CN115941405A - SNR estimation method and device of 5G small base station system based on SRS - Google Patents

SNR estimation method and device of 5G small base station system based on SRS Download PDF

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CN115941405A
CN115941405A CN202211659946.XA CN202211659946A CN115941405A CN 115941405 A CN115941405 A CN 115941405A CN 202211659946 A CN202211659946 A CN 202211659946A CN 115941405 A CN115941405 A CN 115941405A
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signal
srs
channel estimation
channel
estimation
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赵强
史涛
许秋平
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Shenzhen Guoren Wireless Communication Co Ltd
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Abstract

The invention relates to an SNR estimation method and a device of a 5G small base station system based on SRS, which adopts SRS signals periodically transmitted under a 5G NR communication protocol framework to calculate signal power and noise and adopts a least square method (LS) algorithm to calculate channel estimation response. In addition, the invention also carries out time offset estimation and compensation on the channel response of the SRS signal to obtain more accurate final channel estimation so as to reduce the influence of interference signal noise on the estimation performance and improve the accuracy of signal power calculation, thereby obtaining more accurate SNR estimation value and further improving the communication quality of a 5G small base station system.

Description

SNR estimation method and device of 5G small base station system based on SRS
Technical Field
The invention relates to the technical field of mobile communication, in particular to a method and a device for estimating an SNR (signal to noise ratio) of a 5G small base station system based on an SRS (sounding reference signal).
Background
In a mobile communication 5G small base station system, generally, an SRS (sounding reference signal) is used to measure a Signal Noise Ratio (SNR). SNR refers to estimating and measuring the information and noise power or energy, respectively, in a received signal and calculating the ratio of the information to the noise. The signal-to-noise ratio is an important index for measuring the quality of the mobile communication 5G system. On one hand, the system uses the SNR parameter to measure the channel quality, and on the other hand, the performance of other algorithm modules in the system can be optimized through the SNR parameter. With the rapid development of high-speed communication systems, the requirements on SNR estimation are also higher and higher, and requirements on higher accuracy, better performance, simpler calculation and easier implementation are also met.
At present, a method for calculating an SNR estimation by a 5G small cell site system is a Maximum Likelihood (Maximum Likelihood) estimation method, which calculates a channel estimation response H by using a received frequency domain signal y and using a least square (ls) algorithm, and then calculates a signal noise Ni by using y-H × x (x is a locally generated SRS sequence signal). Finally, the signal-to-noise ratio SNR = H × x/(y-H × x). Due to the design specification requirements and performance considerations of the 5G small station system, when SRS parameters are configured, inter-frequency interference is considered, a 2-comb configuration is adopted, and at this time, the SRS transmitted by the user is configured as comb4, and the value of the comb offset combOffset is 0,2 (namely, the RE at the positions 0,2,4,6,8, 10 in each RB is an SRS signal, and the RE at the positions 1,3,5,7,9, 11 is an interference signal). Thus, over the entire bandwidth, only the SRS signal is present on top, and the data on all the base carriers is noise-backed. The configuration can stagger the effective data in the frequency domain mapping, thereby reducing the inter-frequency interference and ensuring the performance requirement. In practical tests, the problem that SNR measurement is inaccurate due to the fact that the channel estimation response H calculated by the traditional LS least square algorithm is not accurate enough in the scene with large time offset is found. Therefore, the more accurate the channel estimation response calculation is, the more accurate the SNR calculation is, and the more important the performance improvement of the whole 5G small base station system is.
Therefore, it is desirable to provide a method and apparatus for estimating SNR with more accurate channel estimation.
Disclosure of Invention
The invention aims to solve the technical problem of providing an SNR estimation method and device of a 5G small base station system based on SRS, which has more accurate channel estimation.
In order to solve the above technical problem, the present invention provides a method for estimating SNR of a 5G small cell base station system based on SRS, which comprises the following steps:
s1, extracting an SRS measuring signal Y' SRS (k, l, r) from received frequency domain data; wherein k is a subcarrier index of a received SRS signal, l is an OFDM symbol, and r is a receiving antenna;
s2, generating a local occurrence sequence Xsrs (k, l, p) according to a 3GPP protocol; wherein, p is the index of the transmitting antenna port;
s3, calculating to obtain a coarse channel estimation based on a least square estimation algorithm according to the SRS measuring signal Y' SRS (k, l, r) and the local occurrence sequence Xsrs (k, l, p)
Figure 275213DEST_PATH_IMAGE001
；
S4, estimating the coarse channel
Figure 302074DEST_PATH_IMAGE001
Performing continuous Nm subcarrier smoothing interference-removing processing to obtain intermediate channel estimation
Figure 628014DEST_PATH_IMAGE002
；
Wherein, the
Figure 530155DEST_PATH_IMAGE003
，
Figure 650558DEST_PATH_IMAGE004
Is the port number of the SRS, nu is the number of users,
Figure 430295DEST_PATH_IMAGE005
s5, estimating by using the intermediate channel
Figure 294346DEST_PATH_IMAGE006
Estimating the time offset to obtain the time offsetThe value TA;
s6, estimating the intermediate channel according to the time offset value TA
Figure 577560DEST_PATH_IMAGE006
And the SRS measuring signal Y' SRS (k, l, r) is subjected to time offset compensation to obtain a compensation channel estimation
Figure 383711DEST_PATH_IMAGE007
And compensating the measurement signal Ysrs (k, l, r);
s7, estimating the compensation channel according to an MMSE (minimum mean square error) equalization algorithm
Figure 385165DEST_PATH_IMAGE008
Carrying out interpolation filtering processing to obtain covariance matrixes theta (k) and MMSE matrixes phi (k') among different subcarriers at different moments;
s8, calculating a weight w (k, l; k ', l ') according to the covariance matrix theta (k) and the MMSE matrix phi (k '), and estimating the compensation channel according to the weight w (k, l; k ', l ')
Figure 787327DEST_PATH_IMAGE008
Performing RE-level interpolation operation to obtain final channel estimation
Figure 925048DEST_PATH_IMAGE006
；
S9, estimating according to the final channel
Figure 918411DEST_PATH_IMAGE009
And said locally occurring sequence Xsrs (k, l, p) calculates the signal power Pu over the frequency band; based on the compensated measurement signal Ysrs (k, l, r), the final channel estimate
Figure 626736DEST_PATH_IMAGE009
And said locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the frequency band;
s10, according to the signal power Pu on the frequency band and the noise power Ni on the frequency band, calculating formula based on signal-to-noise ratio
Figure 98168DEST_PATH_IMAGE010
Determining an intermediate signal-to-noise ratio SNR';
s11, according to the intermediate signal-to-noise ratio SNR' and the covariance matrix
Figure 355974DEST_PATH_IMAGE011
To obtain a new MMSE matrix
Figure 989081DEST_PATH_IMAGE012
(ii) a And then, returning to the step S6 to perform sequential stepwise calculation again until the step S8 obtains the final signal-to-noise ratio SNRest according to the signal-to-noise ratio calculation formula.
2. The SRS-based 5G small cell base station system SNR estimation method of claim 1, wherein the step S3 further includes:
the coarse channel estimation
Figure 699548DEST_PATH_IMAGE001
=
Figure 223939DEST_PATH_IMAGE013
。
Further, the step S4 further includes:
the intermediate channel estimation
Figure 70672DEST_PATH_IMAGE014
。
Further, the step S5 further includes:
the time offset value TA =
Figure 405839DEST_PATH_IMAGE015
；
Wherein, the first and the second end of the pipe are connected with each other,
Figure 338023DEST_PATH_IMAGE016
；
Figure 416837DEST_PATH_IMAGE017
4096, if two combs are separated, then L =2
Figure 134388DEST_PATH_IMAGE018
If the comb is four combs, then L =4
Figure 109298DEST_PATH_IMAGE018
Angle is an arctangent function;
the step S6 further includes:
the compensated channel estimation
Figure 59936DEST_PATH_IMAGE019
；
The compensated measurement signal Ysrs (k, l, r) =
Figure 411283DEST_PATH_IMAGE020
。
Further, the step S7 further includes:
the covariance matrix
Figure 232608DEST_PATH_IMAGE021
；
Wherein the content of the first and second substances,
Figure 893266DEST_PATH_IMAGE022
for the maximum amount of delay that the channel propagates,
Figure 800042DEST_PATH_IMAGE023
a carrier index value for the entire bandwidth,
Figure 955080DEST_PATH_IMAGE024
is an SRS carrier index value;
the MMSE matrix
Figure 896491DEST_PATH_IMAGE025
(ii) a Wherein the SNR 0 Is the initial signal-to-noise ratio;
in step S11, the new MMSE matrix
Figure 478782DEST_PATH_IMAGE026
。
Further, the step S8 further includes:
the weight value
Figure 889166DEST_PATH_IMAGE027
；
Further, the step S9 further includes:
signal power Pu on the frequency band
Figure 582315DEST_PATH_IMAGE028
(ii) a Wherein, the
Figure 378233DEST_PATH_IMAGE029
Said
Figure 397005DEST_PATH_IMAGE030
Is composed of
Figure 12794DEST_PATH_IMAGE031
The transposition conjugation;
noise power Ni on the frequency band
Figure 24481DEST_PATH_IMAGE032
(ii) a Wherein the content of the first and second substances,
Figure 674905DEST_PATH_IMAGE033
said
Figure 598999DEST_PATH_IMAGE034
Is that
Figure 233243DEST_PATH_IMAGE035
The transpose of (c) is conjugated.
In order to solve the above technical problem, the present invention further provides a device for estimating SNR of a 5G small cell base station system based on SRS, which is characterized in that the device comprises a first signal unit, a second signal unit, a first arithmetic unit, a second arithmetic unit, a time offset unit, a channel estimation unit and a signal-to-noise ratio calculation unit;
the first signal unit extracts SRS measuring signals Y' SRS (k, l, r) from the received frequency domain data; according to the time offset value TA generated by the time offset unit, performing time offset compensation on the SRS measuring signal Y' SRS (k, l, r) to obtain a compensated measuring signal Ysrs (k, l, r); wherein k is a subcarrier index of a received SRS signal, l is an OFDM symbol, and r is a receiving antenna;
the second signal unit generates a local occurrence sequence Xsrs (k, l, p) according to a 3GPP protocol; wherein, p is the index of the transmitting antenna port;
the first arithmetic unit is used for estimating according to the final channel
Figure 268195DEST_PATH_IMAGE036
And said locally occurring sequence Xsrs (k, l, p) calculates the signal power Pu over the frequency band;
the channel estimation unit is used for calculating the final channel estimation
Figure 523858DEST_PATH_IMAGE036
(ii) a The final channel estimation
Figure 618853DEST_PATH_IMAGE036
Estimating the compensated channel according to the weight w (k, l; k', l
Figure 474813DEST_PATH_IMAGE037
Performing RE-level interpolation operation to obtain; the weight w (k, l; k ', l ') is obtained by calculation according to the covariance matrix theta (k) and the MMSE matrix phi (k ') among different subcarriers at different moments; estimating the compensation channel by the covariance matrix theta (k) and the MMSE matrix phi (k') among different subcarriers at different moments according to an MMSE equalization algorithm
Figure 313456DEST_PATH_IMAGE037
Carrying out interpolation filtering processing to obtain; the compensated channel estimation
Figure 204052DEST_PATH_IMAGE037
Estimating the intermediate channel according to the TA
Figure 719216DEST_PATH_IMAGE038
Performing time offset compensation to obtain; the intermediate channel estimation
Figure 62472DEST_PATH_IMAGE039
By estimating the coarse channel
Figure 439227DEST_PATH_IMAGE040
Performing continuous Nm subcarrier smoothing interference removal processing to obtain the carrier wave; the coarse channel estimation
Figure 918750DEST_PATH_IMAGE040
Calculating according to the measurement signal Ysrs (k, l, r) and the local occurrence sequence Xsrs (k, l, p) based on a least square estimation algorithm; wherein, the
Figure 621127DEST_PATH_IMAGE041
，
Figure 936833DEST_PATH_IMAGE042
Is the port number of the SRS; nu is the number of users,
Figure 117278DEST_PATH_IMAGE043
the second arithmetic unit is used for estimating the final channel according to the compensation measurement signal Ysrs (k, l, r)
Figure 982466DEST_PATH_IMAGE044
And said locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the frequency band;
the time offset unit is used for utilizing the intermediate channel estimation
Figure 590165DEST_PATH_IMAGE039
Performing time offset estimation to obtain the time offset value TA;
the signal-to-noise ratio calculation unit is used for calculating a formula based on the signal-to-noise ratio according to the signal power Pu on the frequency band and the noise power Ni on the frequency band
Figure 626123DEST_PATH_IMAGE045
Determining an intermediate signal-to-noise ratio SNR 'and outputting the intermediate signal-to-noise ratio SNR' to the first arithmetic unit; then receiving the signal power Pu on the new frequency band output by the first arithmetic unit and the noise power Ni on the new frequency band output by the second arithmetic unit, and calculating the formula based on the signal-to-noise ratio
Figure 875839DEST_PATH_IMAGE045
Obtaining the final signal-to-noise ratio SNRest;
the channel estimation unit is further used for obtaining a new MMSE matrix phi (k ') according to the intermediate signal-to-noise ratio SNR' and the covariance Sinc function theta (k); calculating a new weight w (k, l; k ', l ') according to the covariance Sinc function theta (k) between different subcarriers at different times and the new MMSE matrix phi (k '), and estimating the compensation channel according to the new weight w (k, l; k ', l ')
Figure 329954DEST_PATH_IMAGE046
Performing RE-level interpolation operation to obtain new final channel estimation
Figure 374133DEST_PATH_IMAGE044
；
The first arithmetic unit is further configured to estimate a channel according to the new final channel
Figure 648120DEST_PATH_IMAGE044
Calculating the local SRS generating sequence Xsrs (k, l, p) to obtain signal power Pu on a new frequency band, and outputting the signal power Pu to the signal-to-noise ratio calculating unit;
the second arithmetic unit is further configured to estimate a channel according to the new final channel
Figure 435947DEST_PATH_IMAGE044
The compensated measurement signal Ysrs (k, l, r) and the locally occurring sequence Xsrs (k, l, p) calculate the noise power Ni over the new frequency band.
Further, the coarse channel estimation
Figure 495301DEST_PATH_IMAGE040
=
Figure 444803DEST_PATH_IMAGE047
；
The intermediate channel estimation
Figure 737244DEST_PATH_IMAGE048
；
The covariance matrix
Figure 797604DEST_PATH_IMAGE049
(ii) a Wherein the content of the first and second substances,
Figure 475578DEST_PATH_IMAGE050
for the maximum amount of delay that the channel propagates,
Figure 861560DEST_PATH_IMAGE051
a carrier index value for the entire bandwidth,
Figure 110139DEST_PATH_IMAGE024
is an SRS carrier index value;
the MMSE matrix
Figure 239769DEST_PATH_IMAGE052
(ii) a Wherein the SNR 0 Is the initial signal-to-noise ratio;
the new MMSE matrix
Figure 522983DEST_PATH_IMAGE026
；
The weight value
Figure 565019DEST_PATH_IMAGE053
；
The final channel estimation
Figure 566474DEST_PATH_IMAGE054
(ii) a Wherein T represents a matrix transpose;
signal power Pu on the frequency band
Figure 234215DEST_PATH_IMAGE028
(ii) a Wherein, the
Figure 637515DEST_PATH_IMAGE055
；
Noise power Ni on the frequency band
Figure 99720DEST_PATH_IMAGE056
(ii) a Wherein, the
Figure 588470DEST_PATH_IMAGE033
Said
Figure 309170DEST_PATH_IMAGE034
Is that
Figure 566976DEST_PATH_IMAGE035
Is conjugated.
Further, the time offset value TA =
Figure 200083DEST_PATH_IMAGE057
；
Wherein the content of the first and second substances,
Figure 176129DEST_PATH_IMAGE058
；
Figure 185674DEST_PATH_IMAGE059
4096, if two combs are available, L =2
Figure 794858DEST_PATH_IMAGE060
If the comb is four combs, then L =4
Figure 130025DEST_PATH_IMAGE060
Angle is an arctangent function;
the compensated channel estimation
Figure 62208DEST_PATH_IMAGE061
；
The compensated measurement signal Ysrs (k, l, r) =
Figure 141023DEST_PATH_IMAGE062
。
Compared with the prior art, the invention has the following beneficial effects: the invention adopts SRS signals periodically sent under a 5G NR communication protocol framework to calculate signal power and noise, and adopts a least square method principle LS algorithm to calculate channel estimation response. In addition, the invention also carries out time offset estimation and compensation on the channel response of the SRS signal to obtain more accurate final channel estimation so as to reduce the influence of interference signal noise on the estimation performance and improve the accuracy of signal power calculation, thereby obtaining more accurate SNR estimation value and further improving the communication quality of the 5G small base station system.
Drawings
FIG. 1 is a diagram of steps of a method for estimating SNR of a SRS-based 5G small cell system according to an embodiment of the present invention;
fig. 2 is a block diagram of a structure of an apparatus for estimating SNR of a 5G small cell base station system based on SRS according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It is noted that the terms first, second and the like in the description and in the claims of the present application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that the operations are performed in other sequences than in the embodiments of the invention.
As shown in fig. 1, the method for estimating SNR of a 5G small cell base station system based on SRS according to an embodiment of the present invention includes the following steps:
s1, extracting an SRS measuring signal Y' SRS (k, l, r) from received frequency domain data; where k is the subcarrier index of the received SRS signal, and according to the protocol, k is an even number, which may be 0,2,4,8, 8230, etc., or 0,4,8,12, 8230, etc. l is an OFDM (Orthogonal Frequency Division Multiplexing) symbol, and r is a receiving antenna.
S2, generating a local occurrence sequence Xsrs (k, l, p) according to a 3GPP protocol; where p is the transmit antenna port index.
The 3gpp ts38.211 protocol specifies generating antenna ports
Figure 842263DEST_PATH_IMAGE063
The generation formula of SRS sequence Xsrs (k, l, p) of (1):
Figure 597598DEST_PATH_IMAGE064
wherein:
Figure 17078DEST_PATH_IMAGE065
，
Figure 368425DEST_PATH_IMAGE066
e {1,2,4} consecutive OFDM symbols;
Figure 455330DEST_PATH_IMAGE067
，
Figure 866719DEST_PATH_IMAGE068
(ii) a i is an index value of the antenna port.
Figure 789807DEST_PATH_IMAGE069
The number of RBs occupied by the SRS in the frequency domain is shown, and the Table 6.4.1.4.3-1 of the 3gpp ts38.211 protocol can be referred to. Let B = B SRS ，B SRS ∈{0,1,2,3}，C SRS E {0, 1.., 63} is the SRS bandwidth configuration index. Are all set by an upper layer parameter freqHopping, and are determined by the upper layer parameter freqHopping
Figure 944845DEST_PATH_IMAGE069
The value of (a).
Figure 886256DEST_PATH_IMAGE070
Is the number of transmission combs, which takes the value 2 or 4, contained in the higher layer parameter transmissionComb.
Figure 468547DEST_PATH_IMAGE071
。
Antenna port
Figure 862619DEST_PATH_IMAGE063
Cyclic shift of
Figure 70616DEST_PATH_IMAGE072
Obtained according to the following formula:
Figure 866533DEST_PATH_IMAGE073
Figure 354147DEST_PATH_IMAGE074
Figure 501094DEST_PATH_IMAGE075
wherein the content of the first and second substances,
Figure 997935DEST_PATH_IMAGE076
included in the higher layer parameter transmissionComb, the protocol specifies,
Figure 399091DEST_PATH_IMAGE077
。
Figure 323185DEST_PATH_IMAGE078
the series of low peak-to-average ratios is generated by the following formula:
Figure 426270DEST_PATH_IMAGE079
wherein the content of the first and second substances,
Figure 461222DEST_PATH_IMAGE080
is a sequence of a base sequence which is,
Figure 215420DEST_PATH_IMAGE081
is the length of the sequence and is,
Figure 310415DEST_PATH_IMAGE082
is the number of carriers per RB, j is a complex number,
Figure 635217DEST_PATH_IMAGE083
is cyclically shifted by different
Figure 224593DEST_PATH_IMAGE083
And
Figure 849609DEST_PATH_IMAGE035
multiple sequences can be generated from a single motif sequence.
Base sequence
Figure 115506DEST_PATH_IMAGE080
Into groups, where u e {0, 1.., 29} is the group number, v is the base sequence number within the sequence, and when a group contains only one base sequence (v = 0), the length of each base sequence is
Figure 458762DEST_PATH_IMAGE081
Wherein
Figure 84785DEST_PATH_IMAGE084
. With this configuration, one group contains only one base sequence.
Base sequence
Figure 564307DEST_PATH_IMAGE085
Is defined in dependence on length
Figure 266684DEST_PATH_IMAGE086
. When the length of the base sequence is equal to or greater than 36, that is
Figure 831658DEST_PATH_IMAGE087
Radical sequence
Figure 277683DEST_PATH_IMAGE085
Defined by the following equation:
Figure 362444DEST_PATH_IMAGE088
Figure 970143DEST_PATH_IMAGE089
wherein:
Figure 287992DEST_PATH_IMAGE090
，
Figure 272129DEST_PATH_IMAGE091
N ZC ×(u+1)/31+1/2+v×
Figure 726244DEST_PATH_IMAGE092
length N ZC Is satisfying N ZC ＜M ZC Is the maximum prime number of.
When the length of the base sequence is less than 36, the following two cases are distinguished:
for M ZC =30，
Figure 754111DEST_PATH_IMAGE093
For M ZC ∈{6,12,18,24}，
Figure 559256DEST_PATH_IMAGE094
Figure 390126DEST_PATH_IMAGE096
) Defined by 4 tables of section 5.2.2 of the 3GPP TS38.211 protocol, and respectively corresponds to M ZC Equal to 4 cases of 6/12/18 and 24, and will not be described in detail.
S3, calculating to obtain a coarse channel estimation according to the measurement signal Ysrs (k, l, r) and the local generation sequence Xsrs (k, l, p) based on a least square estimation algorithm
Figure 605207DEST_PATH_IMAGE040
. Namely, it is
Figure 382801DEST_PATH_IMAGE097
。
S4, estimating a coarse channel
Figure 708740DEST_PATH_IMAGE040
Carry out continuous N m Smoothing interference-removing treatment of sub-carrier to obtain intermediate channel estimation
Figure 871868DEST_PATH_IMAGE038
。
That is to say that the temperature of the molten steel,
Figure 523430DEST_PATH_IMAGE048
。
wherein, the first and the second end of the pipe are connected with each other,
Figure 772008DEST_PATH_IMAGE041
，
Figure 885327DEST_PATH_IMAGE042
is the number of ports, N, of the SRS u Is the number of the users,
Figure 434120DEST_PATH_IMAGE098
s5, estimating by using the intermediate channel
Figure 725424DEST_PATH_IMAGE038
And performing time offset estimation to obtain a time offset value TA.
Specifically, the time offset value TA =
Figure 726878DEST_PATH_IMAGE057
；
Wherein the content of the first and second substances,
Figure 394619DEST_PATH_IMAGE099
；
Figure 797919DEST_PATH_IMAGE059
4096, if two combs are separated, then L =2
Figure 10857DEST_PATH_IMAGE060
If the comb is four combs, then L =4
Figure 499607DEST_PATH_IMAGE060
And angle is an arctangent function.
S6, estimating an intermediate channel according to the time offset value TA
Figure 705460DEST_PATH_IMAGE038
And the SRS measuring signal Y' SRS (k, l, r) carries out time offset compensation to obtain a compensation channel estimation
Figure 963266DEST_PATH_IMAGE046
And compensate the measurement signal Ysrs (k, l, r).
In particular, channel estimation is compensated
Figure 861952DEST_PATH_IMAGE061
；
Compensated measurement signal Ysrs (k, l, r) =
Figure 87266DEST_PATH_IMAGE062
。
S7, estimating the intermediate channel according to an MMSE (minimum mean square error) equalization algorithm
Figure 831231DEST_PATH_IMAGE038
And carrying out interpolation filtering processing to obtain covariance matrixes theta (k) and MMSE matrixes phi (k') among different subcarriers at different moments.
For SRS channel estimation, only single symbol is needed to be configured, so that only frequency domain interpolation needs to be considered, time domain interpolation can be ignored, and covariance matrix can be obtained
Figure 943544DEST_PATH_IMAGE049
(ii) a MMSE matrix
Figure 13131DEST_PATH_IMAGE052
。
Wherein the content of the first and second substances,
Figure 210894DEST_PATH_IMAGE050
for the maximum amount of delay that the channel propagates,
Figure 509282DEST_PATH_IMAGE051
is a carrier space, may be configured to be 30kHz, is a carrier index value for the entire bandwidth,
Figure 741681DEST_PATH_IMAGE024
is an SRS carrier index value; SNR 0 For initial signal-to-noise ratio, 30dB may be set.
S8, calculating weight w (k, l; k ', l ') according to the covariance matrix theta (k) and the MMSE matrix phi (k '), and estimating an intermediate channel according to the weight w (k, l; k ', l ')
Figure 982169DEST_PATH_IMAGE038
Performing RE-level interpolation operation to obtain final channel estimation
Figure 667228DEST_PATH_IMAGE044
。
Weight value
Figure 18575DEST_PATH_IMAGE100
。
Final channel estimation
Figure 89168DEST_PATH_IMAGE101
(ii) a Where T denotes a matrix transpose.
S9, estimating according to the final channel
Figure 766137DEST_PATH_IMAGE044
And calculating the signal power Pu on the frequency band by the local generation sequence Xsrs (k, l, p), and finally estimating the channel according to the compensation measurement signal Ysrs (k, l, r)
Figure 672913DEST_PATH_IMAGE044
And the locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the band.
Signal power Pu over a frequency band
Figure 827951DEST_PATH_IMAGE028
(ii) a Wherein the content of the first and second substances,
Figure 769362DEST_PATH_IMAGE029
，
Figure 356246DEST_PATH_IMAGE030
is composed of
Figure 750319DEST_PATH_IMAGE031
The transpose of (c) is conjugated.
Figure 709047DEST_PATH_IMAGE102
To represent
Figure 239386DEST_PATH_IMAGE031
Multiplied by the transposed conjugate of itself, it can be converted to a real number, i.e., signal power.
Noise power Ni on frequency band
Figure 992578DEST_PATH_IMAGE103
(ii) a Wherein the content of the first and second substances,
Figure 388793DEST_PATH_IMAGE104
，
Figure 885634DEST_PATH_IMAGE105
is that
Figure 801637DEST_PATH_IMAGE106
The transpose of (c) is conjugated.
Figure 460152DEST_PATH_IMAGE035
Noise represented on OFDM symbols of SRSThe value of the noise, which is a complex number,
Figure 828816DEST_PATH_IMAGE107
to represent
Figure 880080DEST_PATH_IMAGE035
Multiplied by the transposed conjugate of itself, it can be converted to a real number, i.e., noise power.
mean refers to calculating the mean.
S10, according to the signal power Pu on the frequency band and the noise power Ni on the frequency band, calculating formula based on signal to noise ratio
Figure 650590DEST_PATH_IMAGE045
Determining an intermediate signal-to-noise ratio SNR';
s11, according to the intermediate signal-to-noise ratio SNR' and the covariance matrix
Figure 745585DEST_PATH_IMAGE108
To obtain a new MMSE matrix
Figure 601545DEST_PATH_IMAGE109
(ii) a And then, returning to the step S8 to perform sequential stepwise calculation again until the step S10 obtains the final signal-to-noise ratio SNRest according to the signal-to-noise ratio calculation formula.
Specifically, the new MMSE matrix in this step
Figure 705767DEST_PATH_IMAGE026
。
Then, returning to step S8, calculating the weight
Figure 314472DEST_PATH_IMAGE110
The new MMSE matrix calculated in step S11 is used
Figure 580368DEST_PATH_IMAGE111
Input weight calculation formula
Figure 923625DEST_PATH_IMAGE112
Get new rightsValue of
Figure 565959DEST_PATH_IMAGE110
Then the new weight value is added
Figure 311061DEST_PATH_IMAGE113
Inputting a calculation formula of final channel estimation
Figure 498591DEST_PATH_IMAGE114
To obtain a new final channel estimate
Figure 63565DEST_PATH_IMAGE044
(ii) a Step S9 is executed again, and the new final channel estimation is carried out
Figure 509589DEST_PATH_IMAGE044
Calculation formula Pu of signal power on input frequency band
Figure 843619DEST_PATH_IMAGE028
，
Figure 451318DEST_PATH_IMAGE029
Obtaining the signal power Pu on the new frequency band; new final channel estimation
Figure 752855DEST_PATH_IMAGE044
Formula Ni for calculating noise power in input frequency band
Figure 205833DEST_PATH_IMAGE056
；
Figure 659948DEST_PATH_IMAGE033
Obtaining the noise power Ni on a new frequency band; step S10 is executed again, the signal power Pu on the new frequency band and the noise power Ni on the new frequency band are input into the SNR calculation formula
Figure 189281DEST_PATH_IMAGE115
And obtaining the final signal-to-noise ratio SNRest.
As shown in fig. 2, the apparatus for estimating SNR of a 5G small cell system based on SRS according to an embodiment of the present invention includes a first signal unit, a second signal unit, a first computing unit, a second computing unit, a time offset unit, a channel estimation unit, and a signal-to-noise ratio computing unit.
The first signal unit extracts an SRS measuring signal Y' SRS (k, l, r) from the received frequency domain data; according to the time offset value TA generated by the time offset unit, performing time offset compensation on the SRS measuring signal Y' SRS (k, l, r) to obtain a compensated measuring signal Ysrs (k, l, r); where k is a subcarrier index of the received SRS signal, l is an OFDM symbol, and r is a receiving antenna.
The second signal unit generates a local occurrence sequence Xsrs (k, l, p) according to the 3GPP protocol; where p is the transmit antenna port index.
The first arithmetic unit is used for estimating according to the final channel
Figure 463267DEST_PATH_IMAGE116
And the locally occurring sequence Xsrs (k, l, p) calculates the signal power Pu over the frequency band.
The channel estimation unit is used for calculating final channel estimation
Figure 985515DEST_PATH_IMAGE116
(ii) a Final channel estimation
Figure 294137DEST_PATH_IMAGE116
Estimating the compensated channel according to the weight w (k, l; k', l
Figure 492906DEST_PATH_IMAGE117
Performing RE-level interpolation operation to obtain; the weight w (k, l; k ', l ') is obtained by calculation according to the covariance matrix theta (k) and the MMSE matrix phi (k ') among different subcarriers at different moments; estimating a compensation channel by the covariance matrix theta (k) and the MMSE matrix phi (k') among different subcarriers at different time according to an MMSE equalization algorithm
Figure 519768DEST_PATH_IMAGE117
Carrying out interpolation filtering processing to obtain; compensating channel estimates
Figure 845707DEST_PATH_IMAGE117
Estimating the intermediate channel according to the time offset value TA
Figure 274414DEST_PATH_IMAGE118
Performing time offset compensation to obtain; intermediate channel estimation
Figure 394817DEST_PATH_IMAGE118
By estimating the coarse channel
Figure 659707DEST_PATH_IMAGE119
Performing continuous Nm subcarrier smoothing interference removal processing to obtain the carrier wave; coarse channel estimation
Figure 789337DEST_PATH_IMAGE119
Calculating according to the measurement signal Ysrs (k, l, r) and the local occurrence sequence Xsrs (k, l, p) based on a least square estimation algorithm; wherein the content of the first and second substances,
Figure 806972DEST_PATH_IMAGE120
，
Figure 363855DEST_PATH_IMAGE121
is the port number of the SRS; nu is the number of users,
Figure 365309DEST_PATH_IMAGE122
in particular, coarse channel estimation
Figure 282319DEST_PATH_IMAGE119
=
Figure 420039DEST_PATH_IMAGE123
。
Intermediate channel estimation
Figure 147823DEST_PATH_IMAGE124
。
Covariance matrix
Figure 370994DEST_PATH_IMAGE125
(ii) a Wherein the content of the first and second substances,
Figure 842427DEST_PATH_IMAGE126
for the maximum amount of delay that the channel propagates,
Figure 585386DEST_PATH_IMAGE127
is a carrier space, may be configured to be 30kHz, is a carrier index value for the entire bandwidth,
Figure 749651DEST_PATH_IMAGE128
is an SRS carrier index value.
MMSE matrix
Figure 194539DEST_PATH_IMAGE129
(ii) a Wherein the SNR 0 For initial signal-to-noise ratio, 30dB may be set.
Weight value
Figure 204083DEST_PATH_IMAGE130
。
Final channel estimation
Figure 581975DEST_PATH_IMAGE131
(ii) a Where T denotes a matrix transpose.
The second arithmetic unit is used for estimating the final channel according to the compensation measurement signal Ysrs (k, l, r)
Figure 635251DEST_PATH_IMAGE116
And the locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the band.
Time offset unit for using intermediate channel estimation
Figure 98593DEST_PATH_IMAGE118
And performing time offset estimation to obtain a time offset value TA.
Specifically, the time offset value TA =
Figure 646249DEST_PATH_IMAGE132
；
Wherein the content of the first and second substances,
Figure 878647DEST_PATH_IMAGE133
；
Figure 853557DEST_PATH_IMAGE134
4096, if two combs are separated, then L =2
Figure 289348DEST_PATH_IMAGE135
If the comb is four combs, then L =4
Figure 906274DEST_PATH_IMAGE135
Angle is an arctangent function;
compensating channel estimation
Figure 727600DEST_PATH_IMAGE136
；
Compensated measurement signal Ysrs (k, l, r) =
Figure 138990DEST_PATH_IMAGE137
。
The signal-to-noise ratio calculation unit is used for calculating a formula based on the signal-to-noise ratio according to the signal power Pu on the frequency band and the noise power Ni on the frequency band
Figure 311345DEST_PATH_IMAGE138
Determining an intermediate signal-to-noise ratio SNR ', and outputting the intermediate signal-to-noise ratio SNR' to a first arithmetic unit; then receiving the signal power Pu on the new frequency band output by the first arithmetic unit and the noise power Ni on the new frequency band output by the second arithmetic unit, and calculating the formula based on the signal-to-noise ratio
Figure 450071DEST_PATH_IMAGE138
And obtaining the final signal-to-noise ratio SNRest.
The channel estimation unit is further adapted to estimate the channel estimate based on the intermediate signal-to-noise ratio, SNR', and the covariance, sinc-function
Figure 657062DEST_PATH_IMAGE108
To obtain a new MMSE matrix
Figure 973773DEST_PATH_IMAGE109
(ii) a Calculating a new weight w (k, l; k ', l ') according to the covariance Sinc function theta (k) between different subcarriers at different moments and the new MMSE matrix phi (k '), and estimating a compensation channel according to the new weight w (k, l; k ', l ')
Figure 367846DEST_PATH_IMAGE139
Performing RE-level interpolation operation to obtain new final channel estimation
Figure 326574DEST_PATH_IMAGE116
。
Wherein the new MMSE matrix
Figure 873224DEST_PATH_IMAGE140
。
The first arithmetic unit is further used for estimating the channel according to the new final channel
Figure 891996DEST_PATH_IMAGE116
And calculating a local SRS generating sequence Xsrs (k, l, p) to obtain a signal power Pu on a new frequency band, and outputting the signal power Pu to a signal-to-noise ratio calculating unit.
In particular, the signal power Pu on the frequency band
Figure 773364DEST_PATH_IMAGE141
(ii) a Wherein the content of the first and second substances,
Figure 270205DEST_PATH_IMAGE142
。
the second arithmetic unit is also used for estimating the channel according to the new final channel
Figure 920629DEST_PATH_IMAGE116
The measurement signal Ysrs (k, l, r) and the locally occurring sequence Xsrs (k, l, p) are compensated, and the noise power Ni over the new frequency band is calculated.
In particular, noise power Ni in frequency band
Figure 93990DEST_PATH_IMAGE143
(ii) a Wherein the content of the first and second substances,
Figure 728234DEST_PATH_IMAGE144
，
Figure 763186DEST_PATH_IMAGE145
is that
Figure 533696DEST_PATH_IMAGE146
Is conjugated.
In summary, the invention calculates the signal power and noise by using the SRS signal periodically transmitted under the framework of the 5G NR communication protocol, and calculates the channel estimation response by using the least square method LS algorithm. In addition, the invention also carries out time offset estimation and compensation on the channel response of the SRS signal to obtain more accurate final channel estimation so as to reduce the influence of interference signal noise on the estimation performance and improve the accuracy of signal power calculation, thereby obtaining more accurate SNR estimation value and further improving the communication quality of the 5G small base station system.
The above examples merely represent preferred embodiments of the present invention, which are described in more detail and detail, but are not to be construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications, such as combinations of different features in various embodiments, may be made without departing from the spirit of the invention, and these are within the scope of the invention.

Claims (10)

1. A method for estimating SNR of a 5G small cell system based on SRS is characterized by comprising the following steps:
s1, extracting an SRS measuring signal Y' SRS (k, l, r) from received frequency domain data; wherein k is a subcarrier index of a received SRS signal, l is an OFDM symbol, and r is a receiving antenna;
s2, generating a local occurrence sequence Xsrs (k, l, p) according to a 3GPP protocol; wherein, p is the index of the transmitting antenna port;
s3, calculating to obtain a coarse channel estimation value based on a least square estimation algorithm according to the SRS measuring signal Y' SRS (k, l, r) and the local occurrence sequence Xsrs (k, l, p)Meter
Figure 641057DEST_PATH_IMAGE001
；
S4, estimating the coarse channel
Figure 530515DEST_PATH_IMAGE001
Performing continuous Nm subcarrier smoothing interference-removing processing to obtain intermediate channel estimation
Figure 471927DEST_PATH_IMAGE002
；
Wherein, the
Figure 54218DEST_PATH_IMAGE003
，
Figure 448290DEST_PATH_IMAGE004
Is the port number of the SRS, nu is the number of users,
Figure 407019DEST_PATH_IMAGE005
s5, estimating by using the intermediate channel
Figure 692682DEST_PATH_IMAGE002
Performing time offset estimation to obtain a time offset value TA;
s6, estimating the intermediate channel according to the time offset value TA
Figure 445875DEST_PATH_IMAGE002
And the SRS measuring signal Y' SRS (k, l, r) is subjected to time offset compensation to obtain a compensation channel estimation
Figure 592822DEST_PATH_IMAGE006
And compensating the measurement signal Ysrs (k, l, r);
s7, estimating the compensation channel according to an MMSE (minimum mean square error) equalization algorithm
Figure 824084DEST_PATH_IMAGE007
Carrying out interpolation filtering processing to obtain covariance matrixes theta (k) and MMSE matrixes phi (k') among different subcarriers at different moments;
s8, calculating a weight w (k, l; k ', l ') according to the covariance matrix theta (k) and the MMSE matrix phi (k '), and estimating the compensation channel according to the weight w (k, l; k ', l ')
Figure 740087DEST_PATH_IMAGE006
Performing RE-level interpolation operation to obtain final channel estimation
Figure 664181DEST_PATH_IMAGE008
；
S9, estimating according to the final channel
Figure 298424DEST_PATH_IMAGE008
And said locally occurring sequence Xsrs (k, l, p) calculates the signal power Pu over the frequency band; the final channel estimation is based on the compensated measurement signal Ysrs (k, l, r)
Figure 333376DEST_PATH_IMAGE008
And said locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the frequency band;
s10, according to the signal power Pu on the frequency band and the noise power Ni on the frequency band, calculating formula based on signal-to-noise ratio
Figure 838307DEST_PATH_IMAGE009
Determining an intermediate signal-to-noise ratio SNR';
s11, according to the intermediate signal-to-noise ratio SNR' and the covariance matrix
Figure 198881DEST_PATH_IMAGE010
To obtain a new MMSE matrix
Figure 553377DEST_PATH_IMAGE011
(ii) a Then, the process returns to the step S6 to perform another stepAnd sequentially and gradually calculating until the step S8 obtains the final signal-to-noise ratio SNRest according to the signal-to-noise ratio calculation formula.
2. The SRS-based 5G small cell base station system SNR estimation method of claim 1, wherein the step S3 further includes:
the coarse channel estimation
Figure 392020DEST_PATH_IMAGE001
=
Figure 17036DEST_PATH_IMAGE012
。
3. The SRS-based 5G small cell base station system SNR estimation method of claim 1, wherein the step S4 further includes:
the intermediate channel estimation
Figure 548512DEST_PATH_IMAGE013
。
4. The SRS-based 5G small cell base station system SNR estimation method according to claim 1, wherein the step S5 further includes:
the time offset value TA =
Figure 626189DEST_PATH_IMAGE014
；
Wherein the content of the first and second substances,
Figure 268523DEST_PATH_IMAGE015
；
Figure 13625DEST_PATH_IMAGE016
4096, if two combs are separated, then L =2
Figure 450423DEST_PATH_IMAGE017
If the comb is four combs, then L =4
Figure 280976DEST_PATH_IMAGE017
Angle is an arctangent function;
the step S6 further includes:
the compensated channel estimation
Figure 195842DEST_PATH_IMAGE018
；
The compensated measurement signal Ysrs (k, l, r) = c
Figure 296915DEST_PATH_IMAGE019
。
5. The SRS-based 5G small cell base station system SNR estimation method of claim 1, wherein the step S7 further includes:
the covariance matrix
Figure 170194DEST_PATH_IMAGE020
；
Wherein, the first and the second end of the pipe are connected with each other,
Figure 488042DEST_PATH_IMAGE021
for the maximum amount of delay that the channel can propagate,
Figure 206600DEST_PATH_IMAGE022
a carrier index value for the entire bandwidth,
Figure 660715DEST_PATH_IMAGE023
an SRS carrier index value;
the MMSE matrix
Figure 704894DEST_PATH_IMAGE024
(ii) a Wherein the SNR 0 Is the initial signal-to-noise ratio;
in step S11, the new MMSE matrix
Figure 244460DEST_PATH_IMAGE025
。
6. The SRS-based 5G small cell base station system SNR estimation method of claim 1, wherein the step S8 further includes:
the weight value
Figure 766708DEST_PATH_IMAGE026
；
The final channel estimation
Figure 340909DEST_PATH_IMAGE027
(ii) a Where T denotes a matrix transpose.
7. The SRS-based 5G small cell system SNR estimation method of claim 1, wherein the step S9 further includes:
signal power Pu on the frequency band
Figure 290410DEST_PATH_IMAGE028
(ii) a Wherein, the
Figure 815807DEST_PATH_IMAGE029
The above-mentioned
Figure 141747DEST_PATH_IMAGE030
Is composed of
Figure 570454DEST_PATH_IMAGE031
Transpose conjugation;
noise power Ni on the frequency band
Figure 690857DEST_PATH_IMAGE032
(ii) a Wherein, the first and the second end of the pipe are connected with each other,
Figure 205015DEST_PATH_IMAGE033
said
Figure 334645DEST_PATH_IMAGE034
Is that
Figure 352279DEST_PATH_IMAGE035
The transpose of (c) is conjugated.
8. A SNR estimation device of a 5G small base station system based on SRS is characterized by comprising a first signal unit, a second signal unit, a first arithmetic unit, a second arithmetic unit, a time bias unit, a channel estimation unit and a signal-to-noise ratio calculation unit;
the first signal unit extracts SRS measuring signals Y' SRS (k, l, r) from the received frequency domain data; according to the time offset value TA generated by the time offset unit, performing time offset compensation on the SRS measuring signal Y' SRS (k, l, r) to obtain a compensated measuring signal Ysrs (k, l, r); wherein k is a subcarrier index of a received SRS signal, l is an OFDM symbol, and r is a receiving antenna;
the second signal unit generates a local occurrence sequence Xsrs (k, l, p) according to a 3GPP protocol; wherein, p is the index of the transmitting antenna port;
the first arithmetic unit is used for estimating according to the final channel
Figure 174742DEST_PATH_IMAGE036
And said locally occurring sequence Xsrs (k, l, p) calculates the signal power Pu over the frequency band;
the channel estimation unit is used for calculating the final channel estimation
Figure 910616DEST_PATH_IMAGE036
(ii) a The final channel estimation
Figure 578358DEST_PATH_IMAGE036
Estimating the compensated channel according to the weight w (k, l; k', l
Figure 217543DEST_PATH_IMAGE037
Performing RE-level interpolation operation to obtain; the weight w (k, l; k ', l ') is obtained by calculation according to the covariance matrix theta (k) and the MMSE matrix phi (k ') among different subcarriers at different moments; estimating the compensation channel by the covariance matrix theta (k) and the MMSE matrix phi (k') among different subcarriers at different moments according to an MMSE equalization algorithm
Figure 945328DEST_PATH_IMAGE037
Carrying out interpolation filtering processing to obtain; the compensated channel estimation
Figure 168499DEST_PATH_IMAGE037
Estimating the intermediate channel according to the time offset value TA
Figure 639931DEST_PATH_IMAGE038
Performing time offset compensation to obtain; the intermediate channel estimation
Figure 897737DEST_PATH_IMAGE038
By estimating the coarse channel
Figure 530844DEST_PATH_IMAGE039
Performing continuous Nm subcarrier smoothing interference removal processing to obtain the carrier wave; the coarse channel estimation
Figure 506890DEST_PATH_IMAGE039
Calculating according to the measurement signal Ysrs (k, l, r) and the local occurrence sequence Xsrs (k, l, p) based on a least square estimation algorithm; wherein, the
Figure 516435DEST_PATH_IMAGE040
，
Figure 628747DEST_PATH_IMAGE041
Is the port number of the SRS; nu is the number of users,
Figure 698334DEST_PATH_IMAGE042
the second arithmetic unit is used for estimating the final channel according to the compensation measurement signal Ysrs (k, l, r)
Figure 129053DEST_PATH_IMAGE036
And said locally occurring sequence Xsrs (k, l, p) calculates the noise power Ni over the frequency band;
the time offset unit is used for utilizing the intermediate channel estimation
Figure 207868DEST_PATH_IMAGE038
Performing time offset estimation to obtain the time offset value TA;
the signal-to-noise ratio calculation unit is used for calculating a formula based on the signal-to-noise ratio according to the signal power Pu on the frequency band and the noise power Ni on the frequency band
Figure 174687DEST_PATH_IMAGE043
Determining an intermediate signal-to-noise ratio SNR 'and outputting the intermediate signal-to-noise ratio SNR' to the first arithmetic unit; then receiving the signal power Pu on the new frequency band output by the first arithmetic unit and the noise power Ni on the new frequency band output by the second arithmetic unit, and calculating the formula based on the signal-to-noise ratio
Figure 415175DEST_PATH_IMAGE043
Obtaining the final signal-to-noise ratio SNRest;
the channel estimation unit is further configured to estimate the channel estimation value based on the intermediate signal-to-noise ratio SNR' and the covariance Sinc function
Figure 100235DEST_PATH_IMAGE044
To obtain a new MMSE matrix
Figure 717161DEST_PATH_IMAGE045
(ii) a Calculating a new weight w (k, l; k ', l ') according to the covariance Sinc function theta (k) among different subcarriers at different moments and the new MMSE matrix phi (k '), and compensating the compensation according to the new weight w (k, l; k ', l ')Channel estimation
Figure 538486DEST_PATH_IMAGE046
Performing RE-level interpolation operation to obtain new final channel estimation
Figure 949876DEST_PATH_IMAGE036
；
The first arithmetic unit is further configured to estimate a channel according to the new final channel
Figure 856652DEST_PATH_IMAGE036
Calculating the local SRS generating sequence Xsrs (k, l, p) to obtain signal power Pu on a new frequency band, and outputting the signal power Pu to the signal-to-noise ratio calculating unit;
the second arithmetic unit is further configured to estimate a channel according to the new final channel
Figure 277269DEST_PATH_IMAGE036
The compensated measurement signal Ysrs (k, l, r) and the locally occurring sequence Xsrs (k, l, p) calculate the noise power Ni on the new frequency band.
9. The SRS-based 5G small cell system SNR estimation apparatus of claim 8, wherein the coarse channel estimation
Figure 953101DEST_PATH_IMAGE039
=
Figure 36857DEST_PATH_IMAGE047
；
The intermediate channel estimation
Figure 430929DEST_PATH_IMAGE048
；
The covariance matrix
Figure 389658DEST_PATH_IMAGE049
(ii) a Wherein, the first and the second end of the pipe are connected with each other,
Figure 185576DEST_PATH_IMAGE050
for the maximum amount of delay that the channel propagates,
Figure 204347DEST_PATH_IMAGE051
a carrier index value for the entire bandwidth,
Figure 820136DEST_PATH_IMAGE023
is an SRS carrier index value;
the MMSE matrix
Figure 582556DEST_PATH_IMAGE024
(ii) a Wherein the SNR 0 Is the initial signal-to-noise ratio;
the new MMSE matrix
Figure 232980DEST_PATH_IMAGE025
；
The weight value
Figure 157074DEST_PATH_IMAGE052
；
The final channel estimation
Figure 791318DEST_PATH_IMAGE053
(ii) a Wherein T represents a matrix transpose;
signal power Pu on the frequency band
Figure 324805DEST_PATH_IMAGE028
(ii) a Wherein, the
Figure 829735DEST_PATH_IMAGE054
；
Noise power Ni on the frequency band
Figure 190310DEST_PATH_IMAGE032
(ii) a Wherein, the
Figure 780691DEST_PATH_IMAGE033
The above-mentioned
Figure 884913DEST_PATH_IMAGE034
Is that
Figure 509930DEST_PATH_IMAGE035
The transpose of (c) is conjugated.
10. The SRS-based 5G small cell system SNR estimation apparatus of claim 8, wherein the time offset value
Figure 41405DEST_PATH_IMAGE055
；
Wherein, the first and the second end of the pipe are connected with each other,
Figure 119083DEST_PATH_IMAGE056
；
Figure 761416DEST_PATH_IMAGE057
4096, if two combs are available, L =2
Figure 240939DEST_PATH_IMAGE058
If the comb is four combs, then L =4
Figure 190920DEST_PATH_IMAGE058
Angle is an arctangent function;
the compensated channel estimation
Figure 21473DEST_PATH_IMAGE059
；
The compensated measurement signal Ysrs (k, l, r) =
Figure 201919DEST_PATH_IMAGE060
。
CN202211659946.XA 2022-12-23 2022-12-23 SNR estimation method and device of 5G small base station system based on SRS Pending CN115941405A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116132228A (en) * 2023-04-19 2023-05-16 深圳国人无线通信有限公司 Channel time offset compensation method and device based on multi-user SRS
CN116527458A (en) * 2023-07-05 2023-08-01 深圳国人无线通信有限公司 SNR estimation method and device for DMRS signal of 5G small cell
CN117081716A (en) * 2023-10-17 2023-11-17 深圳国人无线通信有限公司 SNR estimation method and device of multi-user DMRS signal based on 5G small cell

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116132228A (en) * 2023-04-19 2023-05-16 深圳国人无线通信有限公司 Channel time offset compensation method and device based on multi-user SRS
CN116527458A (en) * 2023-07-05 2023-08-01 深圳国人无线通信有限公司 SNR estimation method and device for DMRS signal of 5G small cell
CN116527458B (en) * 2023-07-05 2024-03-22 深圳国人无线通信有限公司 SNR estimation method and device for DMRS signal of 5G small cell
CN117081716A (en) * 2023-10-17 2023-11-17 深圳国人无线通信有限公司 SNR estimation method and device of multi-user DMRS signal based on 5G small cell
CN117081716B (en) * 2023-10-17 2023-12-19 深圳国人无线通信有限公司 SNR estimation method and device of multi-user DMRS signal based on 5G small cell

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