CN113993145B - Method, device, processor and computer readable storage medium for realizing NR downlink multi-cell detection processing in mobile communication system - Google Patents
Method, device, processor and computer readable storage medium for realizing NR downlink multi-cell detection processing in mobile communication system Download PDFInfo
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Abstract
The invention relates to a method for realizing NR downlink multi-cell detection processing in a mobile communication system, which comprises the steps of respectively generating primary synchronization signal data and secondary synchronization signal data; performing main synchronous sliding correlation; determining a threshold related to the primary synchronization; performing auxiliary synchronization correlation to obtain the maximum value of auxiliary synchronization signal correlation; determining a threshold related to secondary synchronization; determining a physical cell with the strongest signal; calculating a frequency offset value and performing frequency offset compensation; reconstructing the secondary synchronized frequency domain data of the strongest physical cell. The invention also relates to a device, a processor and a computer readable storage medium for realizing NR downlink multi-cell detection processing in the mobile communication system. The method, the device, the processor and the computer readable storage medium for realizing NR downlink multi-cell detection processing in the mobile communication system adopt the data of the strongest cell secondary synchronization signal SSS separated for a plurality of times, reduce the influence of the same-frequency interference, reduce the system operation time and the hardware cost and enhance the real-time performance of algorithm realization.
Description
Technical Field
The invention relates to the field of mobile communication, in particular to the field of mobile communication research and development and testing, and specifically relates to a method, a device, a processor and a computer readable storage medium for realizing NR downlink multi-cell detection processing in a mobile communication system.
Background
The 5G NR is a digital cellular communication mode which is based on the brand new design of OFDM technology. Compared with 4G LTE,5G NR has the remarkable advantages of higher peak rate, capability of supporting larger data transmission application, air interface time delay millisecond level, capability of meeting real-time application such as automatic driving and the like, higher and more flexible spectrum utilization rate, ultra-large network capacity and the like, and meanwhile, 5G NR is downward compatible with 4GLTE, and the inheritance of technology and cost transition problem in actual networking investment are fully considered.
The main key technologies for 5G NR are: 1. the deployment number of 5G base stations in the future is more than 10 times of that in the 4G era, meanwhile, the number of terminals can also be increased in an explosive manner, and in order to realize more efficient site switching, a new coordination algorithm and network dynamic deployment are very important. 2. The content distribution network, facing the service with larger data volume demand in the 5G age, needs to consider not only the problem of increasing transmission bandwidth, but also the problems of route blocking, delay, processing capacity of a website server, and the like, and how to distribute the large-flow service content is the problem to be solved by the content distribution network. M2M communication is the most common application mode of the Internet of things, and M2M communication has wide application value in the aspects of smart power grids, smart home, environment monitoring and the like. Intellectualization, interactivity is a typical feature of M2M communication.
The current NR downlink multi-cell detection method usually detects multiple cells at one time in a section of baseband received data, and has poor effect when the same frequency interference is serious and the signal to noise ratio is bad, often only the strongest cell can be detected, and when the cells are detected, the whole section of SSS sequence is related, and the execution under a serial system is very time-consuming and has poor efficiency. The invention provides a method for rapidly and efficiently detecting NR downlink multi-cell under a complex electromagnetic environment. And the method adopts good channel estimation, and can reduce the influence of the same-frequency interference and noise to the greatest extent by continuously detecting other cells after removing the strongest cell data. Meanwhile, the influence of frequency offset and the speed requirement are fully considered in algorithm design, and PSS detection is consideredAfter the result of (1), SSS correlation and threshold judgment are re-segmented, so that the system operation time and hardware cost are greatly reduced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method, a device, a processor and a computer readable storage medium for realizing NR downlink multi-cell detection processing in a mobile communication system which is rapid, efficient and wide in application range.
In order to achieve the above object, a method, an apparatus, a processor, and a computer readable storage medium for implementing NR downlink multi-cell detection processing in a mobile communication system according to the present invention are as follows:
the method for realizing NR downlink multi-cell detection processing in the mobile communication system is mainly characterized by comprising the following steps:
(1) Generating primary synchronization signal data and secondary synchronization signal data respectively;
(2) Extracting baseband data sampled by a receiving end, and performing main synchronous sliding correlation;
(3) Determining a threshold of the main synchronization correlation, comparing the calculated maximum correlation value of the main synchronization signal with the threshold of the main synchronization correlation, and if the maximum correlation value of the main synchronization signal is larger than the threshold, successfully synchronizing the main synchronization; otherwise, the main synchronization fails, and the step is ended;
(4) Performing auxiliary synchronization correlation to obtain the maximum value of auxiliary synchronization signal correlation;
(5) Determining a threshold of auxiliary synchronization correlation, comparing the calculated maximum correlation value of the auxiliary synchronization signal with the threshold of auxiliary synchronization correlation, and if the maximum correlation value of the auxiliary synchronization signal is greater than the threshold, successfully carrying out auxiliary synchronization; otherwise, the auxiliary synchronization fails, and the step is ended;
(6) Determining a physical cell with the strongest signal in the current baseband data, namely a physical cell corresponding to the largest auxiliary synchronization related value;
(7) Calculating an auxiliary synchronous channel estimated value of the strongest physical cell, and calculating a frequency offset value according to the sampling rate and the subcarrier interval, and performing frequency offset compensation on the baseband data of the receiving end;
(8) Reconstructing the auxiliary synchronous frequency domain data of the strongest physical cell, obtaining time domain data by inverse Fourier transformation, and subtracting the auxiliary synchronous time domain data of the physical cell from the corresponding position of the receiving end band data;
(9) And (5) detecting the physical cell with the strongest current time, and continuing the step (5) until the secondary synchronization fails.
Preferably, the step (2) specifically includes the following steps:
and extracting baseband data sampled by the receiving end, respectively using a main synchronous signal to carry out sliding correlation with the baseband data of the receiving end, and determining the position of the point with the maximum correlation value.
Preferably, the step (4) specifically includes the following steps:
and extracting data of the auxiliary synchronization signal according to the relative position relation between the main synchronization signal and the auxiliary synchronization signal, performing fast Fourier transform to obtain frequency domain data, and performing correlation calculation with part of auxiliary synchronization signal sequences respectively to obtain the maximum value of auxiliary synchronization signal correlation.
Preferably, in the step (2), the main synchronous sliding correlation is performed, specifically:
the primary synchronization sliding correlation is performed according to the following formula:
C n ＝L n ×R′ n ；
wherein C is n L is the PSS time domain correlation result n For local generation of PSS time domain data, R' n Conjugation to receive end band data.
Preferably, the determining the threshold related to the primary synchronization in the step (3) specifically includes the following steps:
calculating and recording the main synchronous signal related values of all points in the sliding window to obtain the average value of the related values of all points; dividing all the point correlation values by the average value, and confirming the threshold value according to the current signal-to-noise ratio so that the peak-to-average ratio value is larger than the threshold value and all the point correlation values are smaller than the threshold value.
Preferably, the determining the threshold related to the secondary synchronization in the step (5) specifically includes the following steps:
and calculating the square of the accumulation result of the correlation values of the secondary synchronization sequences of the cells, dividing the square of the secondary synchronization frequency domain data of the base band of the receiving end, and determining the threshold value of the secondary synchronization correlation.
Preferably, in the step (7), the frequency offset value is calculated, specifically:
calculating the frequency offset value according to the following formula:
Δf＝p×rbw；
where p is the position of peak power and rbw is the resolution bandwidth.
Preferably, in the step (7), frequency offset compensation is performed, specifically:
frequency offset compensation is performed according to the following formula:
R′(m)＝R(m)×e -j2πΔfkTc ；
wherein R' (m) is the baseband data after compensation, R (m) is the original received baseband data, deltaf is the frequency offset value, k is the chip sequence number, and Tc is the chip interval.
Preferably, the step (8) specifically includes the following steps:
(8.1) carrying out equalization treatment on the auxiliary synchronous channel estimation value after the frequency offset compensation;
(8.2) reconstructing the secondary synchronization frequency domain data in the receiving end group band data through the balanced secondary synchronization channel estimation;
(8.3) performing inverse Fourier transform on the frequency domain data of the auxiliary synchronizing signal in the receiving end baseband data to obtain the time domain data of the auxiliary synchronizing signal;
and (8.4) subtracting the time domain data of the reconstructed auxiliary synchronous signal from the position corresponding to the time domain data of the auxiliary synchronous signal in the receiving end band data to obtain new receiving end band data.
The device for realizing NR downlink multi-cell detection processing in the mobile communication system is mainly characterized in that the device comprises:
a processor configured to execute computer-executable instructions;
and a memory storing one or more computer executable instructions which, when executed by the processor, implement the steps of the method for implementing NR downlink multi-cell detection processing in the mobile communication system.
The processor for realizing NR downlink multi-cell detection processing in the mobile communication system is mainly characterized in that the processor is configured to execute computer executable instructions, and when the computer executable instructions are executed by the processor, the steps of the method for realizing NR downlink multi-cell detection processing in the mobile communication system are realized.
The computer readable storage medium is characterized in that the computer program is stored thereon, and the computer program can be executed by a processor to implement the steps of the method for implementing NR downlink multi-cell detection processing in the mobile communication system.
The method, the device, the processor and the computer readable storage medium for realizing NR downlink multi-cell detection processing in the mobile communication system are suitable for rapidly analyzing NR downlink multi-cells, analyzing signal quality and carrying out network optimization in a complex electromagnetic environment. The data of the secondary synchronization signal SSS of the strongest cell is separated for multiple times, so that the influence of the same-frequency interference can be effectively reduced. Meanwhile, the characteristics of the SSS sequence are fully considered in the algorithm design, and the segmentation judgment threshold is calculated in a segmentation mode, so that the system operation time and hardware cost are reduced, and the real-time performance of algorithm implementation is enhanced.
Drawings
Fig. 1 is a flowchart of a method for implementing NR downlink multi-cell detection processing in a mobile communication system according to the present invention.
Fig. 2 is a flowchart of a method for implementing NR downlink multi-cell detection processing to separate strongest cell SSS data in a mobile communication system according to the present invention.
Fig. 3 is a diagram showing the power difference of the strongest co-channel interference cell after analysis in the method for implementing NR downlink multi-cell detection processing in the mobile communication system of the present invention.
Fig. 4 is an effect diagram of the method for implementing NR downlink multi-cell detection processing in the mobile communication system according to the present invention when the method is actually applied to air interface signal analysis.
Detailed Description
In order to more clearly describe the technical contents of the present invention, a further description will be made below in connection with specific embodiments.
The method for realizing NR downlink multi-cell detection processing in the mobile communication system comprises the following steps:
(1) Generating primary synchronization signal data and secondary synchronization signal data respectively;
(2) Extracting baseband data sampled by a receiving end, and performing main synchronous sliding correlation;
(3) Determining a threshold of the main synchronization correlation, comparing the calculated maximum correlation value of the main synchronization signal with the threshold of the main synchronization correlation, and if the maximum correlation value of the main synchronization signal is larger than the threshold, successfully synchronizing the main synchronization; otherwise, the main synchronization fails, and the step is ended;
(4) Performing auxiliary synchronization correlation to obtain the maximum value of auxiliary synchronization signal correlation;
(5) Determining a threshold of auxiliary synchronization correlation, comparing the calculated maximum correlation value of the auxiliary synchronization signal with the threshold of auxiliary synchronization correlation, and if the maximum correlation value of the auxiliary synchronization signal is greater than the threshold, successfully carrying out auxiliary synchronization; otherwise, the auxiliary synchronization fails, and the step is ended;
(6) Determining a physical cell with the strongest signal in the current baseband data, namely a physical cell corresponding to the largest auxiliary synchronization related value;
(7) Calculating an auxiliary synchronous channel estimated value of the strongest physical cell, and calculating a frequency offset value according to the sampling rate and the subcarrier interval, and performing frequency offset compensation on the baseband data of the receiving end;
(8) Reconstructing the auxiliary synchronous frequency domain data of the strongest physical cell, obtaining time domain data by inverse Fourier transformation, and subtracting the auxiliary synchronous time domain data of the physical cell from the corresponding position of the receiving end band data;
(9) And (5) detecting the physical cell with the strongest current time, and continuing the step (5) until the secondary synchronization fails.
As a preferred embodiment of the present invention, the step (2) specifically includes the following steps:
and extracting baseband data sampled by the receiving end, respectively using a main synchronous signal to carry out sliding correlation with the baseband data of the receiving end, and determining the position of the point with the maximum correlation value.
As a preferred embodiment of the present invention, the step (4) specifically includes the following steps:
and extracting data of the auxiliary synchronization signal according to the relative position relation between the main synchronization signal and the auxiliary synchronization signal, performing fast Fourier transform to obtain frequency domain data, and performing correlation calculation with part of auxiliary synchronization signal sequences respectively to obtain the maximum value of auxiliary synchronization signal correlation.
As a preferred embodiment of the present invention, the main synchronous sliding correlation in the step (2) is specifically:
the primary synchronization sliding correlation is performed according to the following formula:
C n ＝L n ×R′ n ；
wherein C is n L is the PSS time domain correlation result n For local generation of PSS time domain data, R' n Conjugation to receive end band data.
As a preferred embodiment of the present invention, the determining the threshold related to the primary synchronization in the step (3) specifically includes the following steps:
calculating and recording the main synchronous signal related values of all points in the sliding window to obtain the average value of the related values of all points; dividing all the point correlation values by the average value, and confirming the threshold value according to the current signal-to-noise ratio so that the peak-to-average ratio value is larger than the threshold value and all the point correlation values are smaller than the threshold value.
As a preferred embodiment of the present invention, the determining the threshold related to the secondary synchronization in the step (5) specifically includes the following steps:
and calculating the square of the accumulation result of the correlation values of the secondary synchronization sequences of the cells, dividing the square of the secondary synchronization frequency domain data of the base band of the receiving end, and determining the threshold value of the secondary synchronization correlation.
As a preferred embodiment of the present invention, the calculating the frequency offset value in the step (7) specifically includes:
calculating the frequency offset value according to the following formula:
Δf＝p×rbw；
where p is the position of peak power and rbw is the resolution bandwidth.
As a preferred embodiment of the present invention, the frequency offset compensation in the step (7) specifically includes:
frequency offset compensation is performed according to the following formula:
R′(m)＝R(m)×e -j2πΔfkTc ；
wherein R' (m) is the baseband data after compensation, R (m) is the original received baseband data, deltaf is the frequency offset value, k is the chip sequence number, and Tc is the chip interval.
As a preferred embodiment of the present invention, the step (8) specifically includes the steps of:
(8.1) carrying out equalization treatment on the auxiliary synchronous channel estimation value after the frequency offset compensation;
(8.2) reconstructing the secondary synchronization frequency domain data in the receiving end group band data through the balanced secondary synchronization channel estimation;
(8.3) performing inverse Fourier transform on the frequency domain data of the auxiliary synchronizing signal in the receiving end baseband data to obtain the time domain data of the auxiliary synchronizing signal;
and (8.4) subtracting the time domain data of the reconstructed auxiliary synchronous signal from the position corresponding to the time domain data of the auxiliary synchronous signal in the receiving end band data to obtain new receiving end band data.
The device for realizing NR downlink multi-cell detection processing in the mobile communication system of the invention comprises:
a processor configured to execute computer-executable instructions;
and a memory storing one or more computer executable instructions which, when executed by the processor, implement the steps of the method for implementing NR downlink multi-cell detection processing in the mobile communication system.
The processor for implementing the NR downlink multi-cell detection process in the mobile communication system of the present invention, wherein the processor is configured to execute computer executable instructions, and when the computer executable instructions are executed by the processor, implement the steps of the method for implementing the NR downlink multi-cell detection process in the mobile communication system.
The computer readable storage medium of the present invention has stored thereon a computer program executable by a processor to perform the steps of the above-described method for performing NR downlink multi-cell detection processing in a mobile communication system.
In a specific embodiment of the present invention, a method for NR downlink multi-cell detection in a mobile communication system specifically includes the following steps:
(1) Respectively generate 3 kinds ofThe sequence and time domain data of the primary synchronization signal PSS are represented, and the sequence and time domain data of the secondary synchronization signal SSS represented by 1008 physical cells PCI are respectively generated;
(2) Extracting baseband data sampled by a receiving end, and respectively using 3 kinds of dataThe represented PSS time domain data is related with the data sliding of the receiving end band, and the position of the point with the maximum related value and the possible +.>A type;
(3) Determining a reasonable threshold, comparing the calculated PSS maximum correlation value with the value of the threshold, if the value is larger than the threshold, indicating that the primary synchronization is successful, otherwise, indicating that the primary synchronization is failed;
(4) After the primary synchronization is successful, according to the relative position relation of SSS and PSS, extracting the time domain data of SSS, and then obtaining frequency domain data through fast Fourier transform FFT, wherein the frequency domain data respectively meets the requirements of 1008 SSS sequencesCorrelating the required partial sequences to find the maximum value;
(5) Determining a reasonable threshold, comparing the calculated SSS maximum correlation value with the value of the threshold, if the SSS maximum correlation value is larger than the value of the threshold, the auxiliary synchronization is successful, otherwise, the auxiliary synchronization is failed;
(6) After the secondary synchronization is successful, the PCI of the physical cell with the strongest signal in the current baseband data can be determined to be the PCI corresponding to the maximum SSS related value;
(7) Calculating SSS channel estimation value of the strongest PCI, calculating frequency offset value according to sampling rate and subcarrier interval, and performing frequency offset compensation on receiving end baseband data;
(8) Reconstructing the SSS frequency domain data of the strongest PCI, performing inverse Fourier transform (IFFT) to the time domain data, and subtracting the SSS time domain data from the corresponding position of the receiving end band data.
(9) Detecting the strongest PCI at the position corresponding to SSS in the new receiving end band data, and jumping to step (5) to continue processing until the secondary synchronization fails.
In the step (1), 3 kinds of PSS data are respectively generated, and 1008 kinds of SSS data are respectively generated, specifically:
physical cell
PSS sequence generation is performed according to the following formula:
d PSS (n)＝1-2x(m)；
wherein,
x(i+7)＝(x(i+4)+x(i))mod2，[x(6)x(5)x(4)x(3)x(2)x(1)x(0)]＝[1 1 1 0 1 1 0]。
and selecting a proper inverse fast Fourier transform size according to the sampling rate FS and the subcarrier spacing SC of the receiving end baseband data to transform the PSS sequence IFFT to a time domain.
SSS sequence generation is performed according to the following formula:
d SSS (n)＝[1-2x 0 ((n+m 0 )mod127)][1-2x 1 ((n+m 1 )mod127)]；
wherein,
x 0 (i+7)＝(x(i+4)+x 0 (i))mod2，x 1 (i+7)＝(x 1 (i+1)+x 1 (i))mod2，
[x 0 (6)x 0 (5)x 0 (4)x 0 (3)x 0 (2)x 0 (1)x 0 (0)]＝[0 0 0 0 0 1]，
[x 1 (6)x 1 (5)x 1 (4)x 1 (3)x 1 (2)x 1 (1)x 1 (0)]＝[0 0 0 0 0 1]。
and selecting a proper inverse fast Fourier transform size according to the sampling rate FS and the subcarrier spacing SC of the receiving end band data to IFFT the SSS sequence to the time domain.
PSS sliding correlation in the step (2) is specifically:
the correlation calculation is performed according to the following formula:
C n ＝L n ·R′ n ；
wherein C is n Is PSS time domain correlation result, L n Is to generate PSS time domain data locally, R' n Is the conjugation of the receiving end band data. To reduce the effects of frequency offset and noise interference, the relevant computation of the PSS may be segmented. Determining a relatively small number of low thresholds in step (3) for screening for possible presence
The threshold determination of the PSS in the step (3) is specifically:
and calculating and recording PSS related values of all points in the sliding window to obtain average values of the related values of all points, dividing the related values of all points by the average values, and confirming a proper threshold value by considering the current signal-to-noise ratio SNR so that the value of the peak-to-average ratio is larger than the threshold and the values of other points are generally smaller than the threshold. The time domain data at the strongest PSS data can be transformed to the frequency domain from the frequency domain consideration, the frequency domain correlation value is calculated, and the reasonable threshold is determined.
In the step (4), SSS frequency domain correlation is specifically:
in the same SS/PBCH block (SSB), SSS occupies the second symbol behind PSS, takes time domain data of the symbol where SSS is located, obtains frequency domain data through fast Fourier transform FFT, and then respectively meets the possibility of PSS detection in 1008 locally generated SSS sequencesThe required partial sequences are correlated and the maximum is calculated. That is, only the satisfaction ofPCI∈{0,1,…1007}，/>Is a sequence of (a). To reduce the effects of frequency offset and noise interference, the correlation computation of the SSS may be performed in segments.
The SSS-related threshold determination in step (5) is specifically:
dividing the square of the SSS sequence correlation accumulation result of each cell by the square of the receiving end baseband SSS frequency domain data to obtain a final result, and determining an absolute threshold value to screen whether the strongest cell passes the threshold.
And (7) calculating and compensating the intermediate frequency offset, which specifically comprises the following steps:
the SSS channel estimation value is a set of 127 complex sequences, which can also be regarded as a set of sampling points with a sampling rate of the subcarrier spacing SC, and are approximately distributed on a circle (arc) due to the influence of frequency offset, instead of being aggregated on the same point (the result in the absence of frequency offset). Calculating the position p of peak power through fast Fourier transform FFT processing of more than 127 points, and considering the resolution bandwidthWherein FFT size The FFT size is known as Δf=p× rbw.
The frequency offset compensation formula is:
R′(m)＝R(m)×e -j2πΔfkTc ；
where R' (m) is the baseband data after compensation, R (m) is the original received baseband data, Δf is the frequency offset value, k is the chip number, and Tc is the chip interval.
The step (8) further comprises the following steps:
(8.1) carrying out equalization processing on the SSS channel estimation value after the frequency offset compensation, and reducing the influence of noise and interference;
(8.2) reconstructing SSS frequency domain data within the receiver-side band data using the equalized SSS channel estimate;
(8.3) performing inverse Fourier transform (IFFT) on the SSS frequency domain data in the receiving end baseband data to obtain SSS time domain data;
(8.4) subtracting the reconstructed SSS time domain data comprising the data of the symbol where the SSS is located and the data of the cyclic prefix at the position corresponding to the SSS time domain data in the receiving end band data to obtain new receiving end band data for subsequent cell detection.
In a specific embodiment of the present invention, the method for NR downlink multi-cell detection in the mobile communication system includes the following steps:
1) The sampling rate fs=30.72 MHz, the subcarrier spacing sc=30 khz, FFT and IFFT size FFT are formulated size (IFFT size ) =1024, respectively generates 3 kinds ofThe sequence and time domain data of the primary synchronization signal PSS are represented, and the sequence and time domain data of the secondary synchronization signal SSS are generated by 1008 kinds of physical cells PCI, respectively. The formula is as follows:
physical cell
PSS sequence generation is performed according to the following formula:
d PSS (n)＝1-2x(m)……(1)
wherein,
x(i+7)＝(x(i+4)+x(i))mod2，[x(6)x(5)x(4)x(3)x(2)x(1)x(0)]＝[1 1 1 0 1 1 0]。
through inverse Fourier transform IFFT (IFFT) size =1024) transforms the above PSS sequence to the time domain.
SSS sequence generation is performed according to the following formula:
d SSS (n)＝[1-2x 0 ((n+m 0 )mod127)][1-2x 1 ((n+m 1 )mod127)]… … (2) wherein,
x 0 (i+7)＝(x 0 (i+4)+x 0 (i))mod2，x 1 (i+7)＝)x 1 (i+1)+x 1 (i))mod2，
[x 0 (6)x 0 (5)x 0 (4)x 0 (3)x 0 (2)x 0 (1)x 0 (0)]＝[0 0 0 0 0 1]，
[x 1 (6)x 1 (5)x 1 (4)x 1 (3)x 1 (2)x 1 (1)x 1 (0)]＝[0 0 0 0 0 1]。
through inverse Fourier transform IFFT (IFFT) size =1024) transforms the SSS sequence to the time domain.
2) Extracting the baseband data sampled by the receiving end for 25ms (the time length of the baseband data of the receiving end is required to be ensured to be longer than one period of SSB), and respectively using 3 types of the dataRepresentative PSS time domain data and whole 25ms receiving end baseband dataSliding correlation, determining the position and possible presence of the point with the greatest correlation value>Types. The correlation calculation is performed according to the following formula:
C n ＝L n ·R′ n ……(3)
wherein C is n Is PSS time domain correlation result, L n Is to generate PSS time domain data locally, R' n Is the conjugation of the receiving end band data. To reduce the effects of frequency offset and noise interference, the relevant computation of the PSS may be segmented. Determining a correlation peak-to-average ratio threshold G-PAPR, e.g., 0.4 times, against a relatively small number of low thresholds in step 3) to screen for possible presence
3) The PSS correlation values of all points within 25ms are calculated and recorded to obtain an average value of the correlation values of all points, the correlation values of all points are divided by the average value, and an appropriate threshold value is confirmed so that the value of the peak-to-average ratio PAPR is greater than the threshold and the values of other points are generally less than the threshold, for example, the time domain correlation peak-to-average ratio threshold G-papr=6. Or from the frequency domain consideration, calculating the frequency domain correlation value at the PSS peak point for determining the threshold. Comparing the calculated PSS peak-to-average ratio PAPR with a peak-to-average ratio threshold G-PAPR value, if the value is larger than the threshold G-PAPR value, the primary synchronization is successful, otherwise, the primary synchronization is failed;
4) After the primary synchronization is successful, according to the relative position relation between the SSS and the PSS, namely in the same SS/PBCH block (SSB), the SSS occupies the second symbol behind the PSS, time domain data of the SSS are extracted, fast Fourier transform FFT is carried out to obtain frequency domain data, and then the frequency domain data are respectively matched with 1008 locally generated SSS sequences to meet the possibility of PSS detectionThe desired partial sequences are correlated and the maximum value is found. I.e. only detection of fulfilment +.>PCI∈{0,1,…1007}，Is a sequence of (a). To reduce the effects of frequency offset and noise interference, the correlation computation of the SSS may be performed in segments, e.g., SSS sequences of length 127 may be computed in 4 segments, the first 3 segments 32 and the last 1 segment 31. By examining the characteristics of each SSS sequence, it can be found that the number of 1's and-1's in the 32 points of the segment is approximately equivalent, which ensures orthogonality of the relevant data.
5) Dividing the square of the correlation accumulation result of the segmented SSS sequence by the square of the segmented SSS frequency domain data of the baseband of the receiving end to obtain a final result, and determining an absolute threshold value to screen whether the strongest cell passes the threshold. The sum of the squares of the correlation between the 32 local SSS sequences and the corresponding 32 data in the receiving end band data is divided by the sum of the squares of the corresponding 32 data in the receiving end band data, the theoretical maximum value is 32, and a reasonable threshold value is determined by considering the signal to noise ratio, for example, the threshold value is defined as G-SSS-32=4. Only the SSS correlation value of the current segment passes the threshold and the next segment is continuously calculated, and only the SSS correlation value of the 4 segments passes the threshold, the current detected physical cell is considered to exist.
6) After the secondary synchronization is successful, the PCI of the physical cell with the strongest signal in the current baseband data can be determined to be the PCI corresponding to the maximum SSS related value;
7) The SSS channel estimation value is a set of 127 complex sequences, which can also be regarded as a set of sampling points with a sampling rate of the subcarrier spacing SC, and are approximately distributed on a circle (arc) due to the influence of frequency offset, instead of being aggregated on the same point (the result in the absence of frequency offset). Calculating the position p of peak power through fast Fourier transform FFT processing of more than 127 points, and considering the resolution bandwidthWherein FFT size The FFT size is known as Δf=p× rbw. The frequency offset compensation formula is:
R′(m)＝R(m)×e -j2πΔfkTc ……(4)
where R' (m) is the baseband data after compensation, R (m) is the original received baseband data, Δf is the frequency offset value, k is the chip number, and Tc is the chip interval.
8) The inverse Fourier transform IFFT obtains SSS time domain data of the strongest PCI in the baseband of the receiving end, and then the SSS time domain data is subtracted from the corresponding position of the baseband data of the receiving end. The method specifically comprises the following steps:
8.1 Performing equalization processing on the SSS channel estimation value after frequency offset compensation, and reducing the influence of noise and interference;
8.2 Reconstructing SSS frequency domain data within the receiver baseband data using the equalized SSS channel estimates;
8.3 Performing inverse Fourier transform (IFFT) on the SSS frequency domain data in the receiving end baseband data to obtain SSS time domain data;
8.4 Subtracting the reconstructed SSS time domain data at the position corresponding to the SSS time domain data in the receiving end band data, wherein the reconstructed SSS time domain data comprises the data of the symbol where the SSS is located and the data of the cyclic prefix, and obtaining new receiving end band data.
9) Detecting the strongest PCI at the position corresponding to SSS in the new receiving end band data again, and jumping to step 4) to continue processing until the secondary synchronization fails.
In practical application, different stations of the 5GNR are synchronous systems, namely, different base stations are timing synchronous through a satellite system, and consistency of data transmission time is guaranteed. Thus, the physical cells of different base stations are theoretically identical in location within the received baseband data, but due to the complexity of the air interface transmission, the locations between different cells may often be offset by a small amount. To achieve better results, cell search may be performed within a segment of the data window near the primary synchronization strongest point, rather than being limited to a single strongest point.
The invention provides a rapid and efficient method for NR downlink multi-cell detection, which is suitable for a complex electromagnetic environment, and can effectively reduce the influence of co-channel interference by separating data of a strongest cell auxiliary synchronization signal SSS for multiple times. Meanwhile, the characteristics of the SSS sequence are fully considered in the algorithm design, and the segmentation judgment threshold is calculated in a segmentation mode, so that the system operation time and hardware cost are reduced, the real-time performance of algorithm realization is enhanced, and the environment using capability is high.
The specific implementation manner of this embodiment may be referred to the related description in the foregoing embodiment, which is not repeated herein.
It is to be understood that the same or similar parts in the above embodiments may be referred to each other, and that in some embodiments, the same or similar parts in other embodiments may be referred to.
It should be noted that in the description of the present invention, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present invention, unless otherwise indicated, the meaning of "plurality" means at least two.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and further implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution device. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
Those of ordinary skill in the art will appreciate that all or part of the steps carried out in the method of the above embodiments may be implemented by a program to instruct related hardware, and the corresponding program may be stored in a computer readable storage medium, where the program when executed includes one or a combination of the steps of the method embodiments.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing module, or each unit may exist alone physically, or two or more units may be integrated in one module. The integrated modules may be implemented in hardware or in software functional modules. The integrated modules may also be stored in a computer readable storage medium if implemented as software functional modules and sold or used as a stand-alone product.
The above-mentioned storage medium may be a read-only memory, a magnetic disk or an optical disk, or the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The method, the device, the processor and the computer readable storage medium for realizing NR downlink multi-cell detection processing in the mobile communication system are suitable for rapidly analyzing NR downlink multi-cells, analyzing signal quality and carrying out network optimization in a complex electromagnetic environment. The data of the secondary synchronization signal SSS of the strongest cell is separated for multiple times, so that the influence of the same-frequency interference can be effectively reduced. Meanwhile, the characteristics of the SSS sequence are fully considered in the algorithm design, and the segmentation judgment threshold is calculated in a segmentation mode, so that the system operation time and hardware cost are reduced, and the real-time performance of algorithm implementation is enhanced.
In this specification, the invention has been described with reference to specific embodiments thereof. It will be apparent, however, that various modifications and changes may be made without departing from the spirit and scope of the invention. The specification and drawings are, accordingly, to be regarded in an illustrative rather than a restrictive sense.
Claims (10)
1. A method for implementing NR downlink multi-cell detection processing in a mobile communication system, the method comprising the steps of:
(1) Generating primary synchronization signal data and secondary synchronization signal data respectively;
(2) Extracting baseband data sampled by a receiving end, and performing main synchronous sliding correlation;
(3) Determining a threshold of the main synchronization correlation, comparing the calculated maximum correlation value of the main synchronization signal with the threshold of the main synchronization correlation, and if the maximum correlation value of the main synchronization signal is larger than the threshold, successfully synchronizing the main synchronization; otherwise, the main synchronization fails, and the step is ended;
(4) Performing auxiliary synchronization correlation to obtain the maximum value of auxiliary synchronization signal correlation;
(5) Determining a threshold of auxiliary synchronization correlation, comparing the calculated maximum correlation value of the auxiliary synchronization signal with the threshold of auxiliary synchronization correlation, and if the maximum correlation value of the auxiliary synchronization signal is greater than the threshold, successfully carrying out auxiliary synchronization; otherwise, the auxiliary synchronization fails, and the step is ended;
(6) Determining a physical cell with the strongest signal in the current baseband data, namely a physical cell corresponding to the largest auxiliary synchronization related value;
(7) Calculating an auxiliary synchronous channel estimated value of the strongest physical cell, and calculating a frequency offset value according to the sampling rate and the subcarrier interval, and performing frequency offset compensation on the baseband data of the receiving end;
(8) Reconstructing the auxiliary synchronous frequency domain data of the strongest physical cell, obtaining time domain data by inverse Fourier transformation, and subtracting the auxiliary synchronous time domain data of the physical cell from the corresponding position of the receiving end band data;
(9) Detecting the strongest physical cell at present, continuing the step (5) until the secondary synchronization fails;
the step (3) of determining the threshold related to the primary synchronization specifically comprises the following steps:
calculating and recording the main synchronous signal related values of all points in the sliding window to obtain the average value of the related values of all points; dividing all the point correlation values by the average value, and confirming a threshold value according to the current signal-to-noise ratio so that the peak-to-average ratio value is larger than the threshold value and the other point correlation values are smaller than the threshold value;
the step (5) of determining the threshold related to the secondary synchronization specifically comprises the following steps:
and calculating the square of the accumulation result of the correlation values of the secondary synchronization sequences of the cells, dividing the square of the secondary synchronization frequency domain data of the base band of the receiving end, and determining the threshold value of the secondary synchronization correlation.
2. The method for implementing NR downlink multi-cell detection process in a mobile communication system according to claim 1, wherein said step (2) specifically comprises the steps of:
and extracting baseband data sampled by the receiving end, respectively using a main synchronous signal to carry out sliding correlation with the baseband data of the receiving end, and determining the position of the point with the maximum correlation value.
3. The method for implementing NR downlink multi-cell detection process in a mobile communication system according to claim 1, wherein said step (4) specifically comprises the steps of:
and extracting data of the auxiliary synchronization signal according to the relative position relation between the main synchronization signal and the auxiliary synchronization signal, performing fast Fourier transform to obtain frequency domain data, and performing correlation calculation with part of auxiliary synchronization signal sequences respectively to obtain the maximum value of auxiliary synchronization signal correlation.
4. The method for implementing NR downlink multi-cell detection processing in a mobile communication system according to claim 1, wherein in the step (2), a primary synchronization sliding correlation is performed, specifically:
the primary synchronization sliding correlation is performed according to the following formula:
C n ＝L n ×R ′ n ；
wherein the method comprises the steps of，C n L is the PSS time domain correlation result n For locally generating PSS time domain data, R ′ n Conjugation to receive end band data.
5. The method for implementing NR downlink multi-cell detection processing in a mobile communication system according to claim 1, wherein the calculating a frequency offset value in the step (7) specifically includes:
calculating the frequency offset value according to the following formula:
Δf＝p×rbw；
where p is the location of peak power, rbw is the resolution bandwidth,FFT size is the size of the FFT.
6. The method for implementing NR downlink multi-cell detection processing in a mobile communication system according to claim 1, wherein the step (7) performs frequency offset compensation, specifically includes:
frequency offset compensation is performed according to the following formula:
R ′ (m)＝R(m)×e -j2πΔfkTc ；
wherein R is ′ (m) is the baseband data after compensation, R (m) is the original received baseband data, deltaf is the frequency offset value, k is the chip sequence number, and Tc is the chip interval.
7. The method for implementing NR downlink multi-cell detection process in a mobile communication system according to claim 1, wherein said step (8) comprises the steps of:
(8.1) carrying out equalization treatment on the auxiliary synchronous channel estimation value after the frequency offset compensation;
(8.2) reconstructing the secondary synchronization frequency domain data in the receiving end group band data through the balanced secondary synchronization channel estimation;
(8.3) performing inverse Fourier transform on the frequency domain data of the auxiliary synchronizing signal in the receiving end baseband data to obtain the time domain data of the auxiliary synchronizing signal;
and (8.4) subtracting the time domain data of the reconstructed auxiliary synchronous signal from the position corresponding to the time domain data of the auxiliary synchronous signal in the receiving end band data to obtain new receiving end band data.
8. An apparatus for implementing NR downlink multi-cell detection processing in a mobile communication system, the apparatus comprising:
a processor configured to execute computer-executable instructions;
a memory storing one or more computer-executable instructions which, when executed by the processor, perform the steps of the method of performing NR downlink multi-cell detection processing in a mobile communication system as claimed in any one of claims 1 to 7.
9. A processor for implementing an NR downlink multi-cell detection process in a mobile communication system, wherein the processor is configured to execute computer executable instructions that, when executed by the processor, implement the steps of the method for implementing an NR downlink multi-cell detection process in a mobile communication system according to any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon a computer program executable by a processor to perform the steps of the method of implementing NR downlink multi-cell detection processing in a mobile communication system according to any of claims 1 to 7.
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