CN104270328A - Method for estimating signal-to-noise ratio in real time - Google Patents
Method for estimating signal-to-noise ratio in real time Download PDFInfo
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- CN104270328A CN104270328A CN201410590639.XA CN201410590639A CN104270328A CN 104270328 A CN104270328 A CN 104270328A CN 201410590639 A CN201410590639 A CN 201410590639A CN 104270328 A CN104270328 A CN 104270328A
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Abstract
The invention relates to a real-time estimation method. A passband digital signal received by a receiving end is x(n),and an output result y(n) is obtained through quadrature down variable-frequency conversion; according to the average power Px(k) of some concrete input data x(k) and the average power Py(k) of some concrete output data y(k), the estimated value p^(k) of a signal-to-noise ratio is obtained when the kth data is received, wherein the calculation formula of p^(k) is shown in the specification. The method utilizes the relationship between the total average power of the received signal and the average power of useful signals and the average power of noises before and after quadrature down-conversion to solve the average power of the useful signals and the average power of the noises, thereby estimating the signal-to-noise ratio. The method is suitable for single-carrier digital modulation signals and is also suitable for multi-carrier digital modulation signals. Compared with other estimation methods, the real-time estimation method has the characteristics that caching of large amounts of data is not required, calculated amount is small, low complexity, wide adaptability and high efficiency are achieved, and the real-time estimation method is especially suitable for hardware implementation, and is applied to the technical field of cooperative communication, non-cooperative signal analysis and electromagnetic environment monitoring.
Description
Technical field
The present invention relates to the method for estimation of signal to noise ratio, specifically a kind of signal to noise ratio real-time estimation method of digital modulation signals.
Background technology
?signal to noise ratio weighs an important parameter of channel quality, and many application all need signal to noise ratio as priori, such as, adaptive coding and modulating in cooperative communication, bit error rate estimation, Turbo decoding etc.; And non-co-operation signal is analyzed, signal to noise ratio selects the important references parameter of Modulation Identification method, and be the important evidence of assessment data after demodulating confidence level; In addition, the normalized prerequisite of signal power in the accurate estimation of signal to noise ratio or demodulating process, only has the normalization realizing signal, could realize the correct judgement of symbol.
At present, signal-noise ratio estimation method mainly contains method of estimation, segmentation symbol square signal-to-noise ratio (SNR) estimation, the method for estimation based on Subspace Decomposition, maximum Likelihood based on symbol square, and auto-relativity function method etc.These methods all need buffer memory a large amount of data when carrying out signal-to-noise ratio (SNR) estimation, and estimated accuracy requires that higher required data buffer storage space is larger, and this adds hard-wired complexity undoubtedly; In addition, said method is only suitable for the signal to noise ratio of estimate sheet carrier wave digital modulation signals except digital signal processing, and digital signal processing computation complexity is very large, hardware implementing difficulty.
Summary of the invention
The present invention proposes a kind of digital modulation signals signal to noise ratio real-time estimation method, directly utilize spontaneous signal in demodulating process, real-time estimated snr, buffer memory five data are only needed in estimation procedure, thus overcome said method needs shortcoming data cached in a large number, and method proposed by the invention is to digital modulation signals not special requirement, has both been applicable to single carrier digital modulation signals and has also been applicable to multi-carrier digital modulation signal.
Technical scheme of the present invention is as follows:
A kind of signal to noise ratio real-time estimation method, is characterized in that real-time estimating step is as follows:
(1) the passband digital signal crossed by noise pollution that receiving terminal receives is
, wherein,
; Described
lfor data length, namely for the length of window of signal-to-noise ratio (SNR) estimation,
ifor window sequence number; When the passband digital signal received is a kth input data
time, described k ∈ n;
(2) so
average power be:
，
Wherein
for receiving
kduring-1 data
average power;
(3) for received passband digital signal
after, carry out quadrature frequency conversion and passband signal is converted to baseband signal, quadrature frequency conversion Output rusults
; When ignore low-pass filtering on the impact of baseband signal after, described in
can equivalently representedly be:
, wherein
for complex baseband signal,
for white complex gaussian noise,
for the impulse response of low pass filter in quadrature frequency conversion process, wherein
data length be K; Therefore, when receiving a kth input data
after, the output data obtained are
;
(4) so
average power be:
;
(5) basis
average power
with
average power
obtain receiving
kthe estimated value of signal to noise ratio during individual data
for:
，
Wherein
;
(6) get
k=
k+ 1, repeat (1)-(5), until
k=
l, get
estimation procedure terminates.
Further, the quadrature frequency conversion described in step (3) comprises shift frequency and low-pass filtering two steps, and the effect of low-pass filtering is the high-frequency signal produced in filtering shift frequency process.
From above-mentioned estimation flow process, the present invention only need additional buffered c,
k,
,
with
five intermediate data, and due to quadrature frequency conversion be the general process of signal receiving, so the complexity increase caused by algorithm for estimating almost can be ignored.
Beneficial effect of the present invention is as follows:
The present invention utilizes before and after quadrature frequency conversion, the relation of Received signal strength total mean power and useful signal average power and noise average power, solves useful signal average power and noise average power, and then estimates signal to noise ratio; The present invention had both been applicable to single carrier digital modulation signals, was also applicable to multi-carrier digital modulation signal; Have compared with other methods of estimation and do not need the features such as buffer memory mass data, amount of calculation are little, have that complexity is low, wide adaptability, efficiency high, be particularly suitable for hardware implementing, be applicable to the technical fields such as cooperative communication, non-co-operation signal analysis, electromagnetic environment monitor.
Accompanying drawing explanation
Fig. 1 is estimation steps flow chart of the present invention;
Fig. 2 is that the signal to noise ratio in the specific embodiment of the invention estimates dynamic process figure in real time.
Embodiment
A kind of signal to noise ratio real-time estimation method disclosed by the invention, as shown in Figure 1, its real-time estimating step is as follows:
(1) the passband digital signal crossed by noise pollution that receiving terminal receives is
, wherein,
; Described
lfor data length, namely for the length of window of signal-to-noise ratio (SNR) estimation,
ifor window sequence number; When the passband digital signal received is a kth input data
time, described k ∈ n;
(2) so
average power be:
，
Wherein
for receiving
kduring-1 data
average power;
(3) for received passband digital signal
after, carry out quadrature frequency conversion and passband signal is converted to baseband signal, quadrature frequency conversion Output rusults
; When ignore low-pass filtering on the impact of baseband signal after, described in
can equivalently representedly be:
, wherein
for complex baseband signal,
for white complex gaussian noise,
for the impulse response of low pass filter in quadrature frequency conversion process, wherein
data length be K; Therefore, when receiving a kth input data
after, the output data obtained are
;
(4) so
average power be:
;
(5) basis
average power
with
average power
obtain receiving
kthe estimated value of signal to noise ratio during individual data
for:
，
Wherein
;
(6) get
k=
k+ 1, repeat (1)-(5), until
k=
l, get
estimation procedure terminates.
Specifically verify above-mentioned signal-noise ratio estimation method for a kind of 16QAM signal.
Simulation parameter is: character rate 1/16sps; Carrier frequency 1/4Hz; Sample rate 1Hz; Forming filter is square-root raised-cosine filter, and form factor is 0.35; Data length is 16000(1000 symbol); Signal to noise ratio is 10dB; Low pass filter
h(
n) be FIR filter, exponent number is 16, is 3/8Hz by frequency, concrete coefficient is: 0.0000,0.0048,0.0080-0.0089,-0.0429 ,-0.0290,0.0973,0.2834,0.3745,0.2834,0.0973 ,-0.0290 ,-0.0429,-0.0089 0.0080,0.0048,0.0000.
The real-time estimating step of signal to noise ratio is as follows:
(1) get
,
l=16000, utilize (13) formula to calculate c=0.3255, and get
k=1
(2) data are received
;
(3) calculate
;
(4) the after quadrature frequency conversion is received
kindividually count data
;
(5) calculate
;
(6) calculate
;
(7) make
k=
k+ 1, (1)-(6) until
k=
l, obtain
dB.
As shown in Figure 2, the dynamic process that signal to noise ratio is estimated in real time is shown.
Claims (2)
1. a signal to noise ratio real-time estimation method, is characterized in that real-time estimating step is as follows:
(1) the passband digital signal crossed by noise pollution that receiving terminal receives is
, wherein,
; Described
lfor data length, namely for the length of window of signal-to-noise ratio (SNR) estimation,
ifor window sequence number; When the passband digital signal received is a kth input data
time, described k ∈ n;
(2) so
average power be:
，
Wherein
for receiving
kduring-1 data
average power;
(3) for received passband digital signal
after, carry out quadrature frequency conversion and passband signal is converted to baseband signal, quadrature frequency conversion Output rusults
; When ignore low-pass filtering on the impact of baseband signal after, described in
equivalently representedly be:
, wherein
for complex baseband signal,
for white complex gaussian noise,
for the impulse response of low pass filter in quadrature frequency conversion process, wherein
data length be K; Therefore, when receiving a kth input data
after, the output data obtained are
;
(4) so
average power be:
;
(5) basis
average power
with
average power
obtain receiving
kthe estimated value of signal to noise ratio during individual data
for:
，
Wherein
;
(6) get
k=
k+ 1, repeat (1)-(5), until
k=
l, get
estimation procedure terminates.
2. a kind of signal to noise ratio real-time estimation method according to claim 1, is characterized in that: the quadrature frequency conversion described in step (3) comprises shift frequency and low-pass filtering two steps, and the effect of low-pass filtering is the high-frequency signal produced in filtering shift frequency process.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106330362A (en) * | 2016-08-25 | 2017-01-11 | 中国电子科技集团公司第十研究所 | Data assisted signal to noise ratio estimation method |
| CN110876187A (en) * | 2018-09-03 | 2020-03-10 | 普天信息技术有限公司 | Uplink power control method and device |
| CN117556246A (en) * | 2024-01-09 | 2024-02-13 | 电信科学技术第五研究所有限公司 | Method for separating single wave signal from carrier mixed signal |
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| 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 |
| 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 |
| CN102307166A (en) * | 2011-08-31 | 2012-01-04 | 成都久鑫电子科技有限公司 | SNR (signal to noise ratio) estimation method |
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2014
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Patent Citations (4)
| 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 |
| 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 |
| CN102307166A (en) * | 2011-08-31 | 2012-01-04 | 成都久鑫电子科技有限公司 | SNR (signal to noise ratio) estimation method |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106330362A (en) * | 2016-08-25 | 2017-01-11 | 中国电子科技集团公司第十研究所 | Data assisted signal to noise ratio estimation method |
| CN110876187A (en) * | 2018-09-03 | 2020-03-10 | 普天信息技术有限公司 | Uplink power control method and device |
| CN117556246A (en) * | 2024-01-09 | 2024-02-13 | 电信科学技术第五研究所有限公司 | Method for separating single wave signal from carrier mixed signal |
| CN117556246B (en) * | 2024-01-09 | 2024-03-19 | 电信科学技术第五研究所有限公司 | Method for separating single wave signal from carrier mixed signal |
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