PRACH (Physical Random Access Channel) detection method and equipment for realizing ultra-long distance communication, medium and program product

Abstract

The invention provides a PRACH detection method, equipment, medium and program product for realizing ultra-long distance communication, and the method comprises the steps: carrying out the segment-by-segment coarse detection of a received PRACH time domain baseband signal, so as to determine whether a PRACH signal exists in a current data segment, if the PRACH signal is detected, carrying out the subsequent segment detection, and if the PRACH signal is not detected, carrying out the subsequent segment detection; if yes, detecting the next data segment circularly; performing fine detection on each OFDM symbol in the segment after the coarse detection to obtain a power estimation value and a time delay estimation value of each OFDM symbol; and based on the fine detection result, performing accurate time delay estimation value judgment based on the power and time delay association relationship between the symbols so as to obtain the accurate time delay position of the PRACH signal. According to the invention, the PRACH detection of the ultra-long distance communication is realized, and the ultra-long distance communication can be supported based on a standard 5G protocol.

Description

Technical Field

[0001] The present invention relates to the field of 5G communication, and in particular, to a method, device, medium, and program product for detecting a PRACH (Physical Random Access Channel) for realizing ultra-long-distance communication. Background Art

[0002] In a 5G communication system, the uplink synchronization process essential for system operation is realized based on the Physical Random Access Channel (PRACH). The communication distance supported by the PRACH is one of the key factors determining the coverage radius of a 5G cell. Increasing the communication distance supported by the PRACH can effectively reduce the deployment density of 5G base stations, which is of great significance for reducing the deployment and operation costs of the 5G network. Having the ability to detect PRACH over ultra-long distances can not only greatly improve traditional terrestrial networking but also meet the application requirements of current 5G-NTN.

[0003] The existing 5G PRACH detection scheme can support a maximum communication distance of about 107 km and cannot support communication applications over longer distances. The existing PRACH detection scheme constrains the delay of the PRACH signal reaching the base station side to be planned and controlled within the CP. The PRACH signals sent by all users within the cell coverage need to meet the delay fluctuation range within the CP when reaching the base station side. When the communication distance is greater and the equivalent transmission delay is higher than the CP length, the PRACH signal sent by a user can reach the base station at any moment within the Round-Trip Time (RTT) delay (for example, at a communication distance of 300 km, the RTT delay is 2 ms). The existing PRACH detection scheme cannot accurately detect the PRACH signal, and the base station receiver needs to optimize the design of the PRACH signal detection. Summary of the Invention

[0004] Aiming at the problem that the existing 5G PRACH detection scheme cannot support ultra-long-distance communication, the present invention provides a method, device, medium, and program product for detecting a PRACH for realizing ultra-long-distance communication, which can support ultra-long-distance (at least 300 Km) communication based on the standard 5G protocol.

[0005] A method for detecting a PRACH for realizing ultra-long-distance communication provided by the present invention includes the following steps:

[0006] Step 1, Detection Segmentation Setting: According to the maximum transmission delay in the application scenario, set the length N_total of the potential PRACH data to be processed; according to the adopted PRACH transmission format, set the number of PRACH symbol data N_Symb and the number of segments N included in each segment; set the maximum number of root sequences Nu for detection; set the maximum number of root sequence indices Nroot included;

[0007] Step 2, Initialize the data segment index i = 0, initialize the set u of root sequences that have been detected as u = {}, and initialize the root sequence index as RootIdx = 0;

[0008] Step 3, Frequency Domain Data Extraction: Process the received PRACH time-domain baseband signal with a length of N_total, and make subsequent decisions based on the processing results;

[0009] Step 4, Root Sequence Duplicate Detection Decision: If the current root sequence index RootIdx < Nu and is not included in the set u of root sequences, then jump to Step 5 for processing; otherwise, RootIdx++, jump to Step 4, and perform the loop of the next root sequence;

[0010] Step 5, Preliminary Detection: Perform preliminary PRACH detection on the PRACH frequency-domain baseband signal of the i-th segment, where 0 < i < N - 1; and make a decision based on the preliminary PRACH detection result: If there is a PRACH signal in the preliminary PRACH detection, then jump to Step 6 for secondary detection within the segment; otherwise, i++, jump to Step 5 for the detection of the next data segment;

[0011] Step 6, Secondary Detection: Perform PRACH detection on each of the N_Symb PRACH symbols included in the i-th segment, and record the peak power and delay value detected for each PRACH symbol;

[0012] Step 7, Secondary Detection Result Decision: Based on the peak power and delay values detected for the N_Symb PRACH symbols, make a decision on the correlation relationship between the symbols, and obtain the delay estimation value and the starting position of the starting symbol of the PRACH signal within the i-th segment;

[0013] Step 8, Final Detection Result Statistics: Calculate the total transmission delay based on the segment index value, the delay estimation value within the segment, and the starting position of the starting symbol;

[0014] Step 9, Loop Decision: If i < N - 1, then i++, jump to Step 5 for the detection of the next data segment; otherwise, RootIdx++, jump to Step 4 for the detection of the next root sequence.

[0015] In some embodiments, the processing of Step 3 is as follows:

[0016] Shift the center position of the PRACH in the frequency domain to the system zero-frequency position through frequency shifting, so as to extract the PRACH time-domain baseband signal through downsampling filtering processing;

[0017] Transform the PRACH time-domain baseband signal extracted through downsampling filtering processing into the frequency domain to obtain the PRACH frequency-domain baseband signal;

[0018] Conjugately multiply the PRACH frequency-domain baseband signal and the local PRACH sequence root by root according to the corresponding sequence index;

[0019] Perform IFFT transformation on the conjugately multiplied data to the time domain;

[0020] Calculate the PDP according to the time-domain result of the conjugately multiplied data.

[0021] In some embodiments, the preliminary detection in step 5 is specifically as follows:

[0022] Peak search: First, merge the PDPs of the symbols in different antennas / segments, and then search for the peak for each root order;

[0023] Noise estimation: Calculate the average noise power NP of the current root order according to the searched peak u ;

[0024] Primary threshold decision: Set the first decision threshold PIR th , and perform preliminary PRACH detection according to the peak, the average noise power NP u and the first decision threshold PIR th to determine whether there is a PRACH signal in the preliminary PRACH detection; The primary decision result is expressed as:

[0025] ValidPidSet u = find(PeakSum u ≥ NP u * PIR th )

[0026] where, ValidPidSet u represents the primary decision result of the existence of the PRACH signal.

[0027] In some embodiments, the secondary detection in step 6 is performed with reference to the preliminary detection in step 5, where:

[0028] During peak search, peak search needs to be performed on each symbol within the segment;

[0029] During noise estimation, noise estimation needs to be performed on each symbol within the segment;

[0030] During the primary threshold decision, threshold decision needs to be performed on each symbol within a segment;

[0031] For the found PRACH symbols, record the peak power and time delay value detected for each PRACH symbol.

[0032] In some embodiments, the association relationship decision between symbols in step 7 is as follows:

[0033] Set the second decision threshold PIR th2 , based on the peak value obtained from the secondary detection, the average noise power, and the second decision threshold PIR th2 , obtain the time delay estimation value MeanTo;

[0034] Set the third decision threshold PIR th3 , based on the time delay estimation value MeanTo, the symbol length N ifft and the third decision threshold PIR th3 , determine the starting position SymbOffsetInSegment of the starting symbol within the segment.

[0035] In some embodiments, in step 9, it is necessary to identify the root order of the detected starting position of the valid starting symbol, and during subsequent segmentation loops, the repetition detection of this root order is no longer performed.

[0036] In some embodiments, the calculation formula for the total transmission time delay is as follows:

[0037] TotalTimeOffset

[0038] = SegmentStartPos + MeanTo + SymbOffsetInSegment * N fft

[0039] where TotalTimeOffset is the total transmission time delay.

[0040] The present invention also provides an electronic device, including:

[0041] At least one processor; and a memory communicatively connected to the at least one processor;

[0042] wherein, the memory stores instructions executable by the at least one processor, and the at least one processor, by executing the instructions stored in the memory, causes the at least one processor to execute the described method.

[0043] The present invention also provides a computer-readable storage medium, and the computer-readable storage medium is used to store instructions, and when the instructions are executed, the above-described method is implemented.

[0044] The present invention also provides a computer program product, which, when called by a computer, causes the computer to execute the above-mentioned method.

[0045] In summary, due to the adoption of the above technical solutions, the beneficial effects of the present invention are as follows:

[0046] The present invention adopts a method of segment detection and joint inter-symbol detection for the received time-domain baseband signal, realizes the PRACH detection for ultra-long-distance communication, and based on the standard 5G protocol, can support ultra-long-distance (at least 300 Km) communication. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a flowchart of the method for realizing PRACH detection for ultra-long-distance communication in an embodiment of the present invention.

[0048] Figure 2 It is a flowchart of the segment detection decision in an embodiment of the present invention.

[0049] Figure 3 It is a simulation result diagram in an embodiment of the present invention.

[0050] Figure 4 It is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. Usually, the components of the embodiments of the present invention described and illustrated herein can be arranged and designed in various different configurations.

[0052] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0053] In order to detect PRACH under ultra-long distance transmission, the present invention proposes a PRACH detection method for realizing ultra-long distance communication, and its implementation principle is as follows: adopt the method of segment detection and inter-symbol joint detection for the received time-domain baseband signal. First, according to the preset data segment configuration, perform a rough detection on each segment of the received PRACH time-domain baseband signal to determine whether there is a PRACH signal in the current data segment. If a PRACH signal is detected, perform subsequent in-segment detection. If no PRACH signal is detected, loop to perform the next data segment detection; after the rough detection, for the data segment in which a PRACH signal can be detected within the segment, perform a fine detection on each OFDM symbol within the segment to obtain the power estimation value and delay estimation value of each OFDM symbol; based on the fine detection results, perform an accurate delay estimation value judgment based on the power and delay correlation relationship between symbols to obtain the accurate delay position of the PRACH signal.

[0054] As Figure 1 、 Figure 2 shown, a PRACH detection method for realizing ultra-long distance communication proposed by an embodiment of the present invention includes the following steps:

[0055] Step 1, detection segment setting: according to the maximum transmission delay situation in the application scenario, set the length N_total of the potential PRACH data to be processed; according to the adopted PRACH transmission format, set the number N_Symb of PRACH symbol data included in each segment and the number of segments N; set the maximum number Nu of root sequences used for detection; set the maximum number Nroot of root sequence indexes included.

[0056] Among them, some system configurations can be preferably as follows:

[0057] Each root sequence is limited to only allocate one user resource;

[0058] The transmission period of PRACH needs to satisfy > RTT delay to avoid aliasing of multiple time-domain OCCs of PRACH;

[0059] Within each PRACH transmission period, there can only be one time-domain transmission opportunity.

[0060] Step 2, initialize the data segment index i = 0, initialize the set u = {} of the root sequences that have been detected, and initialize the root sequence index as RootIdx = 0;

[0061] Step 3, frequency-domain data extraction: process the received PRACH time-domain baseband signal with a length of N_total, and make subsequent judgments according to the processing results;

[0062] Step 4, Root sequence repetition detection and decision: If the current root sequence index RootIdx < Nu and it is not included in the root sequence set u, then jump to Step 5 for processing; otherwise, RootIdx++, jump to Step 4, and perform the loop for the next root sequence;

[0063] Step 5, Preliminary detection: Perform preliminary PRACH detection on the i-th (0 < i < N - 1) segment of the PRACH frequency-domain baseband signal; and make a decision based on the preliminary PRACH detection result: If there is a PRACH signal in the preliminary PRACH detection, then jump to Step 6 for intra-segment secondary detection; otherwise, i++, jump to Step 5 for the next data segment detection;

[0064] Step 6, Secondary detection: Perform PRACH detection on each of the N_Symb PRACH symbols included in the i-th segment, and record the peak power and time delay value detected for each PRACH symbol;

[0065] Step 7, Secondary detection result decision: Based on the peak power and time delay values detected for the N_Symb PRACH symbols, make a decision on the correlation relationship between the symbols, and obtain the time delay estimate value MeanTo and the starting position SymbOffsetInSegment of the starting symbol of the PRACH signal in the i-th segment;

[0066] Step 8, Final detection result statistics: Calculate the total transmission time delay TotalTimeOffset based on the segment index value, the intra-segment time delay estimate value, and the starting position of the starting symbol;

[0067] Step 9, Loop decision: If i < N - 1, then i++, jump to Step 5 for the next data segment detection; otherwise, RootIdx++, jump to Step 4 for detection of the next root sequence.

[0068] In some embodiments, the processing of Step 3 is as follows:

[0069] Perform sliding segmentation on the PRACH time-domain received signal with each OFDM as the step size. The length of each segment is the number of OFDM symbols included in the PRACH, and process each segment of data.

[0070] First, shift the center position of the PRACH frequency domain to the system zero-frequency position through frequency shifting, and extract the PRACH time-domain baseband signal through downsampling filtering (using a low-pass filter).

[0071] The frequency shifting process is as follows:

[0072]

[0073] n = 0, 1,..., N u +Ncp -1

[0074] seg = 0, 1, ..., N Seg -1

[0075]

[0076] The downsampling filtering process is expressed as follows:

[0077]

[0078] n' = 1, ..., (N u +(N cp ) / N os -1

[0079] seg = 0, 1, ..., N Seg -1

[0080] Then, perform matched filtering on the PRACH time-domain baseband signal for each segment.

[0081] Transform the PRACH time-domain baseband signal extracted through downsampling filtering into the frequency domain to obtain the PRACH frequency-domain baseband signal;

[0082] The domain transformation process is as follows:

[0083]

[0084] k = 1, ..., N fft -1

[0085] N fft = N u / N os

[0086] seg = 0, 1, …, N Seg -1

[0087] Then, conjugate multiply the PRACH frequency-domain baseband signal and the local PRACH sequence one by one according to the corresponding sequence index, and the process is as follows:

[0088] Z(k, r, u, s, seg) = Y * (k, r, s, seg) * X(k, u)

[0089] k = 0, ..., L RA -1

[0090] u ∈ S Root

[0091] Perform IFFT (Inverse Fast Fourier Transform) on the conjugate - multiplied data to transform it into the time domain:

[0092]

[0093] n = 0,..., N ifft -1

[0094] Then calculate the PDP according to the time - domain result of the conjugate - multiplied data:

[0095] p(n, u, r, s)=|c(n, r, u, s)| 2

[0096] In some embodiments, according to the processing result of step 3, the preliminary detection in step 5 is as follows:

[0097] Peak search: First, perform PDP merging on the symbols within different antennas / segments:

[0098]

[0099] Then search for peaks for each root order, and the processing method is as follows:

[0100]

[0101] n ∈ (Pos i , Pos i +N winSize -1)

[0102] k = 0

[0103] Noise estimation: Calculate the average noise power NP of the current root order according to the searched peak u :

[0104]

[0105] Primary threshold decision: Set the first decision threshold PIR th , and perform preliminary PRACH detection according to the peak, the average noise power NP u and the first decision threshold PIR rh to determine whether there is a PRACH signal in the preliminary PRACH detection, expressed as:

[0106] ValidPidSet u =find(PeakSum u ≥NP u *PIR th )

[0107] Among them, ValidPidSet u represents the primary decision result of the existence of the PRACH signal.

[0108] In some embodiments, the secondary detection in step 6 can refer to the preliminary detection in step 5, specifically as follows:

[0109] Same as the peak search in step 5, the difference is that peak search is performed for each symbol within the segment.

[0110] Same as the noise estimation in step 5, the difference is that noise estimation is performed for each symbol within the segment.

[0111] Same as the primary threshold decision in step 5, the difference is that threshold decision is performed for each symbol within the segment.

[0112] Through step 6, for the found PRACH symbols, record the peak power and delay value detected for each PRACH symbol.

[0113] In some embodiments, the determination of the correlation relationship between symbols in step 7 is as follows:

[0114] First, set the second decision threshold PIR th2 , and obtain the delay estimation value:

[0115] CandidtIdx0 = find(PeakSum u,s ≥NP u,s *PIR th2 )

[0116] MeanTo = mean(TASet(CandidtIdx0))

[0117] Then, determine the starting position of the valid starting symbol to determine the starting position of the starting symbol within the segment:

[0118] If the delay estimation value MeanTo is greater than half of the symbol length N ifft / 2, and there is more than one valid symbol in the candidate set CandidtIdx0, then:

[0119] SymbOffsetInSegment = CandidtIdx0(1) - Noffset

[0120] Among them,

[0121] SymbOffsetInSegment is the starting position of the starting symbol within the segment;

[0122] Noffset is the influence factor of the CP under different PRACH formats during detection;

[0123] Otherwise, if there is only one symbol in the candidate set CandidtIdx0, then use it as the symbol finally detected, Candidt = CandidtIdx0(1); if there are multiple symbols in the candidate set CandidtIdx0, then judge whether the first symbol (i.e., CandidtIdx0(1)) in the candidate set CandidtIdx0 is valid according to the time delay and PIR strength of the first symbol in the candidate set CandidtIdx0.

[0124] Determine the previous symbol position index preSymbPosIdx = CandidtIdx0(1) - 1;

[0125] Obtain the time delay deviation TimeDiffAbs = abs(MeanTo - Ta u );

[0126] u = preSymbPosIdx

[0127] If TimeDiffAbs < TA_thresold and (PeakSum u，presymbPosIdx ≥ NP u *PIR th3 ), then use preSymbPosIdx as the candidate first symbol, and record SymbOffsetInSegment = preSymbPosIdx - 1.

[0128] Among them, TA_thresold is the timing threshold, and PIR th3 is the third decision threshold.

[0129] In some embodiments, the calculation formula of the total transmission time delay TotalTimeOffset is as follows:

[0130] TotalTimeOffset

[0131] = SegmentStartPos + MeanTo + SymbOffsetInSegment * N fft

[0132] That is, the total transmission time delay is the sum of the segment start position deviation, the timing deviation within the superimposed symbol, and the symbol deviation within the segment.

[0133] In some embodiments, in step 9, it is necessary to identify the root order #u of the detected valid start symbol start position, so that when performing the subsequent segmentation loop, the root order #u will no longer be detected repeatedly.

[0134] The effects of the present invention will be further described below in conjunction with simulation experiments.

[0135] The simulation parameters are set as shown in Table 1.

[0136] Table 1, Parameter settings for the simulation:

[0137]

[0138] The simulation results are as Figure 3 shown. It can be seen that based on the detection standard of 3GPP, the present invention can support a communication distance of 300 Km. Taking the 3GPP standard PRACH format FMT C2 of the simulation case as an example, an SNR of -3 dB can be achieved at a 1% missed detection probability. Moreover, the present invention can meet the false alarm probability index required by 3GPP, which is lower than 1‰.

[0139] Based on the same technical concept, an embodiment of the present invention also provides an electronic device, which can implement the PRACH detection method process for realizing ultra-long-distance communication provided in the above embodiment of the present invention. In one embodiment, the electronic device can be a server, a terminal device, or other electronic devices. As Figure 4 shown, the electronic device may include:

[0140] At least one processor, and a memory connected to the at least one processor. In the embodiment of the present invention, the specific connection medium between the processor and the memory is not limited. Figure 4 In Figure 4 it is taken as an example that the processor and the memory are connected through a bus. The bus is represented by a thick line in Figure 4 and the connection manners between other components are only for illustrative purposes and are not to be construed as limiting. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 4 it is only represented by a single thick line in

[0141] but it does not mean that there is only one bus or one type of bus. Alternatively, the processor can also be called a controller, and there is no limitation on the name.

[0141] In the embodiment of the present invention, the memory stores instructions executable by at least one processor. By executing the instructions stored in the memory, the at least one processor can execute a PRACH detection method for realizing ultra-long-distance communication described above. The processor can implement Figure 4 the functions of each module in the device shown in

[0142] Among them, the processor is the control center of the device, which can connect various parts of the entire control device through various interfaces and lines. By running or executing the instructions stored in the memory and calling the data stored in the memory, various functions of the device and process data, thereby monitoring the device as a whole.

[0143] In an alternative design, the processor may include one or more processing units. The processor may integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, application programs, etc., and the modem processor mainly processes wireless communications. It can be understood that the above-mentioned modem processor may not be integrated into the processor either. In some embodiments, the processor and the memory may be implemented on the same chip, and in some embodiments, they may also be separately implemented on independent chips.

[0144] The processor may be a general-purpose processor, such as a CPU, a digital signal processor, an application-specific integrated circuit, a field-programmable gate array, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of a PRACH detection method for implementing ultra-long-distance communication disclosed in combination with the embodiments of the present invention may be directly embodied as being executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0145] As a non-volatile computer-readable storage medium, the memory can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The memory may include at least one type of storage medium. For example, it may include flash memory, a hard disk, a multimedia card, a card-type memory, a random access memory (RAM), a static random access memory (SRAM), a programmable read-only memory (PROM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic memory, a magnetic disk, an optical disc, and so on. The memory is 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 in the embodiments of the present invention may also be a circuit or any other device capable of implementing a storage function, for storing program instructions and / or data.

[0146] By programming the design of the processor, the code corresponding to a PRACH detection method for implementing ultra-long-distance communication introduced in the foregoing embodiments can be solidified into the chip, so that the chip can execute when running Figure 1Steps of the method of the illustrated embodiment. How to design and program the processor is a well-known technique to those skilled in the art and will not be elaborated here.

[0147] Based on the same inventive concept, an embodiment of the present invention further provides a storage medium storing computer instructions, which when run on a computer, cause the computer to execute a PRACH detection method for realizing ultra-long-distance communication as described above.

[0148] In some optional embodiments, various aspects of a PRACH detection method for realizing ultra-long-distance communication provided by the present invention can also be implemented in the form of a program product, which includes program code. When the program product runs on a device, the program code is used to cause the control device to execute the steps in a PRACH detection method for realizing ultra-long-distance communication according to various exemplary embodiments of the present invention described above in this specification.

[0149] It should be noted that although several units or subunits of the device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present invention, the features and functions of the two or more units described above can be embodied in one unit. Conversely, the features and functions of one unit described above can be further divided and embodied by multiple units. In addition, although the operations of the method of the present invention are described in a specific order in the drawings, this does not require or imply that these operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution.

[0150] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0151] The present invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each flow and / or block in the flowchart illustrations and / or block diagrams, and combinations of flows and / or blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processors of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a server such that the instructions executed by the processor of the computer or other programmable data processing device create means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in a block or blocks.

[0152] Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user computing device, partly on the user device, as a stand-alone software package, partly on the user computing device and partly on a remote computing device, or entirely on the remote computing device or server.

[0153] In the case of a remote computing device, the remote computing device may be connected to the user computing device through any type of network including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., through the Internet using an Internet service provider).

[0154] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable memory produce a manufacture including instruction means for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in a block or blocks.

[0155] These computer program instructions may also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on the computer or other programmable device to produce a computer-implemented process, whereby the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in the flow Figure 1 one or more flows and / or blocks Figure 1 or means for implementing the functions specified in a block or blocks.

[0156] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A PRACH detection method for realizing ultra-long-distance communication, characterized in that: The steps include: Step 1, detection segment setting: according to the maximum transmission delay in the application scenario, set the potential PRACH data length N_total to be processed; according to the adopted PRACH transmission format, set the PRACH symbol data N_Symb and the number of segments N contained in each segment; set the maximum number of root sequences Nu used in the detection; set the maximum number of root sequence indexes Nroot contained; Step 2, initialize the data segment index i=0, initialize the detected root sequence set u={}, and initialize the root sequence index to RootIdx=0; Step 3, frequency domain data extraction: Process the received PRACH time domain baseband signal of length N_total, and make subsequent decisions based on the processing results; Step 4, root sequence duplication detection judgment: if the current root sequence index RootIdx is less than Nu and is not included in the root sequence set u, then jump to step 5 for processing; Otherwise, RootIdx++, jump to step 4 and loop for the next root sequence; Step 5: Preliminary detection: Perform preliminary PRACH detection on the PRACH frequency domain baseband signal of the i-th segment. <i<N-1; And judge according to the preliminary PRACH detection result: if there is a PRACH signal in the preliminary PRACH detection, jump to step 6 and perform a secondary detection within the segment; Otherwise, i++, jump to step 5 to detect the next data segment; Step 6, secondary detection: perform PRACH detection on each of the N_Symb PRACH symbols contained in the i-th segment, and record the peak power and delay value detected for each PRACH symbol; Step 7, secondary detection result judgment: According to the peak power and delay value detected by N_Symb PRACH symbols, the correlation relationship between the symbols is judged to obtain the delay estimation value and the starting position of the starting symbol of the PRACH signal in the i-th segment; Step 8, final detection result statistics: calculate the total transmission delay according to the segment index value, the intra-segment delay estimation value and the starting position of the starting symbol; Step 9, loop judgment: if i<N-1, then i++, jump to step 5, and perform the next data segment detection; Otherwise, RootIdx++, jump to step 4 and perform the next root sequence detection.

2. The PRACH detection method for realizing ultra-long-distance communication according to claim 1, characterized in that: Step 3 is processed as follows: The PRACH frequency domain center position is moved to the system zero frequency position through frequency shifting, so as to extract the PRACH time domain baseband signal through downsampling filtering; The PRACH time domain baseband signal extracted by downsampling filtering is transformed into the frequency domain to obtain a PRACH frequency domain baseband signal; The PRACH frequency domain baseband signal and the local PRACH sequence are conjugate-multiplied root by root according to the corresponding sequence index; Perform IFFT transformation on the conjugate multiplied data to the time domain; The PDP is calculated from the time domain result of the conjugate multiplied data.

3. The PRACH detection method for realizing ultra-long-distance communication according to claim 2, characterized in that: The preliminary test in step 5 is as follows: Peak search: first perform PDP combination on symbols in different antennas / segments, and then search for the peak value for each root sequence; Noise estimation: Calculate the average noise power NP of the current root sequence based on the peak value found u ; Primary threshold decision: Set the first decision threshold PIR th , and according to the peak and average noise power NP u and the first decision threshold PIR th Perform preliminary PRACH detection to determine whether there is a PRACH signal in the preliminary PRACH detection; the primary decision result is expressed as: ValidPidSet u =find(PeakSum u ≥NP u *PIR th ) Among them, ValidPidSet u Indicates the primary decision result of the presence of a PRACH signal.

4. The PRACH detection method for realizing ultra-long-distance communication according to claim 3, characterized in that: The secondary test in step 6 is performed with reference to the primary test in step 5, where: When searching for peak values, it is necessary to perform a peak search on each symbol in the segment; When estimating noise, it is necessary to perform noise estimation on each symbol in the segment; During the primary threshold decision, it is necessary to make a threshold decision for each symbol in the segment; For the PRACH symbols found, the peak power and delay values ​​detected for each PRACH symbol are recorded.

5. The PRACH detection method for realizing ultra-long-distance communication according to claim 4, characterized in that: The association relationship between the symbols in step 7 is determined as follows: Set the second decision threshold PIR th2 , according to the peak and average noise power obtained by the secondary detection and the second decision threshold PIR th2 , get the delay estimation value MeanTo; Set the third decision threshold PIR th3 , according to the delay estimation value MeanTo and symbol length N ifft And the third decision threshold PIR th3 , determine the starting position of the starting symbol in the segment SymbOffsetInSegment.

6. The PRACH detection method for realizing ultra-long-distance communication according to claim 5, characterized in that: In step 9, the root sequence of the starting position of the valid start symbol needs to be marked, and the root sequence will not be repeatedly detected in the subsequent segmentation cycle.

7. The PRACH detection method for realizing ultra-long-distance communication according to claim 5, characterized in that: The total transmission delay is calculated as follows: TotalTimeOffset=SegmentStartPos+MeanTo+SymbOffsetInSegment*N fft Among them, TotalTimeOffset is the total transmission delay.

8. An electronic device, characterized in that: include: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the at least one processor executes the method as described in any one of claims 1 to 7 by executing the instructions stored in the memory.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium is used to store instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is implemented.

10. A computer program product, characterized in that When the computer program product is called by a computer, the computer is caused to execute the method according to any one of claims 1 to 7.

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