CN111884956B - SNR estimation method and device based on pilot signal - Google Patents

SNR estimation method and device based on pilot signal Download PDF

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CN111884956B
CN111884956B CN202010604154.7A CN202010604154A CN111884956B CN 111884956 B CN111884956 B CN 111884956B CN 202010604154 A CN202010604154 A CN 202010604154A CN 111884956 B CN111884956 B CN 111884956B
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pilot signal
snr
signal
energy
noise
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CN111884956A (en
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张亮
刘合武
胡杰
郑林
朱齐雄
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China Information And Communication Technology Group Co ltd
Fiberhome Telecommunication Technologies Co Ltd
Wuhan Fisilink Microelectronics Technology Co Ltd
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Fiberhome Telecommunication Technologies Co Ltd
Wuhan Fisilink Microelectronics Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
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    • H04B17/30—Monitoring; Testing of propagation channels
    • H04B17/309—Measuring or estimating channel quality parameters
    • H04B17/336—Signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
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    • H04L25/0228—Channel estimation using sounding signals with direct estimation from sounding signals
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Abstract

The invention discloses a pilot signal-based SNR estimation method and a pilot signal-based SNR estimation device, wherein the method comprises the following steps: extracting an actual pilot signal from a received signal to be estimated; calculating noise signal energy according to a locally known reference pilot signal and an actual pilot signal; calculating SNR according to the locally known reference pilot signal energy and the noise signal energy; correcting the SNR according to the ratio of the reference pilot signal energy to the average energy of the system; wherein, the position of the sequence of the reference pilot signal on the mapped constellation diagram is configurable. The method uses the known Pilot signal as a reference signal, and obtains the SNR by calculation according to the known Pilot signal, and the whole process does not need all data to participate in the operation, thereby reducing the complexity of the calculation process and improving the calculation efficiency and the calculation precision; in addition, the Pilot signal energy can be configured, and the flexibility is stronger.

Description

SNR estimation method and device based on pilot signal
Technical Field
The present invention belongs to the field of communication technologies, and in particular, to a method and an apparatus for SNR estimation based on pilot signals.
Background
With the development of modern communication technology towards high speed, stability and large capacity, a Modulation mode of Quadrature Amplitude Modulation (QAM for short) has been more and more widely applied in the current high-speed optical fiber communication system. QAM modulation is the combination of an orthogonal carrier modulation technology and a multilevel amplitude keying technology, and two paths of orthogonal carriers are used for modulating two paths of parallel signals respectively, so that the bandwidth can be effectively utilized, and the transmission rate of a system is improved. The quadrature amplitude modulation technique can be classified into 8QAM, 16QAM, 32QAM, 64QAM, 128QAM, etc., and different numbers represent the number of bits that can be transmitted by one modulation symbol, i.e. the order of the quadrature amplitude modulation technique. For example, one modulation symbol of 16QAM (i.e., a quadrature amplitude modulation technique with an order of 16) can transmit information of 4 bits. Generally, the quadrature amplitude modulation technique of order greater than 4 is collectively referred to as a high-order quadrature amplitude modulation technique. The invention mainly relates to a high-order quadrature amplitude modulation technology.
Signal-to-Noise Ratio (SNR) generally refers to estimating and measuring the information and Noise power or energy in a received Signal, respectively, and calculating the Ratio between the information and the Noise. In a communication system, the snr is an important indicator for measuring the communication quality and is also an important component of channel estimation. 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 SNR estimation. With the rapid development of high-speed communication systems, the requirements on SNR estimation are higher and higher, the requirements on accuracy are higher, the performance is better, the calculation is simpler, and the implementation is easier.
Currently, the commonly used SNR estimation methods are roughly divided into: a Maximum Likelihood (Maximum likehood) estimation method, a Second order fourth order matrix (the Second order fourth order matrix) estimation method, a Data Fitting (Data Fitting) estimation method, and the like. The maximum likelihood estimation method is to make hard decision on the despread received signal by using a maximum likelihood criterion, then estimate noise energy according to the despread received signal and a corresponding decision signal, and further estimate an SNR according to the noise energy; however, the estimation deviation is larger when the signal-to-noise ratio is lower, and the main reason of the method is that more hard decision errors exist under the condition of lower signal-to-noise ratio, the noise energy calculated on the basis of the wrong hard decision has larger deviation, the corresponding signal-to-noise ratio estimation deviation is also larger, and the calculation accuracy is lower. The second-order and fourth-order matrix estimation method is an algorithm for estimating SNR by utilizing the correlation of second-order moment and fourth-order moment of a signal, and has the advantages that carrier phase recovery is not needed, and a receiver is not needed for judgment; however, since the quadratic mean of the despread received signal needs to be counted, the calculation amount is large, the calculation complexity is large, and the calculation time is long, which not only increases the burden of the system, but also affects the response speed of the system. The data fitting estimation method is a method for estimating the signal-to-noise ratio by separating the energy of signals and noise by curve fitting according to different characteristics of autocorrelation functions of cyclostationary signals and noise; the signal-to-noise ratio accuracy of the method is proportional to the curve fitting order, namely the higher the data fitting order is, the higher the accuracy of the signal-to-noise ratio estimation is, but the more complicated the calculation is correspondingly, and the flexibility is poor.
In summary, the currently used SNR estimation method mainly has the following disadvantages: the method needs a large amount of data to participate in calculation, and has the disadvantages of large calculation amount, high calculation complexity, long calculation time, large power consumption, low calculation accuracy, poor flexibility and the like, so that a simple, quick and accurate SNR estimation method is urgently needed to be designed.
Disclosure of Invention
In view of the above drawbacks or needs for improvement in the prior art, the present invention provides a method and an apparatus for estimating SNR based on Pilot signals, which aims to estimate SNR by using known Pilot signals as reference signals, and provide a method for estimating SNR with simpler, faster, and more accurate calculation, thereby solving the technical problems of complicated calculation, long calculation time, high power consumption, low calculation accuracy, poor flexibility, and the like in the conventional SNR estimation.
To achieve the above object, according to one aspect of the present invention, there is provided a method for SNR estimation based on pilot signals, characterized in that quadrature amplitude modulation is used in a communication link to map the signals onto a constellation diagram; the SNR estimation method comprises:
extracting an actual pilot signal from a received signal to be estimated;
calculating noise signal energy according to a locally known reference pilot signal and an actual pilot signal;
calculating SNR according to the locally known reference pilot signal energy and the noise signal energy;
correcting the SNR according to the ratio of the reference pilot signal energy to the average energy of the system;
wherein the position of the sequence of the reference pilot signal on the mapped constellation diagram is configurable.
Preferably, M pilot signal sequences are inserted into the signal according to a preset protocol requirement on the system transmitting side, so that the reference pilot signal comprises M reference pilot signal sequences; then, at the receiving side, the extracting the actual pilot signal from the received signal to be estimated specifically includes: and extracting M actual pilot signal sequences from the received signal to be estimated according to the determined pilot signal sequence insertion information.
Preferably, the calculating noise signal energy according to the locally known reference pilot signal and the actual pilot signal specifically includes:
respectively taking locally known M reference pilot signal sequences as a standard, and calculating the noise amplitude N of each actual pilot signal sequence by using a constellation diagrami；
According to the noise amplitude N of each actual pilot signal sequenceiCalculating to obtain the noise energy pow of each noisei；
For each noise energy pow obtained by calculationiAveraging is performed to obtain the final desired noise signal energy noi.
Preferably, the corresponding constellation point of the signal on the constellation diagram is I + jQ, I represents an in-phase component, and Q represents a quadrature component; any actual pilot signal sequence PiNoise amplitude N ofiThe calculation formula is specifically as follows:
Ni＝ΔIi+j·ΔQi；
wherein, Delta Ii＝Ii'-Ii，ΔQi＝Qi'-Qi；IiFor the actual pilot signal sequence PiIn-phase component of (1)iIs' is corresponding toThe in-phase component of the reference pilot signal sequence of (a); qiFor the actual pilot signal sequence PiOf (a) quadrature component, Qi' is the orthogonal component of the corresponding reference pilot signal sequence; i-1, 2, 3., M-1, M.
Preferably any actual pilot signal sequence PiCorresponding noise energy powiThe calculation formula is specifically as follows:
powi＝ΔIi 2+ΔQi 2。
preferably, the SNR is calculated according to the locally known reference pilot signal energy and the noise signal energy, specifically:
Figure BDA0002560310240000041
wherein sig is the average energy of the locally known M reference pilot signal sequences.
Preferably, the SNR is calculated according to the locally known reference pilot signal energy and the noise signal energy, specifically:
respectively carrying out amplification and shift operation on the reference pilot signal energy and the noise signal energy until the two signals are respectively greater than a preset value, and recording the respective shift bit widths of the two signals;
the bit width of the shift between the reference pilot signal energy and the noise signal energy is differentiated, and the absolute value of the difference is multiplied by 3 to be used as an integral part estimation value of the SNR;
respectively searching data after the reference pilot signal energy and the noise signal energy are shifted into respective LUT tables, and taking the difference value of the two searched numerical values as the fractional part estimated value of the SNR;
and adding the integer part estimated value and the decimal part estimated value of the SNR to obtain a final SNR estimated value.
Preferably, the quadrature amplitude modulation is in particular 8QAM, 16QAM, 64QAM or 128 QAM.
According to another aspect of the present invention, an SNR estimation apparatus based on a pilot signal is provided, which is characterized by comprising a signal extraction module, a noise calculation module, an SNR calculation module and an SNR modification module;
the signal extraction module is used for extracting an actual pilot signal from a received signal to be estimated;
the noise calculation module is used for calculating noise signal energy according to a locally known reference pilot signal and an actual pilot signal;
the SNR calculation module is used for calculating SNR according to locally known reference pilot signal energy and the noise signal energy;
and the SNR correction module is used for correcting the SNR according to the ratio of the energy of the reference pilot signal to the average energy of the system.
According to another aspect of the present invention, there is provided another apparatus for pilot signal-based SNR estimation, comprising at least one processor and a memory, the at least one processor and the memory being connected via a data bus, the memory storing instructions executable by the at least one processor, the instructions being configured to perform the method for pilot signal-based SNR estimation according to the first aspect after being executed by the processor.
Generally, compared with the prior art, the technical scheme of the invention has the following beneficial effects: the SNR estimation method provided by the invention uses the known Pilot signal as a reference signal, calculates to obtain the noise energy according to the known Pilot signal, and calculates to obtain the SNR according to the known Pilot signal energy and the noise energy, and the whole process does not need to calculate a mean square value or a quartic mean square value and the like, and does not need all data to participate in operation, thereby greatly reducing the complexity of the calculation process, reducing the calculation time, and improving the calculation efficiency and the calculation precision; in addition, Pilot signal energy can be configured, mapping and calculation of a signal energy part in SNR estimation are optimized, and flexibility is higher.
Drawings
Fig. 1 is a flowchart of an SNR estimation method based on pilot signals according to an embodiment of the present invention;
fig. 2 is a schematic diagram illustrating insertion of a Pilot sequence in a system signal according to an embodiment of the present invention;
fig. 3 is a constellation diagram when the quadrature amplitude modulation is 16QAM according to an embodiment of the present invention;
FIG. 4 is a flow chart of a noise signal energy calculation according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of a method for calculating noise amplitude according to an embodiment of the present invention;
fig. 6 is a schematic diagram of estimating SNR based on pilot signals according to an embodiment of the present invention;
FIG. 7 is a flowchart of a method for calculating SNR using dB division according to an embodiment of the present invention;
FIG. 8 is a simplified schematic diagram of the calculation of SNR using dB division according to an embodiment of the present invention;
FIG. 9 is a comparison graph of SNR simulation results when using total data operation and pilot signal operation according to an embodiment of the present invention;
fig. 10 is a graph comparing SNR estimation bias when operating with total data and when operating with pilot signal according to the embodiment of the present invention;
fig. 11 is a comparison diagram of SNR simulation results when SNR is corrected and not corrected by using pilot signal operation according to an embodiment of the present invention;
FIG. 12 is a diagram illustrating a comparison of SNR estimation result deviations when SNR is corrected and not corrected by pilot signal operation according to an embodiment of the present invention;
fig. 13 is a diagram of an apparatus for SNR estimation based on pilot signals according to an embodiment of the present invention;
fig. 14 is a flow chart of DSP processing of a digital coherent receiver according to an embodiment of the present invention;
fig. 15 is a diagram of another apparatus for SNR estimation based on pilot signals according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
Example 1
In order to solve the problems of complex calculation, long calculation time, large power consumption, low calculation precision, poor flexibility and the like in the conventional SNR estimation, the embodiment of the invention provides an SNR estimation method based on Pilot signals (namely Pilot signals). The communication link may use quadrature amplitude modulation, which may be high-order quadrature amplitude modulation such as 8QAM, 16QAM, 64QAM, 128QAM, or the like, or may also be Differential Phase Shift Keying (DPSK), which may map a signal on a constellation diagram, and may determine the energy of the signal according to a coordinate position of the signal on the constellation diagram.
As shown in fig. 1, the SNR estimation method provided by the embodiment of the present invention mainly includes the following steps:
step 10, extracting an actual pilot signal from the received signal to be estimated.
Inserting M Pilot signal sequences into a signal according to a preset protocol requirement at a system transmitting side, specifically referring to a Pilot sequence insertion diagram in fig. 2, where the inserted M Pilot signal sequences are denoted as Pilot-1, Pilot-2,. and Pilot-M, respectively; among the M sequences, some of the M sequences may have the same mapping position on the constellation diagram, and some of the M sequences may have different mapping positions, depending on specific protocol requirements. If the inserting period of the Pilot sequence in the data stream is n, inserting one Pilot sequence every n-1 payload data intervals; here, taking the OFI ZR protocol as an example, n is 32. Wherein payload data, i.e. payload data, corresponds to the blank part between every two Pilot sequences in fig. 2. Therefore, after receiving the signal to be estimated, the receiving side can extract M actual pilot signal sequences, which can be respectively denoted as P, from the received signal to be estimated according to the M pilot signal sequence insertion information determined in the preset protocol requirement1、P2、...、PMWhich correspond to the initially inserted Pilot-1, Pilot-2,. and Pilot-M sequences one by one.
The insertion number M can be set properly according to the calculation requirement, and the number of sequences to be inserted can be calculated according to the number of sequences required; but usually not too few because too few are not statistically characterized. Taking the OFI ZR protocol as an example, 116 determined pilot signal sequences in the protocol are continuously inserted cyclically according to a fixed sequence, that is, M is an integer multiple of 116, for example 1160,11600, and is at least 116.
In addition, flexible configuration can be performed when the Pilot sequence is inserted, that is, the position of the Pilot sequence on the constellation diagram after mapping on the receiving side can be configured, that is, the position of the reference Pilot signal mentioned later on the constellation diagram is configurable. Taking 16QAM as an example, referring to fig. 3, the constellation diagram generally includes 3+3j, 3-3j, -3+3j, -3-3j, i.e. they are located at the outermost circle on the constellation diagram; but in addition, the Pilot sequence can also be flexibly configured to 1+1j, 1-1j, -1+1j, -1-1j, namely the innermost circle on the constellation diagram; the configuration may be in any other position than the three circles, for example, 3.1+3.1j, which is not limited herein.
Step 20, noise signal energy is calculated from the locally known reference pilot signal and the actual pilot signal.
When M Pilot sequences are inserted into the signal, the locally known reference Pilot signal specifically includes M reference Pilot signal sequences, and the finally extracted actual Pilot signal specifically includes M actual Pilot signal sequences. The reference pilot signal is an ideal constellation point without noise on the constellation diagram, while the actual pilot signal is transmitted through the channel and contains noise, so that the actual pilot signal deviates from the corresponding ideal constellation point on the constellation diagram.
The corresponding constellation point of each pilot signal on the constellation diagram is I + jQ, wherein I represents an in-phase component, namely a real part; q represents a quadrature component, i.e., an imaginary part; corresponding signal energy of I2+Q2. After the signal transmitted by the transmitting end is transmitted to the receiving end through the channel, the actual pilot signal received by the receiving end will generate a certain deviation with respect to the reference pilot signal due to the channel noise, and the deviation is shown as being distributed on the reference on the constellation diagramThe surroundings of the pilot signal point; the farther from the reference pilot signal point, the greater the noise. The process of calculating the noise signal energy noi can refer to fig. 4, and specifically includes the following steps:
step 201, respectively taking locally known M reference pilot signal sequences as a standard, calculating the noise amplitude N of each actual pilot signal sequence by using a constellation diagrami. Each group of data includes M actual pilot signal sequences, and respective noise amplitudes need to be calculated respectively, as shown in fig. 5, P _ r represents a received actual pilot signal, P _ l represents a locally known reference pilot signal, and N represents a calculated noise amplitude. For any actual pilot signal sequence PiCorresponding noise amplitude NiThe calculation formula is specifically as follows:
Ni＝ΔIi+j·ΔQi；
wherein, Delta Ii＝Ii'-Ii，ΔQi＝Qi'-Qi；IiFor the actual pilot signal sequence PiIn-phase component of (1)i' is the in-phase component of the corresponding reference pilot signal sequence; qiFor the actual pilot signal sequence PiOf (a) quadrature component, Qi' is the orthogonal component of the corresponding reference pilot signal sequence; 1,2, 3., M-1, M.
Step 202, noise amplitude N according to each actual pilot signal sequenceiCalculating to obtain the noise energy pow of each noisei. For any actual pilot signal sequence PiIts corresponding noise energy powiThe calculation formula is specifically as follows:
powi＝Ni 2＝ΔIi 2+ΔQi 2。
step 203, for each noise energy pow obtained by calculationiAveraging is performed to obtain the final desired noise signal energy noi. Wherein, the calculation formula is as follows:
Figure BDA0002560310240000091
step 30, calculating the SNR from the locally known reference pilot signal energy and the noise signal energy. The specific calculation formula is as follows:
Figure BDA0002560310240000092
wherein sig is the average energy of locally known M reference pilot signal sequences; noi is the average energy of the noise corresponding to the M actual pilot signal sequences, i.e. the noise signal energy obtained by the average calculation in step 203. The above equation is SNR calculation in linear domain, and if converting to decibel (dB) domain, the SNR calculation equation is specifically:
Figure BDA0002560310240000093
it should be noted that, since the M reference pilot signal sequences are often configured on the same circle of the constellation diagram by default, for example, the outer most circle ± 3 ± 3j (i.e. 0000,1000,1010,0010) in fig. 3, the energy value of each reference pilot signal sequence is actually the same, and therefore, the effect of averaging the sig value and not averaging the sig value is the same, and the energy values are all 18. Of course, in other alternative embodiments, if the reference pilot signal sequences are not configured on the same circle of the constellation diagram, the sig value should be the average energy value of the M reference pilot signal sequences.
And step 40, correcting the SNR according to the ratio of the energy of the reference pilot signal to the average energy of the system.
For different high-order quadrature amplitude modulation techniques, the corresponding standard constellation diagrams are different, namely the ratio of the energy of the position where the reference Pilot signal participating in the noise energy calculation is located to the average energy of the system is different. Therefore, the present invention adds a corresponding correction value to the SNR estimation value, and calculates the SNR calculation result in step 30 with the correction value, thereby obtaining an SNR estimation result with higher accuracy. The SNR correction formula is specifically as follows:
Figure BDA0002560310240000094
wherein SNR' is a correction value of SNR, sigSign boardThe average energy value is a standard signal energy value corresponding to the reference pilot signal, and ave is the system average energy; sigSignThe/ave is the ratio of the reference pilot signal energy to the average system energy, and is also called the correction probability.
The whole calculation process introduced above can also be simplified as fig. 6, and by noise calculation based on the known pilot signal, the work of reconstruction, mapping, decision and the like of the traditional method on the signal is reduced, the calculation complexity is reduced, and the calculation efficiency and the calculation accuracy of the system are improved. The above steps are further illustrated below with reference to specific examples:
taking fig. 3 as an example, in a specific embodiment, the quadrature amplitude modulation is 16QAM, and if the mapping position of the reference pilot signal sequence on the constellation diagram is configured at the outermost circle, i.e., ± 3 ± 3j, the known reference pilot signal energy value sig ═ 3)2+(±3)218. When the position of an actual pilot signal sequence on the constellation diagram is 2.8-3.1j, the corresponding reference pilot signal point is 3-3j, and the noise amplitude N ═ 3-3j) - (2.8-3.1j ═ 3-2.8) - (-3+3.1) j ═ 0.2+0.1j, and the corresponding noise energy pow ═ 0.22+0.12. The noise energy corresponding to each of the other actual pilot signal sequences is also calculated by the above method to obtain M noise energy values, and the final required noise signal energy value noi is obtained by averaging, so that the SNR becomes 18/noi.
With continued reference to the quadrant outlined in the lower left portion of fig. 3, when the position of the reference pilot signal on the constellation diagram is-3-3 j, the standard signal energy value sig corresponding to the point is obtainedSign boardIs 18; the other three points in the quadrant are respectively-1-3 j, -1-1j and-3-1 j, and the corresponding energies are respectively 10, 2 and 10, so that the total energy of 4 signal points in the quadrant is 40, and the average energy ave is 10. Therefore, the correction probability is 18/10, and the SNR value calculated above is further divided by the correction probability, so as to obtain the final SNR correction value, specifically:
Figure BDA0002560310240000101
after the above correction formula is calculated, it is found that, since the constellation point of the reference pilot signal is configured at the outermost circle by default, the reference pilot signal energy value sig is 18, and corresponds to the standard signal energy value sigSign boardThe two can be mutually offset in the correction formula, and the obtained product is obtained
Figure BDA0002560310240000102
I.e., SNR' is directly equal to the ratio of the system average energy to the noise signal energy noi. However, the reference pilot signal is configured to the outermost circle of the constellation diagram is a relatively ideal pattern, and the pre-debugging module does not always configure all reference pilot signal sequences to ± 3 ± 3j of the outermost circle, and if the pre-debugging module configures the reference pilot signal to 3.1+3.1j, the reference pilot signal energy value sig is not equal to 18, and the corresponding standard signal energy value sig isSign boardStill 18, where the two cannot be cancelled out in the correction formula.
Further, for 16QAM, if the positions of the reference pilot signal sequence are arranged at intervals of ± 3 ± 3j and ± 1 ± 1j, the average energy value of the reference pilot signal is 10, which is the same as the average energy of the system, i.e. the correction probability is 1, and then the final correction of the SNR estimation value is not needed. In practical applications, the calculation can also be simplified by this method.
The foregoing embodiments only illustrate the case where 16QAM is used for quadrature amplitude modulation, but do not limit the present invention. Except 16QAM, under other high-order quadrature amplitude modulation technologies such as 8QAM, 64QAM and 128QAM, the method can be used for estimating the SNR, and only the corresponding standard constellation diagrams are different; the specific calculation process may refer to 16QAM, which is not described herein.
In summary, the SNR estimation method provided by the embodiment of the present invention mainly has the following beneficial effects:
the local known Pilot signal is used as a reference signal, the SNR is calculated according to the known Pilot signal energy and the noise energy, the calculation of a mean square value or a quartic mean square value and the like is not needed in the whole process, and all data are not needed to participate in the calculation, so that the complexity of the calculation process is greatly reduced, the calculation time is reduced, and the calculation efficiency and the calculation precision are improved; reference Pilot signal energy can be flexibly configured, mapping and calculation of a signal energy part in SNR estimation are optimized, and flexibility is stronger; according to the different ratios of the reference Pilot signal energy participating in noise energy to the average energy of the system, a corresponding correction value is added to the final SNR estimation value, so that a high-precision SNR estimation result can be obtained.
Example 2
On the basis of the foregoing embodiment 1, the embodiment of the present invention further provides another method for estimating SNR based on pilot signals, which is mainly different from embodiment 1 in that a dB division calculation that is easy to implement is adopted to calculate SNR in step 30, so that resources are saved and calculation accuracy is ensured.
Referring to fig. 7 and fig. 8, in the SNR estimation method provided in the embodiment of the present invention, the calculating SNR according to the locally known reference pilot signal energy and the noise signal energy, that is, step 30, specifically includes the following steps:
step 301, performing amplification and shift operations on the reference pilot signal energy and the noise signal energy respectively until the two signals are respectively greater than a preset value, and recording shift bit widths of the two signals.
The specific operation is as follows: taking a predetermined value (i.e. a predetermined maximum value, e.g. 2)30) Then, the two signals are shifted to the left to see which signal reaches the preset value first. Theoretically, the noise signal is much smaller than the reference pilot signal, so the reference pilot signal will reach the preset value first, and the noise signal will reach the preset value later. That is, if the same preset value is reached, the number of bits shifted by the noise signal is greater than that of the reference pilot signal, and the number of bits shifted by each of the two signals, i.e., the bit width of the shift, is recorded after the shift. Here, the reference pilot signal energy may be regarded as an average energy of M reference pilot signal sequences, and the noise signal energy may be regarded as an average energy of noise corresponding to M actual pilot signal sequences.
Step 302, the shift bit width of the reference pilot signal energy and the noise signal energy is differentiated, and the absolute value of the difference is multiplied by 3 to be used as the integer part estimation value of the SNR.
If the noise signal needs to be shifted by 6 bits to reach a preset value and the reference pilot signal needs to be shifted by 2 bits to reach the preset value, the difference between the bit widths of the noise signal and the reference pilot signal is 6-2 to 4, which represents a multiple relation existing between the noise signal and the reference pilot signal; where each shift is a 2-fold relationship, and thus is a 4 x 2-fold relationship here. In the dB algorithm, the 2-fold relation is 3dB, so that the bit width difference of the two signals is multiplied by 3, i.e. 4 × 3 equals 12, as the integer part estimation value of SNR.
Step 303, the data after shifting the reference pilot signal energy and the noise signal energy are respectively entered into respective LUT tables for lookup, and the difference value between the two found numerical values is used as the fractional part estimation value of the SNR.
Here, the data after the two signal shifts need to be respectively intercepted, for example, only the data of the upper five bits is intercepted, then the intercepted data is inquired for the respective corresponding LUT table, and then the data after table lookup is subtracted to be used as the fractional part estimation value of the SNR. The number of the specifically intercepted data bits can be determined according to the precision requirement; for example, if the requirements are not very high, about five bits can be intercepted; if the accuracy requirement is high, tens of bits may be truncated, but this is rarely the case. Generally, it is sufficient to cut five bits, which can save resources while ensuring accuracy, but is not limited in particular.
Step 304, add the integer part estimation value and the fractional part estimation value of the SNR to obtain the final SNR estimation value. The specific calculation formula is as follows:
SNR＝SNRinteger number of+SNRDecimal fraction；
At this point, a preliminary estimation of SNR is completed.
Compared with embodiment 1, the main difference between the two methods lies in the SNR calculation method in step 30, and the specific implementation of the remaining steps, i.e., step 10, step 20, and step 40, is similar to that in embodiment 1, and is not described herein again.
In the conventional method, the SNR is generally calculated by using a principle formula of SNR (db) ═ 10log (sig/noi), but the log logarithm is difficult to implement in hardware and the resource consumption is large; by the method, the SNR estimation value can be obtained by shifting and looking up an LUT table without logarithmic calculation, and the method is more favorable for implementation.
In addition, although some conventional schemes obtain SNR values through LUT query, SNR values are directly obtained through lookup tables, which occupies a large amount of resources. In the SNR estimation method provided by the embodiment of the present invention, only the decimal part is used for LUT lookup, the value of the decimal part is relatively small, the number of bits to be intercepted is usually not very high, and the occupied resources are very small; the larger value of the integer part is mainly obtained by shift processing, and is easier to realize. In some application scenarios, if the requirement on the precision is low, it is even unnecessary to intercept data and perform LUT lookup, that is, the number of the intercepted bits of the data in step 303 is 0, and a fractional part of the value is not needed, and the integer part of the value after the shift processing is directly used as the SNR estimation value, thereby greatly saving the calculation resources.
Example 3
In the conventional scheme, all data (i.e., all received signals) are usually used for SNR estimation, but in the above embodiments 1 and 2, only pilot signals in the received signals are used for SNR estimation, so that all data are not required to participate in calculation, and the calculation process is greatly simplified.
The pilot signal is a number of known data inserted in the transmission system, as shown in fig. 3; the purpose of this is usually to perform accurate channel estimation, symbol synchronization, frequency offset correction, and phase-to-phase noise estimation. The present invention estimates SNR by using pilot signals instead of all data in the conventional scheme, considering the following:
as can be seen from embodiments 1 and 2, the estimation of SNR focuses on the estimation of noise, and the noise is mainly estimated by the deviation of the received signal from the signal at the transmitting end, because the deviation of the signal at the receiving end from the reference constellation point is due to the presence of noise. After the I/Q signal passes through the signal, the degree of the deviation of the entire received signal is theoretically the same as the degree of the deviation of the pilot signal, so that the noise estimation can be performed by using only the deviation of the pilot signal (i.e., the deviation of the actual pilot signal of the receiving end from the known reference pilot signal), thereby realizing the SNR estimation.
In order to further verify the feasibility and accuracy of the SNR estimation methods provided in the above embodiments 1 and 2, the embodiments of the present invention take 16QAM as an example, and a series of simulation studies are respectively performed on SNR estimation when all data participate in the operation in the conventional method and when only pilot signals participate in the operation in the present invention, and the specific results are analyzed as follows:
fig. 9 is a graph comparing SNR simulation results when all data participate in the calculation and only pilot signal participate in the calculation, where (9-1) in fig. 9 shows a simulation result curve of SNR estimation values obtained by using all data participate in the calculation, and fig. 9-2 shows a simulation result curve of SNR estimation values obtained by calculation based on pilot signal according to the present invention. Fig. 10 is a graph showing a comparison of estimated deviations between the SNR estimated value and the SNR standard value obtained by the calculation using all data and the pilot signal alone, in which fig. 10-1 shows a deviation curve between the SNR estimated value and the SNR standard value obtained by the calculation using all data, and fig. 10-2 shows a deviation curve between the SNR estimated value and the SNR standard value obtained by the calculation using the pilot signal according to the present invention. The abscissa in each graph is the SNR standard value set at the time of simulation.
As can be seen from fig. 9 and 10, although the present invention only uses the pilot signal to calculate the SNR, and does not use all data to participate in the calculation, the SNR estimation result is not affected and becomes inaccurate, and even better than all data to participate in the calculation: within the range of 0-15 dB, the SNR estimation error is larger when all conventional data participate in the operation and is between 0-8 dB; the SNR estimation error becomes smaller by 15dB later. When the method is based on pilot signal estimation, SNR estimation errors in the whole range of 0-40 dB are smaller and fluctuate up and down at 0.2; that is to say, the pilot signal estimation method can accurately obtain the SNR estimation value in the whole range of 0-40 dB, and the precision completely meets the requirement.
Further, also for calculating SNR based on pilot signals, fig. 11 also shows a comparison graph of SNR simulation results when SNR is not corrected (i.e. step 40 is not performed) and when SNR is corrected, wherein fig. 11-1 shows a simulation result curve calculated based on pilot signals without correcting SNR, and fig. 11-2 shows a simulation result curve calculated based on pilot signals and corrected SNR (same as fig. 9-2). Fig. 12 shows a comparison graph of SNR estimation bias when SNR is not corrected and SNR is corrected, in which fig. 12-1 shows a bias curve of SNR results calculated based on pilot signals without correcting SNR, and fig. 12-2 shows a bias curve of SNR results calculated based on pilot signals with correcting SNR (the same as fig. 10-2). The abscissa in each graph is the SNR standard value set at the time of simulation.
As can be seen from fig. 11 and 12, if the SNR result is not corrected, the deviation between the finally obtained SNR estimation value and the standard value is large, and the system accuracy requirement is not satisfied; after the correction step is added, the deviation between the SNR estimated value and the standard value is very small and fluctuates about 0.2, so that the precision requirement can be met. Therefore, by correcting the SNR in step 40, a more accurate SNR estimation result can be obtained.
According to the simulation result provided by the embodiment of the invention, the SNR is estimated based on the pilot signal, and the accurate SNR estimation value can be obtained without the participation of all data in the operation; moreover, by adding the correction step, the estimation precision of the SNR is greatly improved.
Example 4
On the basis of the SNR estimation methods based on pilot signals provided in the foregoing embodiments 1 and 2, the embodiments of the present invention further provide an SNR estimation device based on pilot signals, which can be used to implement the methods in embodiments 1 and 2.
As shown in fig. 13, the SNR estimation device mainly includes a signal extraction module, a noise calculation module, an SNR calculation module, and an SNR modification module.
The signal extraction module is configured to extract an actual pilot signal from the received signal to be estimated, that is, to execute the method in step 10;
the noise calculation module is used for calculating noise signal energy according to the locally known reference pilot signal and the actual pilot signal, namely executing the method in the step 20;
the SNR calculating module is configured to calculate SNR according to locally known reference pilot signal energy and the noise signal energy, i.e. execute the method of step 30;
the SNR modification module is configured to modify the SNR according to a ratio of energy of the reference pilot signal to average energy of the system, that is, to execute the method described in step 40.
The detailed function descriptions of the modules may refer to the method descriptions in embodiment 1 and embodiment 2, and are not described herein again.
Further, the SNR estimation apparatus described above can be used in a digital coherent receiver, i.e., the SNR estimation methods described in embodiments 1 and 2 can also be used in a digital coherent receiver.
As shown in fig. 14, after the Digital coherent receiver receives a Signal transmitted from a transmitting end, a Digital Signal Processing (DSP) process mainly includes processes of optical front end compensation, dispersion estimation, dispersion compensation, clock recovery, polarization demultiplexing, frequency offset estimation, phase recovery, SNR estimation, constellation diagram mapping, Forward Error Correction (FEC) decoding, and the like, which are sequentially performed. Correspondingly, the digital coherent receiver comprises a signal receiving module, an optical front-end compensation module, a dispersion estimation module, a dispersion compensation module, a clock recovery module, a polarization demultiplexing module, a frequency offset estimation module, a phase recovery module, a constellation diagram mapping module and an FEC decoding module which are connected in sequence, wherein the SNR estimation module can be connected between the phase recovery module and the constellation diagram mapping module.
The SNR estimation module, that is, the SNR estimation device above, specifically includes a signal extraction module, a noise calculation module, an SNR calculation module, and an SNR correction module, and specific functions are not described herein again.
The modulation format of the original signal received by the digital coherent receiver is common Phase modulation or amplitude Phase modulation, such as Phase Shift Keying (PSK), Quadrature Phase Shift Keying (QPSK), 8QAM, 16QAM, 64QAM, and the like; the signal may be a single polarization signal or a polarization multiplexed signal. The invention mainly relates to a high-order quadrature amplitude modulation technology, namely 8QAM, 16QAM, 64QAM and the like, wherein the signals are polarization multiplexing signals comprising X polarization multiplexing signals and Y polarization multiplexing signals; accordingly, the signal receiving module in the digital coherent receiver includes an X polarization multiplexing signal receiving module and a Y polarization multiplexing signal receiving module, as shown in fig. 14.
Generally, the input signal of the SNR estimation module is a signal to be estimated, and the signal to be estimated is data processed by modules (i.e., modules connected before the SNR estimation module) in a DSP preceding stage of the digital coherent receiver. The optical front-end compensation module mainly performs delay deviation compensation and amplitude phase mismatch compensation on I, Q two paths of signals; the dispersion estimation module mainly estimates the dispersion of the signal; the dispersion compensation module is mainly used for carrying out signal dispersion compensation according to the estimation result of the dispersion estimation module; the clock recovery module is used for realizing conversion of baud rate through insertion; the polarization demultiplexing module is used for eliminating the polarization possibly generated in the transmission process of the signals by utilizing the X and Y signals; the frequency offset estimation module is used for carrying out frequency estimation and recovery; the phase recovery module is used for phase recovery and completing DSP frame synchronization processing. The input signal of the SNR estimation module may be an X polarization branch or a Y polarization branch, that is, the signals of the two branches may share one SNR estimation module.
It should be noted that, data processed by each module at the front stage of the DSP is divided into two branches, one branch enters the SNR estimation module for performing SNR estimation, and the other branch continues to perform constellation mapping and FEC decoding backward. That is to say, the SNR estimation module is actually an independent branch in the receiver, and only uses the data processed by each module at the front stage of the DSP as the input signal, and does not affect the constellation diagram mapping and FEC decoding process at the rear stage; the SNR result calculated by the SNR estimation module can be directly reported to a system so as to evaluate the performance of the whole system. The constellation diagram mapping module is used for de-mapping the constellation diagram mapped by the transmitting terminal; and the FEC decoding module decodes the bit stream coded by the transmitting end by adopting an error correcting code and then transmits the decoded bit stream to the information sink.
In addition, in the whole digital coherent receiver, except that one dispersion estimation module and one SNR estimation module can be shared by the X polarization branch signal and the Y polarization branch signal, two modules are provided, that is, each module is provided for each branch, as shown in fig. 14.
Example 4
On the basis of the SNR estimation methods based on pilot signals provided in the foregoing embodiments 1 and 2, the present invention further provides another SNR estimation device based on pilot signals, which can be used for implementing the foregoing methods, as shown in fig. 15, which is a schematic diagram of the device architecture of the embodiments of the present invention. The pilot signal-based SNR estimation device of the present embodiment includes one or more processors 21 and a memory 22. In fig. 15, one processor 21 is taken as an example.
The processor 21 and the memory 22 may be connected by a bus or other means, and fig. 15 illustrates the connection by a bus as an example.
The memory 22, which is a non-volatile computer-readable storage medium for a pilot signal-based SNR estimation method, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the pilot signal-based SNR estimation method in embodiment 1. The processor 21 executes various functional applications of the pilot signal-based SNR estimation device and data processing, that is, implements the pilot signal-based SNR estimation methods of embodiments 1 and 2, by executing the nonvolatile software programs, instructions, and modules stored in the memory 22.
The memory 22 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 22 may optionally include memory located remotely from the processor 21, and these remote memories may be connected to the processor 21 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The program instructions/modules are stored in the memory 22 and, when executed by the one or more processors 21, perform the pilot signal-based SNR estimation method of embodiment 1 described above, for example, perform the respective steps shown in fig. 1, 4, and 7 described above.
Those of ordinary skill in the art will appreciate that all or part of the steps of the various methods of the embodiments may be implemented by associated hardware as instructed by a program, which may be stored on a computer-readable storage medium, which may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (9)

1. A SNR estimation method based on pilot signal is characterized in that quadrature amplitude modulation is used in a communication link to map a signal on a constellation diagram; the SNR estimation method comprises:
extracting an actual pilot signal from a received signal to be estimated;
calculating noise signal energy according to a locally known reference pilot signal and an actual pilot signal;
respectively carrying out amplification shift operation on reference pilot signal energy and noise signal energy until the two signals are respectively greater than a preset value, stopping the amplification shift operation until the shift bit widths of the two signals are respectively recorded, making a difference between the shift bit widths of the reference pilot signal energy and the noise signal energy, multiplying an absolute value of the difference by 3 to be used as an integer part estimation value of an SNR (signal to noise ratio), respectively searching data after the reference pilot signal energy and the noise signal energy are shifted in respective LUT (look-up Table), using the difference between the two searched values as a fractional part estimation value of the SNR, and adding the integer part estimation value and the fractional part estimation value of the SNR to obtain a final SNR estimation value;
correcting the SNR according to the ratio of the reference pilot signal energy to the average energy of the system;
wherein the position of the sequence of the reference pilot signal on the mapped constellation diagram is configurable.
2. The pilot-signal-based SNR estimation method according to claim 1, wherein M pilot signal sequences are inserted in the signal according to a preset protocol requirement at a system transmitting side such that the reference pilot signal comprises M reference pilot signal sequences; then, at the receiving side, the extracting the actual pilot signal from the received signal to be estimated specifically includes: and extracting M actual pilot signal sequences from the received signal to be estimated according to the determined pilot signal sequence insertion information.
3. The pilot signal-based SNR estimation method according to claim 2, wherein said calculating the noise signal energy from the locally known reference pilot signal and the actual pilot signal is specifically:
respectively taking locally known M reference pilot signal sequences as a standard, and calculating the noise amplitude N of each actual pilot signal sequence by using a constellation diagrami；
According to the noise amplitude N of each actual pilot signal sequenceiCalculating to obtain the noise energy pow of each noisei；
For each noise energy pow obtained by calculationiAveraging is performed to obtain the final desired noise signal energy noi.
4. The pilot signal-based SNR estimation method according to claim 3, wherein the signal has a constellation point I + jQ on a constellation diagram, I representing an in-phase component and Q representing a quadrature component; any actual pilot signal sequence PiNoise amplitude NiThe calculation formula is specifically as follows:
Ni＝ΔIi+j·ΔQi；
wherein, Delta Ii＝Ii'-Ii，ΔQi＝Qi'-Qi；IiFor the actual pilot signal sequence PiIn-phase component of (1)i' is the in-phase component of the corresponding reference pilot signal sequence; qiFor the actual pilot signal sequence PiOf (a) quadrature component, Qi' is the orthogonal component of the corresponding reference pilot signal sequence; i-1, 2, 3., M-1, M.
5. The pilot signal-based SNR estimation method of claim 4, wherein any one of the actual pilot signal sequences PiCorresponding noise energy powiThe calculation formula is specifically as follows:
powi＝ΔIi 2+ΔQi 2。
6. the pilot signal-based SNR estimation method according to claim 3, wherein said calculating the SNR from the locally known reference pilot signal energy and the noise signal energy is specifically:
Figure FDA0003598836490000021
wherein sig is the average energy of the locally known M reference pilot signal sequences.
7. Method for pilot signal based SNR estimation according to any of the claims 1 to 6, characterized in that said quadrature amplitude modulation is in particular 8QAM, 16QAM, 64QAM or 128 QAM.
8. An SNR estimation device based on pilot signals is characterized by comprising a signal extraction module, a noise calculation module, an SNR calculation module and an SNR correction module;
the signal extraction module is used for extracting an actual pilot signal from a received signal to be estimated;
the noise calculation module is used for calculating noise signal energy according to a locally known reference pilot signal and an actual pilot signal;
the SNR calculation module is used for calculating SNR according to locally known reference pilot signal energy and the noise signal energy;
and the SNR correction module is used for correcting the SNR according to the ratio of the energy of the reference pilot signal to the average energy of the system.
9. An apparatus for pilot signal based SNR estimation, comprising at least one processor and a memory, the at least one processor and the memory being coupled via a data bus, the memory storing instructions executable by the at least one processor, the instructions, upon execution by the processor, for performing the method for pilot signal based SNR estimation according to any one of claims 1 to 7.
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