please refer to Figure 2. Figure 2 is a step flow chart of a PRACH peak detection method provided by the present disclosure.

As shown in Figure 2, the peak detection method of PRACH includes steps S1 to S6.

Step S1: Obtain the received PRACH signal, and generate a frequency domain power spectrum based on the PRACH signal.

For example, in the 5G wireless communication system, since the sampling rate of the PRACH signal is different from that of the system, after receiving the PRACH signal, the PRACH signal needs to be preprocessed to obtain the relevant frequency domain power spectrum, also called the energy map. , and then determine whether there is a relevant peak based on the frequency domain power spectrum.

In some embodiments, generating a frequency domain power spectrum according to the PRACH signal includes:

Preprocess the received PRACH signal to obtain the PRACH signal in the time domain;

Perform FFT transformation of the PRACH signal in the time domain to the frequency domain to obtain PRACH frequency domain data corresponding to the PRACH signal;

The frequency domain power spectrum is generated according to the PRACH frequency domain data and a preset frequency domain sequence.

For example, CP (Cyclic Prefix) in communications is a solution proposed in OFDM (Orthogonal Frequency Division Multiplexing, orthogonal frequency division multiplexing technology) to combat the interference of multipath delayed signals. CP's The specific implementation method is to copy the last part of the OFDM symbol with a duration of Tc to the start time of the previous guard band for transmission. After the introduction of CP, the energy of the multipath delay signal and the direct signal are orthogonal, and the co-channel interference within the symbol caused by the multipath delay signal is eliminated. When the terminal equipment transmits the PRACH signal, the base station usually introduces the CP. When receiving the PRACH signal, it is necessary to perform CP processing and then sampling processing to obtain the PRACH signal in the time domain, and then perform FFT (Fast Fourier Transformation, Fast Fourier Transform) on the obtained PRACH signal in the time domain to the frequency domain. , obtain the PRACH frequency domain data corresponding to the PRACH signal, and multiply the PRACH frequency domain data with the frequency domain sequence preset locally by the base station to obtain the frequency domain power spectrum.

Step S2: Obtain the network management configuration data of the base station, set a first noise threshold according to the network management configuration data and the frequency domain power spectrum, and set a second noise according to the first noise threshold and the network management configuration data. Threshold.

Exemplarily, the network management configuration data is pre-configured data. The pre-configuration data can be set through experimental simulation or experience. The network management configuration data and related spectrum data in the frequency domain power spectrum are used to set the first noise threshold to initially Filter out part of the data in the frequency domain power spectrum, then set the second noise threshold based on the first noise threshold and network management configuration data, and use the second noise threshold to perform a more accurate filtering of the spectrum data in the frequency domain power spectrum, so as to Obtain more accurate spectrum data from the frequency domain power spectrum.

In some implementations, setting the first noise threshold according to the network management configuration data and the frequency domain power spectrum includes:

Obtain the first noise threshold factor according to the network management configuration data, and obtain the power maximum value from the frequency domain power spectrum;

The first noise threshold is set according to the power maximum value and the first noise threshold factor.

For example, the first noise threshold factor α is a preset value. For example, the first noise threshold factor is an empirical value through simulation or testing. After FFT transformation to the frequency domain, the PRACH frequency domain data corresponding to the PRACH signal is obtained as z(n), The maximum power value filtered out from the frequency domain power spectrum is max{z(n)}, then the first noise threshold is αmax{z(n)}.

In some implementations, setting the second noise threshold according to the first noise threshold and the network management configuration data includes:

Screen out a first power sequence smaller than the first noise threshold from the frequency power spectrum according to the first noise threshold, and calculate a first temporary noise according to the first power sequence;

Obtain a second noise threshold factor and false alarm threshold information according to the network management configuration data, and set the second noise threshold according to the first temporary noise, the second noise threshold factor and the false alarm threshold information.

Exemplarily, the second noise threshold factor and the false alarm threshold information are both preset values. For example, the second noise threshold factor and the false alarm threshold information are both empirical values through simulation or testing. After determining that the first noise threshold is αmax After {z(n)}, the first power sequence n ₁ (n) satisfies the following conditions:

n ₁ (n)∈{z(n)|z(n)<αmax{z(n)}}

Then, when calculating the first temporary noise Nosie _tmp1 according to the first power sequence n ₁ (n), the first temporary noise Nosie _tmp1 satisfies the following conditions:

Among them, L ₁ is the length of n ₁ (n), and α is the first noise threshold factor.

Then, the second noise threshold is βFaTh×Nosie _tmp1 , where FaTh is the false alarm threshold and β is the second noise threshold factor.

Step S3: Filter out a second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum, and calculate a second temporary noise based on the second power sequence.

In some embodiments, filtering out a second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum includes:

Filtering out power values greater than the first noise threshold in the frequency domain power spectrum to obtain a first frequency domain power spectrum;

Screen out a second power sequence that is less than or equal to the second noise threshold from the first frequency domain power spectrum.

For example, the first frequency domain power spectrum after filtering out frequency data greater than αmax{z(n)} is recorded as z ₁ (n), then the second power sequence n ₂ (n) satisfies, n ₂ (n) ∈{z ₁ (n)|z ₁ (n)≤βFaTh×Nosie _tmp1 }.

When calculating the second temporary noise Nosie _tmp2 based on the second power sequence n ₂ (n), the second temporary noise Nosie _tmp2 satisfies:

Among them, L ₂ is the length of n ₂ (n), FaTh is the false alarm threshold, and β is the second noise threshold factor.

Step S4: Filter out the second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum, and obtain the difference between the second frequency domain power spectrum and the second temporary noise. .

Step S5: Determine whether the difference meets the preset noise confidence threshold, and use the power value in the frequency domain power spectrum that does not meet the noise confidence threshold as the third power sequence, and according to the third power sequence and the second power sequence to calculate the average noise power.

For example, filter out the second frequency domain power spectrum z ₂ (n) that is greater than the second noise threshold βFaTh×Nosie _tmp1 from the first frequency domain power spectrum z ₁ (n) of the frequency domain power spectrum z(n). At this time , take the difference between each element in the second frequency domain power spectrum z ₂ (n) and the second temporary noise Nosie _tmp2 , and obtain the difference between each element in the second frequency domain power spectrum z ₂ (n) and the second temporary noise Nosie _tmp2 Each corresponding difference value, and compare each difference value with the preset noise confidence threshold γ, if the difference value is less than or equal to the noise confidence threshold γ, the difference value corresponds to the second frequency domain power spectrum z ₂ (n) The power value is taken as the third power sequence n ₃ (n), and the third power sequence n ₃ (n) is included in the average noise power calculation.

That is, the third power sequence n ₃ (n) satisfies, n ₃ (n)∈{z ₂ (n)|z ₂ (n)-Nosie _tmp2 ≤γ};

The average noise power NoiseMean satisfies,

Step S6: Set a target peak detection threshold according to the average noise power and the false alarm threshold information, and perform peak detection on the frequency domain power spectrum according to the target peak detection threshold.

For example, after determining the average noise power NoiseMean, set the target peak detection threshold PeakThreshold as: PeakThreshold=NoiseMean×FaTh. According to the target peak detection threshold PeakThreshold, obtain the fourth power sequence in the frequency domain power spectrum z(n) that is greater than the target peak detection threshold PeakThreshold, and obtain the random preamble sequence information corresponding to each element in the fourth power sequence, so that the random preamble can be obtained The preamble ID corresponding to the terminal device is obtained from the sequence information and the time offset TA of the uplink is determined, thereby ensuring the access success rate between the terminal device and the base station.

Please refer to FIG. 3 , which is a schematic structural block diagram of a base station provided by an embodiment of the present disclosure.

As shown in Figure 3, the base station 10 includes a processor 101 and a memory 102. The processor 101 and the memory 102 are connected through a bus 103, which is, for example, an I2C (Inter-integrated Circuit) bus.

Specifically, the processor 101 is used to provide computing and control capabilities to support the operation of the entire base station 10 . The processor 101 can be a central processing unit (Central Processing Unit, CPU). The processor 101 can also be other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC). ), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general processor 101 may be a microprocessor or the processor may be any conventional processor.

Specifically, the memory 102 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) disk, an optical disk, a U disk or a mobile hard disk, etc.

Wherein, the processor 101 is used to run a computer program stored in the memory 102, and implement the following steps when executing the computer program:

Obtain the received PRACH signal and generate a frequency domain power spectrum according to the PRACH signal;

Obtain the network management configuration data of the base station, set a first noise threshold according to the network management configuration data and the frequency domain power spectrum, and set a second noise threshold according to the first noise threshold and the network management configuration data;

Filter out a second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum, and calculate a second temporary noise based on the second power sequence;

Filter out a second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum, and obtain the difference between the second frequency domain power spectrum and the second temporary noise;

Determine whether the difference meets a preset noise confidence threshold, and use the power value in the frequency domain power spectrum that does not meet the noise confidence threshold as a third power sequence, and according to the third power sequence and the The second power sequence calculates the average noise power;

A target peak detection threshold is set according to the average noise power and the false alarm threshold information, and peak detection is performed on the frequency domain power spectrum according to the target peak detection threshold.

In some implementations, when the processor 101 sets the first noise threshold according to the network management configuration data and the frequency domain power spectrum, it includes:

Obtain the first noise threshold factor according to the network management configuration data, and obtain the power maximum value from the frequency domain power spectrum;

The first noise threshold is set according to the power maximum value and the first noise threshold factor.

In some implementations, when the processor 101 sets the second noise threshold according to the first noise threshold and the network management configuration data, the processor 101 includes:

Screen out a first power sequence smaller than the first noise threshold from the frequency power spectrum according to the first noise threshold, and calculate a first temporary noise according to the first power sequence;

Obtain a second noise threshold factor and false alarm threshold information according to the network management configuration data, and set the second noise threshold according to the first temporary noise, the second noise threshold factor and the false alarm threshold information. In some embodiments, when the processor 101 filters out the second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum, the process includes:

Filtering out power values greater than the first noise threshold in the frequency domain power spectrum to obtain a first frequency domain power spectrum;

Screen out a second power sequence that is less than or equal to the second noise threshold from the first frequency domain power spectrum.

In some embodiments, when the processor 101 filters out the second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum, the process includes:

A second frequency domain power spectrum that is greater than the second noise threshold is screened out from the first frequency domain power spectrum of the frequency domain power spectrum.

In some embodiments, when the processor 101 performs peak detection on the frequency domain power spectrum according to the target peak detection threshold, it includes:

Obtain a fourth power sequence in the frequency domain power spectrum that is greater than the target peak detection threshold according to the target peak detection threshold, and obtain preamble sequence information corresponding to each element in the fourth power sequence.

In some embodiments, when the processor 101 generates the frequency domain power spectrum according to the PRACH signal, it includes:

Preprocess the received PRACH signal to obtain the PRACH signal in the time domain;

Perform FFT transformation of the PRACH signal in the time domain to the frequency domain to obtain PRACH frequency domain data corresponding to the PRACH signal;

The frequency domain power spectrum is generated according to the PRACH frequency domain data and a preset frequency domain sequence.

It should be noted that those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the base station described above can be referred to the corresponding process in the aforementioned communication method embodiment, and will not be described again here.

Embodiments of the present disclosure also provide a storage medium for computer-readable storage. The storage medium stores one or more programs. The one or more programs can be executed by one or more processors to implement the following: The steps of any PRACH peak detection method provided in the embodiments of this disclosure.

The storage medium may be an internal storage unit of the base station described in the previous embodiment, such as a hard disk or memory of the base station. The storage medium may also be an external storage device of the base station, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SD) card, or a flash memory card equipped on the base station. (Flash Card) etc.

Those of ordinary skill in the art can understand that all or some steps, systems, and functional modules/units in the devices disclosed above can be implemented as software, firmware, hardware, and appropriate combinations thereof. In hardware embodiments, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be composed of several physical components. Components execute cooperatively. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit . Such software may be distributed on computer-readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). As is known to those of ordinary skill in the art, the term computer storage media includes volatile and nonvolatile media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. removable, removable and non-removable media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disk (DVD) or other optical disk storage, magnetic cassettes, tapes, disk storage or other magnetic storage devices, or may Any other medium used to store the desired information and that can be accessed by a computer. Additionally, it is known to those of ordinary skill in the art that communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media .

It will be understood that the term "and/or" as used in this disclosure and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items. It should be noted that, as used herein, the terms "include", "comprising" or any other variation thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or system that includes a list of elements not only includes those elements, but It also includes other elements not expressly listed or that are inherent to the process, method, article or system. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

The above serial numbers of the embodiments of the present disclosure are only for description and do not represent the advantages and disadvantages of the embodiments. The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person familiar with the technical field can easily think of various equivalent methods within the technical scope disclosed in the present disclosure. Modifications or substitutions, these modifications or substitutions should be covered by the protection scope of this disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims (10)

1. A PRACH peak detection method, applied to base stations, the method includes:

   Obtain the received PRACH signal and generate a frequency domain power spectrum according to the PRACH signal;

   Obtain the network management configuration data of the base station, set a first noise threshold according to the network management configuration data and the frequency domain power spectrum, and set a second noise threshold according to the first noise threshold and the network management configuration data;

   Filter out a second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum, and calculate a second temporary noise based on the second power sequence;

   Filter out a second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum, and obtain the difference between the second frequency domain power spectrum and the second temporary noise;

   Determine whether the difference meets a preset noise confidence threshold, and use the power value in the frequency domain power spectrum that does not meet the noise confidence threshold as a third power sequence, and according to the third power sequence and the The second power sequence calculates the average noise power;

   A target peak detection threshold is set according to the average noise power and the false alarm threshold information, and peak detection is performed on the frequency domain power spectrum according to the target peak detection threshold.
2. The detection method according to claim 1, wherein said setting the first noise threshold according to the network management configuration data and the frequency domain power spectrum includes:

   Obtain the first noise threshold factor according to the network management configuration data, and obtain the power maximum value from the frequency domain power spectrum;

   The first noise threshold is set according to the power maximum value and the first noise threshold factor.
3. The detection method according to claim 2, wherein setting the second noise threshold according to the first noise threshold and the network management configuration data includes:

   Screen out a first power sequence smaller than the first noise threshold from the frequency power spectrum according to the first noise threshold, and calculate a first temporary noise according to the first power sequence;

   Obtain a second noise threshold factor and false alarm threshold information according to the network management configuration data, and set the second noise threshold according to the first temporary noise, the second noise threshold factor and the false alarm threshold information.
4. The detection method according to claim 3, wherein filtering out the second power sequence that is less than or equal to the second noise threshold from the frequency domain power spectrum includes:

   Filtering out power values greater than the first noise threshold in the frequency domain power spectrum to obtain a first frequency domain power spectrum;

   Screen out a second power sequence that is less than or equal to the second noise threshold from the first frequency domain power spectrum.
5. The detection method according to claim 4, wherein filtering out the second frequency domain power spectrum that is greater than the second noise threshold from the frequency domain power spectrum includes:

   A second frequency domain power spectrum that is greater than the second noise threshold is screened out from the first frequency domain power spectrum of the frequency domain power spectrum.
6. The detection method according to claim 5, wherein performing peak detection on the frequency domain power spectrum according to the target peak detection threshold includes:

   Obtain a fourth power sequence in the frequency domain power spectrum that is greater than the target peak detection threshold according to the target peak detection threshold, and obtain preamble sequence information corresponding to each element in the fourth power sequence.
7. The detection method according to any one of claims 1 to 6, wherein generating a frequency domain power spectrum according to the PRACH signal includes:

   Preprocess the received PRACH signal to obtain the PRACH signal in the time domain;

   Perform FFT transformation of the PRACH signal in the time domain to the frequency domain to obtain PRACH frequency domain data corresponding to the PRACH signal;

   The frequency domain power spectrum is generated according to the PRACH frequency domain data and a preset frequency domain sequence.
8. A base station, the base station including a processor, a memory, a computer program stored on the memory and executable by the processor, and a data bus for realizing connection communication between the processor and the memory , wherein when the computer program is executed by the processor, the steps of the PRACH peak detection method according to any one of claims 1 to 7 are implemented.
9. A wireless communication system, the wireless communication system at least includes the base station according to claim 8.
10. A storage medium for computer-readable storage, the storage medium stores one or more programs, the one or more programs can be executed by one or more processors to implement any of claims 1 to 7 A step of peak detection of PRACH.

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