CN102307166B - SNR (signal to noise ratio) estimation method - Google Patents

SNR (signal to noise ratio) estimation method Download PDF

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CN102307166B
CN102307166B CN2011102550233A CN201110255023A CN102307166B CN 102307166 B CN102307166 B CN 102307166B CN 2011102550233 A CN2011102550233 A CN 2011102550233A CN 201110255023 A CN201110255023 A CN 201110255023A CN 102307166 B CN102307166 B CN 102307166B
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signal
sequence
noise ratio
auto
correlation function
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CN102307166A (en
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王甲峰
尹显东
王军
李彪
兰虎生
尹刚
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CHENGDU JIUXIN ELECTRONIC TECHNOLOGY CO LTD
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Abstract

The invention relates to an SNR (signal to noise ratio) estimation method, particularly relating to an SNR estimation method of a single-carrier digital modulation signal. The method provided by the invention is characterized by comprising the following steps: after receiving a discrete complex passband signal polluted by noise, constructing a local BPSK (binary phase shift keying) complex passband modulation sequence according to a sampling period, a symbol period and a forming coefficient; calculating an autocorrelation functions to obtain a value; and simultaneously calculating an autocorrelation function of the discrete complex passband signal to obtain dB. In the circumstances of known symbol speed and forming coefficient, the method provided by the invention can utilize fewer symbolic numbers to obtain higher estimation accuracy with smaller calculated amount, and the SNR estimation method is especially suitable for being applicable to the technical fields including cooperative communication, non-cooperative signal analysis, electromagnetic environment monitoring and the like.

Description

A kind of signal-noise ratio estimation method
Technical field
The present invention relates to a kind of signal-noise ratio estimation method, specifically a kind of signal-noise ratio estimation method of single carrier digital modulation signals.
Background technology
Signal to noise ratio is to weigh an important parameter of channel quality, and many application all need signal to noise ratio as priori, such as the adaptive coding and modulating in cooperative communication, bit error rate estimation, Turbo decoding etc.; And, for non-co-operation signal analysis, signal to noise ratio is to select the important references parameter of Modulation Identification method, and it is the important evidence of assessment data after demodulating confidence level; In addition, in the accurate estimation of signal to noise ratio or demodulating process, the normalized prerequisite of signal power, only have the normalization that realizes signal, could realize the correct judgement of symbol.
At present, signal-noise ratio estimation method mainly contains the method for estimation that the method for estimation, segmentation symbol square signal-to-noise ratio (SNR) estimation, subspace-based of symbol-based square are decomposed, and maximum Likelihood etc.The first two method needs correctly estimate symbol square of accurate timing, and the symbolic number that the accurate estimation of symbol square needs is more, and amount of calculation is larger; The Subspace Decomposition method relates to complicated matrix operation, and amount of calculation is also very large; And maximum likelihood method must be known the probability density of noise, and in most cases, the probability density of noise is unknown, and therefore, this kind of method is of limited application.
Summary of the invention
The present invention is for solving the problems of the technologies described above, based on additive noise and the separate characteristics of signal of communication, a kind of method of estimation of the single carrier digital modulation signals signal to noise ratio based on auto-correlation function is proposed, in the situation that character rate and form factor are known, can utilize less symbolic number to obtain higher estimated accuracy.
In order to reach above-mentioned order ground, the solution of the present invention is as follows:
A kind of signal-noise ratio estimation method, its estimating step is:
A, receive the known sampling period
Figure 2011102550233100002DEST_PATH_IMAGE001
, symbol period
Figure 2011102550233100002DEST_PATH_IMAGE002
And form factor
Figure 2011102550233100002DEST_PATH_IMAGE003
The discrete multiple passband signal that is subject to noise pollution
Figure 2011102550233100002DEST_PATH_IMAGE004
B, the discrete multiple passband signal that steps A receives relatively
Figure 237377DEST_PATH_IMAGE004
, adopt BPSK to construct local BPSK complex radical band modulation sequence as the modulation system of local sequence
Figure 2011102550233100002DEST_PATH_IMAGE005
, at first generate pseudo-random binary sequence, then carry out the BPSK baseband modulation and obtain complex radical band modulation sequence , complex radical band modulation sequence
Figure 809621DEST_PATH_IMAGE005
Sampling period, symbol period and form factor and discrete multiple passband signal
Figure 17880DEST_PATH_IMAGE004
Identical, for ,
Figure 717031DEST_PATH_IMAGE002
With
Figure 984065DEST_PATH_IMAGE003
C, the local BPSK complex radical band modulation sequence obtained according to structure , calculate respectively the auto-correlation function that this sequence time delay is 0
Figure 2011102550233100002DEST_PATH_IMAGE006
, and time delay is
Figure 2011102550233100002DEST_PATH_IMAGE007
Auto-correlation function
Figure 2011102550233100002DEST_PATH_IMAGE008
D, step C is obtained to local BPSK complex radical band modulation sequence Auto-correlation function
Figure 545342DEST_PATH_IMAGE006
And auto-correlation function
Figure 299671DEST_PATH_IMAGE008
Compare, obtain the absolute value of ratio
Figure 2011102550233100002DEST_PATH_IMAGE009
For:
Figure DEST_PATH_IMAGE010
E, the discrete multiple passband signal that is subject to noise pollution that calculating receives respectively again
Figure 912049DEST_PATH_IMAGE004
The time delay auto-correlation function that is 0 , and time delay is
Figure 435434DEST_PATH_IMAGE007
Auto-correlation function
F, according to step D, obtain
Figure 927595DEST_PATH_IMAGE009
, draw signal power
Figure DEST_PATH_IMAGE013
, and noise power
Figure DEST_PATH_IMAGE014
, signal to noise ratio is so
Figure DEST_PATH_IMAGE015
With dB, be expressed as:
Figure DEST_PATH_IMAGE016
DB.
The process of specifically shifting onto of above-mentioned steps is as follows:
When the signal received is the discrete multiple passband signal that is subject to noise pollution
Figure 857637DEST_PATH_IMAGE004
, Can be expressed as
Figure DEST_PATH_IMAGE017
（1）
Wherein The discrete form of single-carrier modulated passband signal,
Figure DEST_PATH_IMAGE019
Discrete zero-mean white Gaussian noise, and With
Figure 986764DEST_PATH_IMAGE019
Between separate.
For the single-carrier modulated passband signal
Figure 778002DEST_PATH_IMAGE018
Can be expressed as,
Figure DEST_PATH_IMAGE020
（2）
Wherein:
Figure DEST_PATH_IMAGE021
For modulation amplitude,
Figure DEST_PATH_IMAGE022
For phase modulation,
Figure DEST_PATH_IMAGE023
For carrier frequency,
Figure DEST_PATH_IMAGE024
For carrier phase, For the shaped pulse function, assuming mode filter here is the root raised cosine filter,
Figure DEST_PATH_IMAGE026
For symbol period,
Figure DEST_PATH_IMAGE027
For the symbolic number received,
Figure DEST_PATH_IMAGE028
Mean the sampling period, kMean the symbol sequence number received, nFor the sampled point sequence number.
Suppose carrier phase during carrying out carrier estimation For constant,
Figure 918576DEST_PATH_IMAGE018
Average is 0,
Figure 690223DEST_PATH_IMAGE004
Time delay is The time, so auto-correlation function
Figure DEST_PATH_IMAGE030
Can utilize following formula to estimate:
Figure DEST_PATH_IMAGE031
（3）
Utilized the incoherent characteristic of noise and signal in computational process.Through arranging, can obtain,
Figure DEST_PATH_IMAGE032
（4）
Wherein
Figure DEST_PATH_IMAGE033
（5）
Figure DEST_PATH_IMAGE034
,
Figure DEST_PATH_IMAGE035
For the complex radical tape symbol.Calculate
Figure 391594DEST_PATH_IMAGE012
Mathematic expectaion
Figure DEST_PATH_IMAGE036
,
Figure DEST_PATH_IMAGE037
（6）
Wherein,
Figure DEST_PATH_IMAGE038
（7）
Wherein .It is visible,
Figure DEST_PATH_IMAGE040
For real number, therefore
Figure DEST_PATH_IMAGE041
Although not necessarily real number, work as symbolic number
Figure 211782DEST_PATH_IMAGE027
When enough large, its imaginary part will go to zero, and now can think
Figure DEST_PATH_IMAGE042
.
Order,
Figure DEST_PATH_IMAGE043
（8）
,
Figure DEST_PATH_IMAGE044
（9）
Get
Figure 439632DEST_PATH_IMAGE012
Absolute value,
Figure DEST_PATH_IMAGE045
（10）
When
Figure DEST_PATH_IMAGE046
,
Figure DEST_PATH_IMAGE047
（11）
Wherein
Figure DEST_PATH_IMAGE048
For signal power,
Figure DEST_PATH_IMAGE049
For noise power.Obviously
Figure 257547DEST_PATH_IMAGE048
,
Figure 508530DEST_PATH_IMAGE049
Be all nonnegative value, therefore have
Figure DEST_PATH_IMAGE050
（12）
It is known according to (6) formula and (7) formula,
Figure DEST_PATH_IMAGE051
（13）
Wherein
Figure DEST_PATH_IMAGE052
Be
Figure 991464DEST_PATH_IMAGE018
Time delay is 0(
Figure 277083DEST_PATH_IMAGE046
) time auto-correlation function.
Order,
Figure DEST_PATH_IMAGE053
,
Figure DEST_PATH_IMAGE054
（14）
Due to
Figure 452850DEST_PATH_IMAGE007
With respect to
Figure DEST_PATH_IMAGE055
Very little,
Figure DEST_PATH_IMAGE056
,
Figure DEST_PATH_IMAGE057
（15）
If can access
Figure 253447DEST_PATH_IMAGE009
Can utilize
Figure DEST_PATH_IMAGE058
Calculate signal power
Figure 279085DEST_PATH_IMAGE013
, and noise power
Figure 402899DEST_PATH_IMAGE014
And then can calculate signal to noise ratio and be
Figure 687250DEST_PATH_IMAGE015
（16）
With dB, be expressed as,
Figure DEST_PATH_IMAGE059
dB （17）
But in the situation that there is noise,
Figure 912826DEST_PATH_IMAGE009
Can't directly calculate.
Observe Expression formula known, ratio Only and the sampling period
Figure 997774DEST_PATH_IMAGE001
, symbol period
Figure 249763DEST_PATH_IMAGE002
And form factor
Figure 149586DEST_PATH_IMAGE003
Relevant, and have nothing to do with Modulation Types, carrier frequency.And
Figure 528746DEST_PATH_IMAGE001
Known, if so symbol period
Figure 830414DEST_PATH_IMAGE002
And form factor
Figure 253306DEST_PATH_IMAGE003
Known, can construct a certain muting complex radical band modulation signal
Figure 453474DEST_PATH_IMAGE005
, its
Figure 823275DEST_PATH_IMAGE001
, And
Figure 573243DEST_PATH_IMAGE003
With
Figure 182078DEST_PATH_IMAGE018
Identical, then calculate respectively the auto-correlation function that this signal lag is 0
Figure 168620DEST_PATH_IMAGE006
, and time delay is
Figure 179301DEST_PATH_IMAGE007
Auto-correlation function , have
Figure 305706DEST_PATH_IMAGE010
（18）
And then calculate signal to noise ratio according to (16) formula or (17) formula.
Relatively, for receiving sequence, can claim that this sequence is local sequence.For the sake of simplicity, can adopt the modulation system of BPSK as local sequence.As for
Figure 830360DEST_PATH_IMAGE007
, owing to working as in theory
Figure DEST_PATH_IMAGE061
The time,
Figure DEST_PATH_IMAGE062
, therefore for the sake of simplicity, can select
Figure DEST_PATH_IMAGE063
.In addition, the symbolic number of local sequence is abundant, to guarantee the stability of result of calculation.
By above-mentioned deriving analysis process, therefore can obtain the estimating step of signal to noise ratio, as follows:
(1) according to the receiving sequence sampling period
Figure 757864DEST_PATH_IMAGE001
, symbol period
Figure 709771DEST_PATH_IMAGE002
And form factor
Figure 293199DEST_PATH_IMAGE003
Construct local BPSK complex radical band sequence
Figure DEST_PATH_IMAGE064
(2) get
Figure DEST_PATH_IMAGE065
, calculate
Figure 605232DEST_PATH_IMAGE064
Auto-correlation function,
Figure 403555DEST_PATH_IMAGE006
,
Figure DEST_PATH_IMAGE066
(3) by (15) formula, calculate
Figure DEST_PATH_IMAGE067
(4) calculate the multiple passband modulation signal of the Noise received
Figure 775630DEST_PATH_IMAGE004
Auto-correlation function
Figure 659404DEST_PATH_IMAGE011
,
Figure DEST_PATH_IMAGE068
(5) by (17) formula estimated snr
Figure DEST_PATH_IMAGE069
.
Beneficial effect of the present invention is as follows:
This method, in the situation that character rate is known, can utilize less symbolic number to obtain higher estimated accuracy, and amount of calculation is less, is specially adapted to the technical fields such as cooperative communication, non-co-operation signal analysis, electromagnetic environment monitor.
The accompanying drawing explanation
The flow chart that Fig. 1 is carrier estimation of the present invention
Fig. 2 is signal-to-noise ratio (SNR) estimation standard variance of the present invention and the true value ratio variation schematic diagram with signal to noise ratio.
Embodiment
By said method, a kind of 8PSK signal of take is verified above-mentioned signal-noise ratio estimation method as example.
Simulation parameter is: character rate 4kB; Carrier frequency 4kHz; Sample rate 16ksps; Form factor 0.35; Symbolic number 4000; Signal to noise ratio 8dB.Estimating step is as follows:
(1) generate local BPSK complex radical band modulation sequence
Figure 775127DEST_PATH_IMAGE064
, symbolic number is 10000;
(2) calculate
Figure 614907DEST_PATH_IMAGE064
Auto-correlation function, ,
(3) obtain
Figure DEST_PATH_IMAGE072
(4) calculate the multiple passband modulation signal of the Noise received
Figure 970933DEST_PATH_IMAGE004
Auto-correlation function ,
Figure DEST_PATH_IMAGE074
(5) calculate signal power and noise power and be respectively, ,
Figure DEST_PATH_IMAGE076
(6) estimated snr is
Figure DEST_PATH_IMAGE077
DB.
As can be seen here, the estimated accuracy of the inventive method is higher.It is worthy of note, because baseband signalling and noise are all random, the result of therefore each emulation is all different.For the statistic property of method of testing, select signal to noise ratio from 3dB ~ 12dB, the signal to noise ratio incremental steps is 1dB, under each signal to noise ratio value, duplicate test is 1000 times, and calculates corresponding average and standard variance.Table 1 has provided signal to noise ratio true value and the contrast of estimating average, and Fig. 2 has provided the change curve of the ratio of standard variance and signal to noise ratio true value with signal to noise ratio.
Table 1 signal to noise ratio true value and the contrast of estimating average
Signal to noise ratio dB 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00
Estimate average dB 3.00 3.99 4.99 5.99 6.99 7.99 8.99 9.98 10.98 11.98
The inventive method is estimating without inclined to one side of signal to noise ratio as can be seen from Table 1, and as can be seen from Figure 2 the inventive method has higher estimated accuracy.
The present invention proposes a kind of based on autocorrelative single carrier digital modulation signals signal-noise ratio estimation method, under character rate and the known condition of form factor, can utilize less symbolic number to obtain higher estimated accuracy.

Claims (3)

1. a signal-noise ratio estimation method is characterized in that estimating step is as follows:
A, receive known sampling period T s, symbol period T and form factor α the discrete multiple passband signal x (n) that is subject to noise pollution;
B, the discrete multiple passband signal x (n) that steps A receives relatively, adopt BPSK to construct local BPSK complex radical band modulation sequence s as the modulation system of local sequence b(n), at first generate pseudo-random binary sequence, then carry out the BPSK baseband modulation and obtain complex radical band modulation sequence s b(n), complex radical band modulation sequence s b(n) sampling period, symbol period and form factor are identical respectively with sampling period, symbol period and the form factor of discrete multiple passband signal x (n), are respectively T s, T and α;
C, the local BPSK complex radical band modulation sequence s obtained according to structure b(n), calculate respectively the auto-correlation function R that this sequence time delay is 0 b, and the time delay auto-correlation function R that is q (0) b(q);
D, step C is obtained to local BPSK complex radical band modulation sequence s b(n) auto-correlation function R bAnd auto-correlation function R (0) b(q) compare, the absolute value f (q) that obtains ratio is:
Figure FDA00003547926400011
E, calculate respectively again the auto-correlation function R (0) that the time delay of the discrete multiple passband signal x (n) that is subject to noise pollution receive is 0, and the time delay auto-correlation function R (q) that is q;
F, the f (q) obtained according to step D, draw signal power P s=f (q) | R (q) |, and noise power P w=| R (0) |-f (q) | R (q) |, signal to noise ratio is so:
Figure FDA00003547926400012
With dB, be expressed as: SNR=10lg (f (q) | R (q) |)-10lg (| R (0) |-f (q) | R (q) |) dB;
Wherein, q>0.
2. a kind of signal-noise ratio estimation method according to claim 1 is characterized in that: in described step B, and the local BPSK complex radical band modulation sequence s of structure b(n) be muting sequence.
3. a kind of signal-noise ratio estimation method according to claim 1 and 2 is characterized in that: in described step, and q=1.
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CN102571033B (en) * 2012-02-01 2014-12-03 成都久鑫电子科技有限公司 Method for estimating forming-filter roll-off coefficient
CN103166722B (en) * 2013-02-27 2015-08-12 北京福星晓程电子科技股份有限公司 A kind of noise energy estimating method
CN104270328B (en) * 2014-10-29 2017-07-25 中国工程物理研究院电子工程研究所 A kind of signal to noise ratio real-time estimation method
CN109586818B (en) * 2018-12-21 2021-05-07 北京昂瑞微电子技术股份有限公司 Signal-to-noise ratio estimation method and device for constant envelope modulation signal

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7190741B1 (en) * 2002-10-21 2007-03-13 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Real-time signal-to-noise ratio (SNR) estimation for BPSK and QPSK modulation using the active communications channel
CN101764780A (en) * 2009-12-28 2010-06-30 北京中星微电子有限公司 Method and system for time and frequency synchronization in orthogonal frequency division multiplexing
CN101977169A (en) * 2010-11-09 2011-02-16 西安电子科技大学 Time domain parameter blind evaluation method of OFDM (Orthogonal Frequency Division Multiplexing) signals
CN102137053A (en) * 2011-05-06 2011-07-27 中国工程物理研究院电子工程研究所 Method for estimating signal to noise ratio of BPSK (Binary Phase Shift Keying) signal

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7190741B1 (en) * 2002-10-21 2007-03-13 The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration Real-time signal-to-noise ratio (SNR) estimation for BPSK and QPSK modulation using the active communications channel
CN101764780A (en) * 2009-12-28 2010-06-30 北京中星微电子有限公司 Method and system for time and frequency synchronization in orthogonal frequency division multiplexing
CN101977169A (en) * 2010-11-09 2011-02-16 西安电子科技大学 Time domain parameter blind evaluation method of OFDM (Orthogonal Frequency Division Multiplexing) signals
CN102137053A (en) * 2011-05-06 2011-07-27 中国工程物理研究院电子工程研究所 Method for estimating signal to noise ratio of BPSK (Binary Phase Shift Keying) signal

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