CN114584232A - Wireless communication sub-band signal-to-noise ratio measuring method based on channel detection reference signal - Google Patents

Wireless communication sub-band signal-to-noise ratio measuring method based on channel detection reference signal Download PDF

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CN114584232A
CN114584232A CN202210144139.8A CN202210144139A CN114584232A CN 114584232 A CN114584232 A CN 114584232A CN 202210144139 A CN202210144139 A CN 202210144139A CN 114584232 A CN114584232 A CN 114584232A
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CN114584232B (en
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刘雨洋
逯利军
钱培专
许闱帷
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Beijing Certusnet Information Technology Co ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B17/00—Monitoring; Testing
    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/382—Monitoring; Testing of propagation channels for resource allocation, admission control or handover
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04L25/0202—Channel estimation
    • H04L25/022—Channel estimation of frequency response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
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Abstract

The invention discloses a method for measuring the signal-to-noise ratio of a wireless communication sub-band based on a channel sounding reference signal, which comprises the following steps: (10) acquiring a time domain channel response estimated value, (20) acquiring a time domain channel response value of each user, (30) acquiring signal power, (40) calculating noise power in a noise window, (50) suppressing noise, (60) acquiring effective signal power, (70) acquiring noise signal amplitude, (80) acquiring broadband noise signal power and (90) calculating a sub-band signal-to-noise ratio. The method for measuring the signal-to-noise ratio of the wireless communication sub-band based on the channel detection reference signal can measure the signal-to-noise ratio of the sub-band when the signal-to-noise ratio is higher, and can provide the signal-to-noise ratio of the sub-band for a scheduling layer, thereby performing an uplink frequency selection function.

Description

Wireless communication sub-band signal-to-noise ratio measuring method based on channel detection reference signal
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a wireless communication sub-band signal-to-noise ratio measuring method based on a channel sounding reference signal.
Background
With the continuous deepening of the 3G, 4G and 5G network construction, the network structure is gradually complicated, the users are gradually increased, and the requirement of the internet experience of the users is higher and higher. At present, on one hand, in a transmission process, frequency selective fading occurs to signals, which causes great difference in received signal quality of different Physical Resource Blocks (PRBs); on the other hand, the different transmission powers of UEs in different cells with the same frequency interfere with each other on the same PRB, so that the co-frequency interference suffered by different PRBs is also different, and thus, the spectrum efficiency of some PRBs may be reduced, thereby reducing the user experience.
In a wireless communication system, an eNB uses an SRS (Sounding Reference Signal) to estimate uplink channel quality of a UE (User Equipment, terminal) in different frequency bands. The DMRS only has frequency domain resources scheduled by the UE and is used for UE demodulation; since the SRS is the frequency domain resource of the whole cell, it is convenient for the mac layer to allocate the frequency domain resource with higher Signal to Interference plus Noise Ratio (SINR) to the UE. The traditional method is to use Least Square (LS) algorithm to calculate the signal-to-noise ratio of the whole broadband, and there is no clear method for the signal-to-noise ratio of the sub-band.
For example, chinese patent application No. 202110534269.8 discloses a method for optimizing noise reduction of channel estimation response based on SRS signals. The method comprises the following steps:
step 1, SRS frequency domain signal extraction: the base station extracts frequency domain data SRS _ CHE _ IN1 corresponding to the SRS signal mapping position according to the uplink frequency domain data YForData and the SRS configuration parameters, and the dimensionality is SRS _ SC _ Num + iSymb + iRxAnt, wherein the SRS _ SC _ Num is the number of REs occupied by the SRS, the iSymb is the number of symbols occupied by the SRS, and the iRxAnt is the number of antennas of the base station;
step 2, generating an SRS mother code local sequence: the base station generates an SRS signal mother code local sequence RBAR according to parameter configuration, wherein the SRS _ SC _ Num is iSymb and iPornu, the SRS _ SC _ Num is the number of REs occupied by the SRS, the iSymb is the number of symbols occupied by the SRS, and the iPornu is the number of all ports of the code division at the frequency domain position;
and 3, acquiring a frequency domain channel response estimation value: according to the SRS frequency domain data YSRS and the mother code sequence RBAR, performing conjugate multiplication by using a least square method criterion to obtain a frequency domain channel estimation response Hls;
and 4, acquiring a time domain channel response estimation value: and performing Inverse Fast Fourier Transform (IFFT) on the frequency domain channel estimation response Hls to obtain a time domain channel estimation response:
step 5, noise suppression treatment: carrying out noise suppression processing on the time domain channel estimation response; the noise reduction treatment comprises in-window noise reduction and out-window noise reduction, W is a window coefficient, the whole window length is divided into a front window, a middle window and a rear window, and noise suppression operation is respectively carried out to obtain a signal after noise suppression.
Step 6, performing FFT on the time domain response after noise suppression: performing Fast Fourier Transform (FFT) on the denoised time domain channel estimation response to obtain a finally required denoised frequency domain channel estimation response pCEdftOut;
the method does not further calculate the signal-to-noise ratio of the sub-band, and does not provide a calculation method for calculating the signal-to-noise ratio of the sub-band, so that a scheduling layer does not obtain the measured value of the signal-to-noise ratio of the sub-band and cannot perform an uplink frequency selection function.
Disclosure of Invention
The invention aims to provide a method for measuring the signal-to-noise ratio of a wireless communication sub-band based on a channel detection reference signal, which can measure the signal-to-noise ratio of the sub-band when the signal-to-noise ratio is high and can provide the signal-to-noise ratio of the sub-band for a scheduling layer so as to perform an uplink frequency selection function.
The technical solution for realizing the purpose of the invention is as follows:
a wireless communication sub-band signal-to-noise ratio measuring method based on a channel sounding reference signal comprises the following steps:
(10) acquiring a time domain channel response estimation value: carrying out complex conjugate multiplication on SRS frequency domain signals extracted from uplink frequency domain data of all users and an SRS mother code local sequence generated according to configuration parameters issued by a scheduling layer to obtain frequency domain channel response estimation values of all users; carrying out IDFT (inverse discrete Fourier transform) on the frequency domain channel response estimation value to obtain time domain channel response estimation values of all users;
(20) acquiring a time domain channel response value of each user: acquiring a channel estimation value of each user in a corresponding channel estimation window according to the cyclic shift value of each user to obtain time domain channel response values of all users;
(30) signal power acquisition: in the signal power signal window of each port of each user, calculating the instantaneous power value of each response in each signal window, and taking the maximum value as the signal power; the signal power signal window is determined according to the displacement factor;
(40) noise power calculation within the noise window: calculating the average noise power in the noise window according to the time domain response results of all signals in the noise window; the noise window is obtained by obtaining the noise window ending position according to the noise window starting position and the noise window ending position;
(50) noise suppression: comparing the instantaneous signal power of each point in each user initial signal window with a noise threshold, and filtering out a signal lower than the noise threshold as noise to obtain an effective signal;
(60) effective signal power acquisition: performing DFT transformation on the effective signal to obtain a noise suppression frequency domain channel response estimation amplitude, and performing square calculation on the noise suppression frequency domain channel response amplitude to obtain effective signal power;
(70) noise signal amplitude acquisition: subtracting the estimated frequency domain channel response value from the estimated noise suppression frequency domain channel response amplitude value to obtain a noise signal amplitude value;
(80) broadband noise signal power acquisition: carrying out square calculation on the amplitude of the noise signal to obtain broadband noise power;
(90) and (3) calculating the signal-to-noise ratio of the sub-band: and dividing the effective signal power by the broadband noise power to obtain a sub-band signal-to-noise ratio.
Compared with the prior art, the invention has the following remarkable advantages:
the invention discloses a method for calculating the signal-to-noise ratio of a sub-band based on the original calculation of the signal-to-noise ratio of a broadband, which is characterized in that an uplink PRB is divided into different sub-bands, for example, 4 PRBs are divided into one sub-band, a physical layer can calculate the average signal-to-noise ratio of each sub-band and report the average signal-to-noise ratio to a scheduling layer, an eNB selects the sub-band with the optimal channel quality for each UE respectively according to the sub-band reporting result of each UE to upload data, selects a proper Modulation and Coding Scheme (MCS) grade for different UEs to schedule, and can preferentially schedule the PRB with the high signal-to-noise ratio in a frequency domain to demodulate under the condition of small PRB configuration of a PUSCH channel.
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
Drawings
Fig. 1 is a main flow chart of a method for measuring a signal-to-noise ratio of a wireless communication sub-band based on a channel sounding reference signal according to the present invention.
Fig. 2 is a diagram of matlab simulation of the time domain channel response estimate acquisition step in fig. 1. Wherein, the configuration 1 is the time domain response of the channel estimation, the configuration 2 and the configuration 4 are the time domain responses obtained from different users respectively, and the configuration 3 and the configuration 5 are the time domain responses filtered from the noise of the corresponding different users.
Fig. 3 and fig. 4 are diagrams of matlab simulation results without noise and with noise, wherein the rules 1-4 correspond to the received frequency domain signal SRS _ CHE _ IN1, the time domain channel estimation result hls before noise suppression, the time domain channel estimation result hls' after noise suppression, and the signal-to-noise ratio measurement result of the sub-band.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments, it being understood that the embodiments and features of the embodiments of the present application can be combined with each other without conflict.
As shown in fig. 1, the method for measuring the signal-to-noise ratio of the wireless communication sub-band based on the channel sounding reference signal of the present invention includes the following steps:
(10) acquiring a time domain channel response estimation value: carrying out complex conjugate multiplication on SRS frequency domain signals extracted from uplink frequency domain data of all users and an SRS mother code local sequence generated according to configuration parameters issued by a scheduling layer to obtain frequency domain channel response estimation values of all users; carrying out IDFT (inverse discrete Fourier transform) on the frequency domain channel response estimation value to obtain time domain channel response estimation values of all users;
as shown in fig. 2, the (10) time domain channel response estimation value obtaining step includes:
(11) and (3) extracting SRS frequency domain signals: extracting channel Sounding Reference Signal (SRS) frequency domain signals from all user uplink frequency domain data received by a base station side;
YFreData is user uplink frequency domain data received by the base station; according to the initial position k of Sounding reference signal sequence frequency domain of each port of each user0And length of Sounding reference signal
Figure BDA0003507986350000041
The SRS configuration parameter information is waited for extracting a frequency domain receiving signal SRS _ CHE _ IN1 of Sounding pilot frequency; the dimensionality is SRS _ SC _ Num _ iSymb _ iRxAnt, wherein the SRS _ SC _ Num is the number of REs occupied by the SRS, the iSymb is the number of symbols occupied by the SRS, and the iRxAnt is the number of antennas of the base station;
(12) generating an SRS mother code local sequence: generating a channel Sounding Reference Signal (SRS) mother code local sequence according to configuration parameters issued by a scheduling layer;
a base station generates an SRS signal mother code local sequence RBAR, and the dimensionality SRS _ SC _ Num is iSymb and iPornum, wherein the SRS _ SC _ Num is the number of REs occupied by SRS, the iSymb is the number of symbols occupied by SRS, and the iPornum is the number of all ports of the code division at the frequency domain position;
(13) obtaining a frequency domain channel response estimation value: carrying out complex conjugate multiplication on the SRS frequency domain signal and an SRS mother code local sequence to obtain frequency domain channel response estimated values of all users;
complex conjugate multiplication is carried out on the SRS frequency domain signal SRS _ CHE _ IN1 and a base sequence RBAR to obtain a Sounding pilot frequency position channel estimation value Hls and a dimension SRS _ SC _ Num _ iSymb _ iRxAnt;
(14) calculating a time domain channel response estimation value: the frequency domain channel response estimation value is subjected to IDFT to obtain time domain channel response estimation values of all users;
IDFT of the corresponding length points of Hls is transformed, namely, the frequency domain channel estimation value is transformed into a time domain channel estimation value Hls through IDFT;
(20) acquiring a time domain channel response value of each user: acquiring a channel estimation value of each user in a corresponding channel estimation window according to the cyclic shift value of each user, thereby obtaining time domain channel response values of all users;
and acquiring the time domain channel response of each user, namely acquiring the channel estimation result of the user in a corresponding channel estimation window according to the cyclic shift value of the user.
Kth ofUEDisplacement factor of p-th port of individual user
Figure BDA0003507986350000051
Calculated from the following formula:
Figure BDA0003507986350000052
wherein
Figure BDA0003507986350000053
Is the maximum number of cyclic shifts, when KTCWhen 2 is true
Figure BDA0003507986350000054
When K isTCWhen equal to 4
Figure BDA0003507986350000055
Figure BDA0003507986350000056
Given by the high-level parameter SRS-cyclic shiftconfig.
Port number ipBy
Figure BDA0003507986350000057
It is determined that,
Figure BDA0003507986350000058
the number of Ports supported for SRS is given by the higher layer parameter NrofSRS-Ports.
(30) Calculating the maximum value of the instantaneous power: in the signal power signal window of each port of each user, calculating the instantaneous power value of each response in each signal window, and taking the maximum value as the signal power; the signal power signal window is determined according to the displacement factor;
the (30) instantaneous power maximum value obtaining step includes:
(31) determining a signal power signal window: determining a signal power signal window of each port of each user according to the displacement factor;
the step (31) of determining the signal power signal window specifically comprises the following steps:
k th, kUEWindow taking interval of p-th port of user
Figure BDA0003507986350000059
Determined as follows:
Figure BDA00035079863500000510
Figure BDA00035079863500000511
Figure BDA00035079863500000512
wherein SRSRBFor the PRB number of SRS signals, N _ SC _ PER _ PRB is set as 12 by default, Comb is the configuration of higher layer, and can be 2 or4, the other two are shown in the figure; windinitIs the initial signal window.
(32) Calculating the signal power:
within the signal window, calculating the instantaneous power value of each response in each signal window, and selecting the maximum value as the final signal power Psignal，max。
The step (32) of calculating the signal power specifically comprises:
calculating instantaneous power value P within signal windowsignal(i) And selects the maximum value Psignal，max；
Psignal(i)＝(real(hls))2+(imag(hls))2
Psignal，max＝max(Psignal(i))
(40) Calculating the noise power in the noise window: calculating the average noise power in the noise window according to the time domain response results of all signals in the noise window; the noise window is obtained by obtaining the noise window ending position according to the noise window starting position and the noise window ending position;
said (40) noise power within noise window calculating step comprises:
(41) noise window calculation: obtaining a noise window according to the starting position and the ending position of the noise window;
starting position nNosie of noise window start7 nWinSize/12, the end position of the noise window is
nNoiseend＝nNoisestart+ nWinSize/12, wherein
Figure BDA0003507986350000061
(42) Noise power calculation within the noise window: calculating the average noise power Pnosie in the noise window according to the time domain response results of all signals in the noise window, wherein the calculation formula of the noise power is shown in a signal power formula;
(50) noise suppression: comparing the instantaneous signal power of each point in each user initial signal window with a noise threshold, and filtering out a signal lower than the noise threshold as noise to obtain an effective signal;
the (50) noise suppressing step comprises:
(51) determining the noise threshold, and taking 0.72 × Psignal，maxAnd th Pnosie as the noise threshold. th is a window access threshold, generally 9;
(52) and (3) effective signal acquisition: the instantaneous signal power P of each point in each user initial signal windowsignal(i) Is compared with a threshold value gate if
Psignal(i)＞gate
Hls is considered to be a valid signal and otherwise considered to be noise, 0 is concatenated and the stored noise-suppressed result is designated hls'.
(60) Effective signal power acquisition: performing DFT transformation on the effective signal to obtain a noise suppression frequency domain channel response estimation amplitude, and performing square calculation on the noise suppression frequency domain channel response amplitude to obtain effective signal power;
DFT transformation is carried out on the effective signal Hls 'to obtain frequency domain channel response Hls' after noise suppression, and the amplitude of the frequency domain channel response is squared to obtain effective signal power PsignalThis value includes only the signal power. Dimension of
Figure BDA0003507986350000071
Figure BDA0003507986350000072
For SRS sequence length, ant is the number of base station receive antennas.
(70) Noise signal amplitude acquisition: subtracting the frequency domain channel response estimated value from the frequency domain channel response estimated amplitude after noise suppression to obtain a noise signal amplitude;
according to the frequency domain channel response estimated value Hls obtained in the step (13), subtracting the frequency domain channel response estimated amplitude Hls' obtained in the step (102) after noise suppression to obtain a noise signal Hlsnoise；
(80) Broadband noise signal power acquisition: carrying out square calculation on the amplitude of the noise signal to obtain broadband noise power;
the noise signal Hls is converted into a noise signalnoiseAmplitude ofSquare calculation is carried out to obtain broadband noise power P'noise(ii) a Dimension of
Figure BDA0003507986350000073
Figure BDA0003507986350000074
For SRS sequence length, ant is the number of base station receive antennas.
(90) And (3) calculating the signal-to-noise ratio of the sub-band: and dividing the effective signal power by the broadband noise power to obtain a sub-band signal-to-noise ratio.
By signal power PsignalDivided by broadband noise power P'noiseAnd if the signal-to-noise ratio of all antennas on all re is reported according to the signal-to-noise ratio of 4 prb of each sub-band, averaging the signal-to-noise ratio values of 24 re to obtain a result, and finally obtaining the signal-to-noise ratio values of all sub-bands. The Mac layer can preferentially schedule the frequency domain sub-band with high signal-to-noise ratio for the UE according to the sub-band signal-to-noise ratio result reported by the physical layer, so that the demodulation performance of the base station is improved.
Results of the experiment
Measurements were made with the signal source at a low frequency of 50M plus-20 dbm noise, and the expected result was that the value of the noise-added subband sinr would be lower than the value of the noise-added sinr. By comparison, it can be seen that the snr of the noise-free subband in fig. 3 is between 26db and 29db, and in the case of low frequency 50M noise in fig. 2, it can be seen that the snr of the noise-free subband is significantly lower than that of the noise-free subband.

Claims (6)

1. A wireless communication sub-band signal-to-noise ratio measuring method based on a channel detection reference signal is characterized by comprising the following steps:
(10) acquiring a time domain channel response estimation value: carrying out complex conjugate multiplication on SRS frequency domain signals extracted from uplink frequency domain data of all users and an SRS mother code local sequence generated according to configuration parameters issued by a scheduling layer to obtain frequency domain channel response estimation values of all users; carrying out IDFT (inverse discrete Fourier transform) on the frequency domain channel response estimation value to obtain time domain channel response estimation values of all users;
(20) acquiring a time domain channel response value of each user: acquiring a channel estimation value of each user in a corresponding channel estimation window according to the cyclic shift value of each user to obtain time domain channel response values of all users;
(30) signal power acquisition: in the signal power signal window of each port of each user, calculating the instantaneous power value of each response in each signal window, and taking the maximum value as the signal power; the signal power signal window is determined according to the displacement factor;
(40) noise power calculation within the noise window: calculating the average noise power in the noise window according to the time domain response results of all signals in the noise window; the noise window is obtained by obtaining the noise window ending position according to the noise window starting position and the noise window ending position;
(50) noise suppression: comparing the instantaneous signal power of each point in each user initial signal window with a noise threshold, and filtering out a signal lower than the noise threshold as noise to obtain an effective signal;
(60) effective signal power acquisition: performing DFT transformation on the effective signal to obtain a noise suppression frequency domain channel response estimation amplitude, and performing square calculation on the noise suppression frequency domain channel response amplitude to obtain effective signal power;
(70) noise signal amplitude acquisition: subtracting the estimated frequency domain channel response value from the estimated noise suppression frequency domain channel response amplitude value to obtain a noise signal amplitude value;
(80) broadband noise signal power acquisition: squaring the amplitude of the noise signal to obtain broadband noise power;
(90) and (3) calculating the signal-to-noise ratio of the sub-band: and dividing the effective signal power by the broadband noise power to obtain a sub-band signal-to-noise ratio.
2. The method of claim 1, wherein the step of obtaining (10) the time domain channel response estimate comprises:
(11) and (3) extracting SRS frequency domain signals: extracting channel sounding reference signal frequency domain signals from all user uplink frequency domain data received by a base station side;
(12) generating an SRS mother code local sequence: generating a channel sounding reference signal mother code local sequence according to configuration parameters issued by a scheduling layer;
(13) obtaining a frequency domain channel response estimation value: carrying out complex conjugate multiplication on the SRS frequency domain signal and an SRS mother code local sequence to obtain frequency domain channel response estimated values of all users;
(14) calculating a time domain channel response estimation value: and transforming the frequency domain channel response estimation value through IDFT to obtain time domain channel response estimation values of all users.
3. The method of claim 1, wherein said signal power acquisition step (30) comprises:
(31) determining a signal power signal window: determining a signal power signal window of each port of each user according to the displacement factor;
(32) calculating the signal power: and calculating the instantaneous power value of each response in each signal window in the signal power signal window, and selecting the maximum value as the final signal power.
4. The method of claim 3, wherein the step of (31) determining the signal power signal window is specifically:
kthUEWindow taking interval of p-th port of user
Figure FDA0003507986340000021
Determined as follows:
Figure FDA0003507986340000022
Figure FDA0003507986340000023
Figure FDA0003507986340000024
wherein SRSRBThe number of PRB of SRS signals is N _ SC _ PER _ PRB is set to 12 by default, Comb is configured in a higher layer, and may be 2 or 4; windinitIs the initial signal window.
5. The method of claim 4, wherein the step of (32) calculating the signal power is specifically:
calculating instantaneous power value P within signal windowsignal(i) And selecting the maximum value Psignal,max；
Psignal(i)＝(real(hls))2+(imag(hls))2，
Psignal，max＝max(Psignal(i))，
Starting position nNosie of noise windowstart7 nWinSize/12, the end position of the noise window is
nNoiseend＝nNoisestart+ nWinSize/12, wherein
Figure FDA0003507986340000031
6. The method of claim 1, wherein said noise suppression step (50) comprises:
(51) and (3) noise threshold determination: take 0.72 × Psignal，maxThe smaller value of th Pnosie is taken as a noise threshold, th is a window threshold, and is generally taken as 9;
(52) and (3) effective signal acquisition: the instantaneous signal power P of each point in each user initial signal windowsignal(i) Is compared with a threshold gate, if
Psignal(i)＞gate，
Hls is considered to be a valid signal and otherwise considered to be noise, 0 is concatenated and the stored noise-suppressed result is designated hls'.
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