CN101316143B - Signal-to-noise ratio estimation device, system and method based on star map measurement - Google Patents

Signal-to-noise ratio estimation device, system and method based on star map measurement Download PDF

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CN101316143B
CN101316143B CN2008101148180A CN200810114818A CN101316143B CN 101316143 B CN101316143 B CN 101316143B CN 2008101148180 A CN2008101148180 A CN 2008101148180A CN 200810114818 A CN200810114818 A CN 200810114818A CN 101316143 B CN101316143 B CN 101316143B
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CN101316143A (en
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黄晓
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Vimicro Corp
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Abstract

The invention provides a signal to noise ratio estimator, system and method that are based on the constellation measurement. The signal to noise ratio estimator includes a constellation demodulator, a constellation measuring device and a signal to noise ratio estimator; wherein, the constellation demodulator demodulates the signal yn that is compensated by a channel compensator, and obtains the estimated value sn of the sending signal to be output to the constellation measuring device; the constellation measuring device carries out constellation measurement on the input signal yn and sn, works out the European distance |yn-sn| between yn and sn to be output to the signal to noise ratio estimator; the signal to noise ratio estimator judges if the channel is a Gaussian channel or flat fading channel according to the input channel information, and the signal to noise ratio of the Gaussian channel or flat fading channel can be estimated directly according to the |yn-sn|; if the channel is found to be a rapid fading channel, the signal to noise ratio of the rapid fading channel can be estimated according to the estimated channel response Hn and the input |yn-sn|. The invention also proposes the corresponding system and method, which decreases the complexity and has good estimation performance.

Description

A kind of SNR estimator, system and method based on star map measurement
Technical field
The present invention relates to the signal-to-noise ratio (SNR) estimation technology of digital communication and DMB receiving system, relate in particular to SNR estimator, system and method based on star map measurement.
Background technology
In communication system,, need know the ratio of signal power and noise power in the receiving symbol usually, i.e. signal to noise ratio in order to evaluate and test or optimize the performance of each module of receiving system.In a lot of the application, because the requirement of system or the influence of channel, the signal to noise ratio of receiving symbol often is not invariable, so need estimate the signal to noise ratio that changes by certain method.
In general, the target of signal-noise ratio estimation method is with the cost of minimum estimated snr as far as possible exactly.At present, Chang Yong signal-noise ratio estimation method can be divided into two classes:
One class is by measuring some statistical property of received signal, as second moment or Fourth-order moment, carries out the estimation of signal to noise ratio through calculating.These class methods be owing to will calculate the statistical property of signal, so the complexity of calculating own is higher, and calculates and need division arithmetic, thereby make hard-wired complexity also correspondingly improve.
Another kind of then is by primary signal and reference signal being compared, calculating its Euclidean distance on planisphere, to estimate the signal to noise ratio of received signal, as shown in Figure 1.The realization of these class methods is simple relatively, but because this method need be carried out the estimation of channel response information to each code element, and need add the processing of making an uproar, so its computation complexity is also higher relatively.
Referring to Fig. 1, for example in European ground digital television broadcast DVB-T/H system, the data-signal of reception (hereinafter to be referred as received signal) can be expressed as:
r n＝H ns n+w n，n＝1，…，N (1)
In the formula: s nBe to send signal, H nBe the frequency response of channel, w nBe additive white Gaussian noise, N is real integer.
So, the signal y after the channel compensator compensates nBe expressed from the next for:
y n = r n H ^ n = s n + w n H ^ n , n = 1 , · · · , N - - - ( 2 )
In the formula:
Figure S2008101148180D00022
It is the channel response that obtains by the channel estimator estimation.
y nAfter the planisphere demodulator carries out demodulation, obtain sending the estimated value of signal
Figure S2008101148180D00023
To send the estimated value of signal again
Figure S2008101148180D00024
Adding adding of the processor of making an uproar by channel makes an uproar to handle and obtains reference signal
Figure S2008101148180D00025
Be shown below:
r ^ n = H ^ n s ^ n - - - ( 3 )
Then, compare and measure reference signal by the star map measurement device
Figure S2008101148180D00027
With received signal r nEuclidean distance And be calculated as follows the power of noise signal:
E { | r n - r ^ n | 2 } = E { | H n s n + w n - H ^ n s ^ n | 2 } - - - ( 4 )
In the formula: E{} represents right
Figure S2008101148180D000210
The calculating of desired value.
At last, by with signal power
Figure S2008101148180D000211
Divided by resulting noise signal power, just can estimate signal to noise ratio
Figure S2008101148180D000212
Promptly be shown below:
Figure S2008101148180D000213
In sum, with respect to the method for analyzing based on signal statistics, less relatively based on the extra computation complexity that signal-noise ratio estimation method brought of the planisphere comparison of channel information.And in traditional signal-noise ratio estimation method,, need before star map measurement, just carry out the estimation of channel response to each code element in order to obtain reference signal based on star map measurement, and add the processing of making an uproar accordingly, so its computation complexity is still apparent higher.Therefore, need traditional signal-noise ratio estimation method based on star map measurement be improved.
Summary of the invention
Technical problem to be solved by this invention provides a kind of SNR estimator based on star map measurement, system and method, can reduce computation complexity and implementation complexity effectively, and can guarantee estimated performance preferably.
In order to solve the problems of the technologies described above, the invention provides a kind of SNR estimator based on star map measurement, comprise the planisphere demodulator, star map measurement device and the signal-to-noise ratio (snr) estimation device that connect successively; Wherein:
The planisphere demodulator is used for the signal y to the channel compensator compensates nCarry out demodulation, obtain the estimated value that sends signal
Figure S2008101148180D00031
Export to the star map measurement device;
The star map measurement device is used for the signal y to input nWith Carry out star map measurement, calculate the Euclidean distance of the two
Figure S2008101148180D00033
Export to the signal-to-noise ratio (snr) estimation device;
The signal-to-noise ratio (snr) estimation device is used for judging when being Gaussian channel or falt fading channel according to the channel information of input, by
Figure S2008101148180D00034
Directly estimate the signal to noise ratio of Gaussian channel or falt fading channel; And then respond according to estimated channel when being fast fading channel if judge With the input Estimate the fast fading channel signal to noise ratio.
Further, above-mentioned signal-to-noise ratio (snr) estimation device comprises channel properties judging module and the first signal-to-noise ratio (snr) estimation device that is connected with the channel properties judging module respectively and the second signal-to-noise ratio (snr) estimation device; Wherein:
The channel properties judging module, be used for channel information, if judge that channel is Gaussian channel or falt fading channel, then to first signal-to-noise ratio (snr) estimation device output estimation order according to input, and if judge that channel is a fast fading channel, then to second signal-to-noise ratio (snr) estimation device output estimation order;
The first signal-to-noise ratio (snr) estimation device, be used to receive estimation order after, adopt formula The signal to noise ratio of estimation Gaussian channel or falt fading channel;
The second signal-to-noise ratio (snr) estimation device, be used to receive estimation order after, adopt formula
Figure S2008101148180D00038
Estimation fast fading channel signal to noise ratio.
Further, channel information comprises one or more in the estimated value of coherence bandwidth of coherence time of channel exponent number, channel and channel.
Further, the planisphere demodulator adopts corresponding hard decision demodulating algorithm to carry out described demodulation according to the modulation system that emission system adopted.
In order to solve the problems of the technologies described above, the invention provides a kind of signal-to-noise ratio (SNR) estimation system that uses above-mentioned SNR estimator of the present invention based on star map measurement, comprise interconnective channel estimator and channel compensator, wherein:
Channel estimator is used for the pilot signal that receives is carried out channel estimating, obtains comprising the estimated channel response
Figure S2008101148180D00039
Export to channel compensator at interior channel information;
Channel compensator is used for basis
Figure S2008101148180D000310
To the data-signal r that receives nCompensate, obtain signal through compensation y n = r n H ^ n ;
This signal-to-noise ratio (SNR) estimation system also comprises respectively the SNR estimator that is connected with channel compensator with channel estimator, is used for the signal y to input nDemodulation is obtained
Figure S2008101148180D00042
Measure then and calculate y nWith
Figure S2008101148180D00043
Euclidean distance on planisphere
Figure S2008101148180D00044
Channel information judgement channel properties according to input is Gaussian channel or falt fading channel again, or described fast fading channel, correspondingly estimates the signal to noise ratio and the fast fading channel signal to noise ratio of Gaussian channel or falt fading channel.
In order to solve the problems of the technologies described above, the invention provides a kind of signal-noise ratio estimation method based on star map measurement, the steps include:
A, to the signal y of channel compensation in the receiving system nCarry out the planisphere demodulation, obtain the estimated value that sends signal
Figure S2008101148180D00045
Y is calculated in B, measurement nWith
Figure S2008101148180D00046
Euclidean distance on planisphere
Figure S2008101148180D00047
C, according to the channel information of receiving system channel estimating, if judge when being Gaussian channel or falt fading channel, by
Figure S2008101148180D00048
Directly estimate the signal to noise ratio of Gaussian channel or falt fading channel; And then respond according to estimated channel when being fast fading channel if judge
Figure S2008101148180D00049
With
Figure S2008101148180D000410
Estimate the fast fading channel signal to noise ratio.
Further, step C adopts formula
Figure S2008101148180D000411
The signal to noise ratio of estimation Gaussian channel or falt fading channel; Adopt formula
Figure S2008101148180D000412
Estimation fast fading channel signal to noise ratio.
Further, step C channel information comprises one or more in the estimated value of coherence bandwidth of coherence time of channel exponent number, channel and channel.
Further, the planisphere demodulation adopts corresponding hard decision demodulating algorithm to carry out according to the modulation system that emission system adopted.
The present invention is based on analysis, directly with the signal y behind the channel compensation to the characteristic of channel nSeparate through planisphere and to obtain after being in harmonious proportion that adding makes an uproar and handling
Figure S2008101148180D000413
With received signal r nRelatively calculate by star map measurement, obtain signal to noise ratio, thus can avoid the channel information of each receiving symbol correspondence is calculated for common Gaussian channel and falt fading channel, thereby reduced computation complexity and the implementation complexity in the conventional method; And the present invention has estimated performance preferably through the Computer Simulation test specification.
Description of drawings
Fig. 1 is the structured flowchart of traditional SNR estimator based on star map measurement;
Fig. 2 is the structured flowchart of the signal-to-noise ratio (SNR) estimation system based on star map measurement of the present invention;
Fig. 2 a is the structured flowchart of the signal-to-noise ratio (snr) estimation device 2330 in the SNR estimator 230 shown in Figure 2;
Fig. 3 is the signal-noise ratio estimation method flow chart based on star map measurement of the present invention.
Embodiment
The present invention improves the SNR estimator based on star map measurement, proposed a kind of calculating and realized simple relatively SNR estimator and method, this SNR estimator comprises planisphere demodulator, star map measurement device and the signal-to-noise ratio (snr) estimation device that connects successively; Wherein, planisphere demodulator input compensates the data-signal that receives from channel compensator and obtains signal y through compensation n, and to this y nCarry out demodulation, obtain the estimated value that sends signal Export to the star map measurement device; The star map measurement device is to the y of input nWith
Figure S2008101148180D00052
Measurement compares its Euclidean distance Export to the signal-to-noise ratio (snr) estimation device; The signal-to-noise ratio (snr) estimation device is according to channel situation, if judge that this channel is Gaussian channel or falt fading channel, then basis
Figure S2008101148180D00054
Directly estimate signal to noise ratio; And if judge that this channel is a fast fading channel, then according to the channel response from channel estimator output
Figure S2008101148180D00055
With Estimate signal to noise ratio.The present invention is by adopting corresponding rationally approximate estimation process mode at different channels, greatly reduce the computation complexity and the implementation complexity of conventional method, and it is have estimated performance preferably, thereby very suitable for digital communication and DMB receiving system.
Below in conjunction with the drawings and specific embodiments technique scheme of the present invention is described in detail.
One aspect of the present invention has proposed signal-to-noise ratio (SNR) estimation system and the SNR estimator thereof based on star map measurement, and Fig. 2 has provided an embodiment.This signal-to-noise ratio (SNR) estimation system 200 comprises channel estimator 210, channel compensator 220 and the SNR estimator 230 that connects successively; Wherein:
Channel estimator 210 is used for the pilot signal that receives is carried out channel estimating, obtains comprising channel response
Figure S2008101148180D00057
At interior channel information, export to channel compensator 220 and signal-to-noise ratio (snr) estimation device 2330 respectively;
Channel compensator 220 is used for responding according to estimated channel
Figure S2008101148180D00061
To the data-signal r that receives nCompensate, obtain signal through compensation y n = r n H ^ n ;
SNR estimator 230 is used for the signal y through compensation to input nThe estimated value that sends signal is obtained in demodulation
Figure S2008101148180D00063
Measure relatively y then nWith Euclidean distance on planisphere
Figure S2008101148180D00065
Judge channel properties according to the channel information of input again, estimate corresponding signal to noise ratio respectively according to channel of different nature.
Contain planisphere demodulator 2310 and star map measurement device 2320 and the signal-to-noise ratio (snr) estimation device 2330 that connects successively in SNR estimator 230 (among Fig. 2 shown in the empty frame) lining; Wherein:
Planisphere demodulator 2310 is used for the signal y through compensation nCarry out the planisphere demodulation, obtain the estimated value that sends signal
Figure S2008101148180D00066
Export to star map measurement device 2320;
In the present embodiment, digital communication receiving system hard decision demodulating algorithm commonly used is adopted in the planisphere demodulation.If emission system adopts different modulation system (such as QPSK, 16QAM or 64QAM), then this planisphere demodulation should be adopted corresponding with it hard decision demodulating algorithm.
Star map measurement device 2320 is connected with channel compensator 220, is used for the signal y through compensation to input nWith the estimated value that sends signal
Figure S2008101148180D00067
Carry out star map measurement, relatively calculate the Euclidean distance of the two
Figure S2008101148180D00068
Export to signal-to-noise ratio (snr) estimation device 2330;
Signal-to-noise ratio (snr) estimation device 2330 is used for channel information according to input when judging that this channel is Gaussian channel or falt fading channel, by
Figure S2008101148180D00069
Directly estimate signal to noise ratio; And then respond according to estimated channel when this channel is fast fading channel if judge
Figure S2008101148180D000610
With the input
Figure S2008101148180D000611
Estimate signal to noise ratio.
The structure of above-mentioned signal-to-noise ratio (snr) estimation device 2330 is shown in Fig. 2 a, and this signal-to-noise ratio (snr) estimation device 2330 comprises: channel properties judging module 2331 and difference connected Gauss/falt fading channel signal-to-noise ratio (snr) estimation device 2332 and fast fading channel signal-to-noise ratio (snr) estimation device 2333; Wherein:
Channel properties judging module 2331, be used for channel information according to input, if judge that channel is Gaussian channel or falt fading channel, then to Gauss/falt fading channel signal-to-noise ratio (snr) estimation device 2332 output estimation orders, and if judge that channel is a fast fading channel, then to the 2333 output estimation orders of fast fading channel signal-to-noise ratio (snr) estimation device;
Especially, in the present embodiment, the judgement of channel properties can be carried out according to the estimated value of the coherence bandwidth of coherence time of channel exponent number, channel and channel.
Gauss/falt fading channel signal-to-noise ratio (snr) estimation device 2332, be used to receive estimation order after, directly according to the Euclidean distance of input
Figure S2008101148180D00071
Estimate signal to noise ratio
Figure S2008101148180D00072
Be shown below:
Figure S2008101148180D00073
Fast fading channel signal-to-noise ratio (snr) estimation device 2333, be used to receive estimation order after, according to the channel response of input Estimate signal to noise ratio
Figure S2008101148180D00075
Be shown below:
Figure S2008101148180D00076
Signal to noise ratio about Gauss/falt fading channel With the fast fading channel signal to noise ratio
Figure S2008101148180D00078
Approximate estimation derive, see also following description.
The present invention has also proposed the signal-noise ratio estimation method based on star map measurement on the other hand, and as shown in Figure 3, the flow process of this method may further comprise the steps:
Step 310: to the signal y of channel compensation in the system nCarry out the planisphere demodulation, obtain the estimated value that sends signal
Figure S2008101148180D00079
In the present embodiment, the planisphere demodulation is adopted different modulation systems according to emitter, such as QPSK, 16QAM or 64QAM, and employing hard decision demodulating algorithm correspondingly.
Step 320: the estimated value that will send signal
Figure S2008101148180D000710
Signal y with the channel compensation nCarry out star map measurement relatively, obtain Euclidean distance
Figure S2008101148180D000711
Step 330: judge according to channel information whether channel is fast fading channel, if execution in step 340; If not, execution in step 350 then;
At this, the judgement of channel properties can be carried out according to the estimated value of the coherence bandwidth of coherence time of channel exponent number, channel and channel;
Step 340: channel is a fast fading channel, responds according to estimated channel
Figure S2008101148180D000712
And Euclidean distance
Figure S2008101148180D000713
Estimate signal to noise ratio, then process ends;
In the present embodiment, be approximated as follows calculating:
Figure S2008101148180D00081
Then top equation is done the denary logarithm computing, just can obtain with dB is the signal-to-noise ratio (SNR) estimation value of unit, shown in above-mentioned formula (7):
Figure S2008101148180D00082
Step 350: channel is Gaussian channel or falt fading channel, directly by Euclidean distance
Figure S2008101148180D00083
Estimate signal to noise ratio, then process ends.
Usually, have for Gaussian channel: | H ^ n | 2 = 1 , Can be reduced to by formula 7 estimated signal-to-noise ratio (SNR) estimation values like this:
Figure S2008101148180D00085
Similarly, have for falt fading channel: E { | H ^ n | 2 } = α ^ H , Can be reduced to by formula 7 estimated signal to noise ratios like this:
Figure S2008101148180D00087
And if have E { | ( y n - s ^ n ) | 2 | H ^ n | 2 } ≈ E { | ( y n - s ^ n ) | 2 } E { | H ^ n | 2 } Set up, top calculating can further be reduced to:
Figure S2008101148180D00089
Can get the signal-to-noise ratio (SNR) estimation value of Gaussian channel shown in the formula (6) or falt fading channel thus.
Through Computer Simulation, estimated performance of the present invention is as shown in the table.
Average signal-to-noise ratio estimated performance under table 1 different channels
Figure S2008101148180D000810
See in sum, in SNR estimator that the present invention proposes, system and method based on star map measurement, owing to no longer need division arithmetic, and for Gaussian channel and falt fading channel when calculating signal to noise ratio, the channel information that no longer needs each receiving symbol correspondence, so computation complexity reduces greatly, thereby the complexity that realizes also significantly reduces thereupon.And test can be reached a conclusion through computer simulation system, and the signal-noise ratio estimation method that the present invention proposes is compared with conventional method and had estimated performance preferably.
Because the present invention can several form is specialized and do not break away from aim of the present invention and necessary characteristic, therefore be understood that the above embodiments are not limited by any details in the above-mentioned explanation, unless stipulate in addition, and do wide explanation in aim that should limit in the appended claims and the scope, all changes and improvements of analog that therefore fall into the border of described claim or this border are included by appended claim.

Claims (7)

1. the SNR estimator based on star map measurement is characterized in that, described SNR estimator comprises planisphere demodulator, star map measurement device and the signal-to-noise ratio (snr) estimation device that connects successively; Wherein:
Described planisphere demodulator is used for the signal y to the channel compensator compensates nCarry out demodulation, obtain the estimated value that sends signal
Figure FSB00000447642200011
Export to described star map measurement device;
Described star map measurement device is used for the described signal y to input nWith described
Figure FSB00000447642200012
Carry out star map measurement, calculate the Euclidean distance of the two Export to described signal-to-noise ratio (snr) estimation device;
Described signal-to-noise ratio (snr) estimation device is used for judging when being Gaussian channel or falt fading channel according to the channel information of input, by described
Figure FSB00000447642200014
Directly estimate the signal to noise ratio of Gaussian channel or falt fading channel; And then respond according to estimated channel when being fast fading channel if judge
Figure FSB00000447642200015
With the input described
Figure FSB00000447642200016
Estimate the fast fading channel signal to noise ratio; Wherein:
Described signal-to-noise ratio (snr) estimation implement body comprises channel properties judging module and the first signal-to-noise ratio (snr) estimation device that is connected with described channel properties judging module respectively and the second signal-to-noise ratio (snr) estimation device, wherein:
Described channel properties judging module, be used for described channel information according to input, if judge that channel is Gaussian channel or falt fading channel, then to described first signal-to-noise ratio (snr) estimation device output estimation order, and if judge that channel is described fast fading channel, then to described second signal-to-noise ratio (snr) estimation device output estimation order;
The described first signal-to-noise ratio (snr) estimation device, be used to receive described estimation order after, adopt formula
Figure FSB00000447642200017
Estimate the signal to noise ratio of described Gaussian channel or falt fading channel;
The described second signal-to-noise ratio (snr) estimation device, be used to receive described estimation order after, adopt formula
Figure FSB00000447642200018
Estimate described fast fading channel signal to noise ratio;
Wherein:
Figure FSB00000447642200019
It is right to represent
Figure FSB000004476422000110
The calculating of desired value;
Figure FSB000004476422000111
It is right to represent
Figure FSB000004476422000112
The calculating of desired value;
Figure FSB000004476422000113
It is right to represent The calculating of desired value;
N=1 ..., N, N are real integer.
2. according to the described SNR estimator of claim 1, it is characterized in that described channel information comprises one or more in the estimated value of coherence bandwidth of coherence time of channel exponent number, channel and channel.
3. according to the described SNR estimator of claim 1, it is characterized in that described planisphere demodulator adopts corresponding hard decision demodulating algorithm to carry out described demodulation according to the modulation system that emission system adopted.
4. the signal-to-noise ratio (SNR) estimation system based on star map measurement that uses each described SNR estimator of claim 1 to 3 comprises interconnective channel estimator and channel compensator, wherein:
Described channel estimator is used for the pilot signal that receives is carried out channel estimating, obtains comprising the estimated channel response Export to described channel compensator at interior channel information;
Described channel compensator is used for according to described
Figure FSB00000447642200022
To the data-signal r that receives nCompensate, obtain signal through compensation
Figure FSB00000447642200023
It is characterized in that described system also comprises respectively the described SNR estimator that is connected with described channel compensator with described channel estimator, be used for described signal y input nDemodulation is obtained described
Figure FSB00000447642200024
Measure then and calculate described y nWith described
Figure FSB00000447642200025
Described Euclidean distance on planisphere Described channel information judgement channel properties according to input is described Gaussian channel or falt fading channel again, or described fast fading channel, correspondingly estimates the signal to noise ratio and the described fast fading channel signal to noise ratio of described Gaussian channel or falt fading channel;
N=1 wherein ..., N, N are real integer.
5. the signal-noise ratio estimation method based on star map measurement is characterized in that, described method step is:
A, to the signal y of channel compensation in the receiving system nCarry out the planisphere demodulation, obtain the estimated value that sends signal
Figure FSB00000447642200027
Described y is calculated in B, measurement nWith described
Figure FSB00000447642200028
Euclidean distance on planisphere
Figure FSB00000447642200029
C, according to the channel information of described receiving system channel estimating, adopt formula if judge when being Gaussian channel or falt fading channel
Figure FSB000004476422000210
Estimate the signal to noise ratio of described Gaussian channel or falt fading channel; And then adopt formula when being fast fading channel if judge Estimate described fast fading channel signal to noise ratio;
Wherein:
Figure FSB000004476422000212
It is right to represent
Figure FSB000004476422000213
The calculating of desired value;
Figure FSB00000447642200031
It is right to represent
Figure FSB00000447642200032
The calculating of desired value;
Figure FSB00000447642200033
It is right to represent
Figure FSB00000447642200034
The calculating of desired value;
Figure FSB00000447642200035
Expression estimate channel response;
N=1 ..., N, N are real integer.
6. in accordance with the method for claim 5, it is characterized in that the described channel information of step C comprises one or more in the estimated value of coherence bandwidth of coherence time of channel exponent number, channel and channel.
7. according to claim 5 or 6 described methods, it is characterized in that described planisphere demodulation adopts corresponding hard decision demodulating algorithm to carry out according to the modulation system that emission system adopted.
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1917493A (en) * 2006-09-12 2007-02-21 重庆重邮信科股份有限公司 16QAM fixed point demodulation method in HSDPA
CN101047688A (en) * 2006-06-13 2007-10-03 华为技术有限公司 Method and device for estimating signal noise ratio
CN101083650A (en) * 2007-07-05 2007-12-05 北京海尔集成电路设计有限公司 Planisphere mapping based signal-noise ratio estimation method and apparatus in multi-carrier system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101047688A (en) * 2006-06-13 2007-10-03 华为技术有限公司 Method and device for estimating signal noise ratio
CN1917493A (en) * 2006-09-12 2007-02-21 重庆重邮信科股份有限公司 16QAM fixed point demodulation method in HSDPA
CN101083650A (en) * 2007-07-05 2007-12-05 北京海尔集成电路设计有限公司 Planisphere mapping based signal-noise ratio estimation method and apparatus in multi-carrier system

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