CN114401175A - Method and device for determining white noise phase variance, electronic equipment and storage medium - Google Patents
Method and device for determining white noise phase variance, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application discloses a method and a device for determining a white noise phase variance, electronic equipment and a storage medium. The method comprises the following steps: determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, wherein the phase modulation signal is a phase signal carrying bit information in the received signal; determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power; and carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise. The phase variance of the white noise is obtained based on the scheme, so that the advanced signal detection and estimation method can utilize the white noise phase variance obtained by estimation to further improve the performance of a receiver of the phase modulation system.
Description
Technical Field
The embodiment of the application relates to the technical field of communication, in particular to a method and a device for determining a white noise phase variance, electronic equipment and a storage medium.
Background
With the development of communication technology, communication systems using different modulation techniques have appeared, wherein in a communication system using phase modulation as a modulation technique, bit information carried in a carrier is carried in a phase, and a receiver demodulates the bit information carried therein by extracting the phase of a received signal.
The signal received by the receiver can be superposed with white noise generated by an electronic device, the superposition of the noise is usually superposition on a complex domain, but the white noise superposed on the complex domain cannot be equivalently converted onto a phase domain, so that the receiver cannot model a noise component in the phase of the received signal, and for advanced signal detection and estimation methods capable of improving the performance of the receiver, because the noise component cannot be modeled, the methods cannot be applied to demodulation of a phase modulation signal, so that the performance of the receiver of a phase modulation system cannot be effectively improved.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining a white noise phase variance, an electronic device and a storage medium, so as to avoid the problem that the receiver performance of a phase modulation system cannot be effectively improved due to the fact that a noise component cannot be modeled and an advanced signal detection and estimation method cannot be applied to demodulation of a phase modulation signal.
In a first aspect, an embodiment of the present application provides a method for determining a white noise phase variance, where the method includes:
determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, wherein the phase modulation signal is a phase signal carrying bit information in the received signal;
determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and performing weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
In a second aspect, an embodiment of the present application further provides a device for determining a white noise phase variance, where the device for determining a white noise phase variance includes:
the device comprises an average power determining module, a phase modulation module and a power control module, wherein the average power determining module is used for determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, and the phase modulation signal is a phase signal carrying bit information in the received signal;
a variance value determining module for determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and the weighted average module is used for carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
In a third aspect, an embodiment of the present application further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method of determining a white noise phase variance as provided in any embodiment of the present application.
In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method for determining a white noise phase variance according to any embodiment of the present application.
According to the technical scheme of the embodiment of the application, a first noise phase variance value and a second noise phase variance value of white noise are determined based on a first average power of a received signal and a second average power of a phase modulation signal in the received signal, and the first noise phase variance value and the second noise phase variance value are weighted and averaged according to a preset weighting value to obtain the phase variance of the white noise, so that the high-level signal detection and estimation method can utilize the white noise phase variance obtained through estimation, and the performance of a receiver of a phase modulation system is further improved.
Drawings
Fig. 1 is a schematic flowchart of a method for determining a white noise phase variance according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a determination process of a noise phase estimation algorithm according to a second embodiment of the present application;
fig. 3 is a schematic structural diagram of a white noise phase variance determining apparatus according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
In the prior art, in a communication system using phase modulation as a modulation technique, transmitted bit information is carried on a phase of a carrier, and a receiver demodulates the bit information carried therein by extracting a phase of a received signal.
The signal received by the receiver can be superposed with white noise generated by an electronic device, the superposition of the noise is usually superposition on a complex domain, but the white noise superposed on the complex domain cannot be equivalently converted onto a phase domain, so that the receiver cannot model a noise component in the phase of the received signal, and for advanced signal detection and estimation methods capable of improving the performance of the receiver, because the noise component cannot be modeled, the methods cannot be applied to demodulation of a phase modulation signal, so that the performance of the receiver of a phase modulation system cannot be effectively improved.
In order to solve the above problem, the inventor proposes to determine a first noise phase variance value and a second noise phase variance value of the white noise by using a first average power and a second average power of a phase modulation signal in a received signal, and perform weighted averaging on the first noise phase variance value and the second noise phase variance value according to a preset weighted value to obtain a phase variance of the white noise.
Example one
Fig. 1 is a schematic flow chart of a method for determining a white noise phase variance according to an embodiment of the present disclosure, which is applicable to a scene of determining a white noise phase variance. The method can be executed by a device for determining the white noise phase variance, which can be implemented in a hardware and/or software manner and can be generally integrated in an electronic device such as a computer with data computing capability, and specifically includes the following steps:
In this step, the received signal refers to a signal received by a receiver in a communication system, and may be represented as y (t) ═ Aejφ(t)+ n (t), where n (t) is white noise superimposed on the received signal, n (t) has a mean of 0 and a variance of σ2。Aejφ(t)Is a phase modulated signal, and carries the transmitted bit information in phi (t). It should be noted that the phase modulation signal is a useful signal portion of the received signal due to the phase signal carrying the bit information.
Exemplary, Aejφ(t)May be a cpm (continuous Phase modulation) modulated signal, where phi (t) is 2 pi sigmai≤nαihiq (T-iT), nT is less than or equal to T is less than or equal to (n +1) T, wherein alphaiIs the modulation value on the i-th symbol, mapped by the transmission bit, hiIs the modulation index, T is the symbol period, and q (T) is the phase response function.
It should be noted that, in this step, the first average power of the received signal is determined, and may be calculated by using a preset formula, and in a specific example, the formula may be
Where T is the symbol period and y (T) is the received signal.
In addition, for the second average power of the phase modulation signal, a conjugate signal corresponding to the local reference signal may be obtained first, where the conjugate signal and the local reference signal have conjugate symmetry. A second average power of the phase modulated signal in the received signal is then determined based on the conjugate signal and the received signal.
Specifically, the received signal may be multiplied by the conjugate signal, and then the average power of the product is calculated, which is the second average power of the phase modulation signal. It should be noted that, since the signal characteristics of the phase modulation signal in the received signal and the local reference signal are the same, the white noise in the received signal can be eliminated to some extent by multiplying the received signal by the conjugate signal, and the average power of the product can be calculated and used as the second average power of the phase modulation signal.
In a specific example, the second average power may be calculated as
Where T is the symbol period, y (T) is the received signal, (Ae)jφ(t))*Is a conjugate signal.
In this step, the average power of the white noise may be obtained, and since the average power of the received signal, i.e. the first average power, and the average power of the phase modulation signal in the received signal, i.e. the second average power, have been obtained in the previous step, the average power of the white noise may be the difference between the first average power and the second average power because the received signal is composed of the phase modulation signal and the white noise signal.
It should be noted that the variance of the white noise is the same as the average power of the white noise, and therefore, the average power of the white noise can be determined as the variance of the white noise, that is, σ2＝P-PSWhere P is the first average power, PSIs a secondThe average power.
In addition, after the variance of the white noise is obtained, the first noise phase variance value and the second noise phase variance value can be determined by using a predetermined first noise phase estimation algorithm and a predetermined second noise phase strand calculation method. Specifically, the variance of the white noise and the second average power may be input into the first noise phase estimation algorithm, so as to obtain a first noise phase variance value output by the first noise phase estimation algorithm; and inputting the variance of the white noise and the first average power into a second noise phase estimation algorithm to obtain a second noise phase variance value output by the second noise phase estimation algorithm.
Wherein, the algorithm formula corresponding to the first noise phase estimation algorithm can be expressed as σ2/2A2Wherein σ is2Variance of white noise, A2Is the average power of the phase modulated signal; the algorithm formula corresponding to the second noise phase estimation algorithm can be expressed as sigma2/2|y(t)|2Wherein σ is2Is the variance of white noise, | y (t) & gtnon-woven phosphor2Is the average power of the received signal.
It should be noted that, the determination of the first noise phase estimation algorithm and the second noise phase estimation algorithm will be described in the following embodiments, and details are not described here.
And 103, carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
In this step, a weight value corresponding to the signal-to-noise ratio of the received signal may be determined from a predetermined signal-to-noise ratio weight value mapping table, and then the first noise phase variance value and the second noise phase variance value are weighted and averaged based on the weight value, and the obtained weighted average value is determined as the phase variance of the white noise.
It should be noted that, different signal-to-noise ratios and different degrees of influence of two phase variance values on the phase variance of the final white noise are different, so in this embodiment, a signal-to-noise ratio weight value mapping table is predetermined, and in this table, weight values corresponding to different signal-to-noise ratios are stored, in a specific example, this table may be as shown in table 1 below, and the data shown in table 1 is only an example.
TABLE 1
| SNR/dB | α | β |
| -2 | 0.05 | 0.95 |
| -1 | 0.1 | 0.9 |
| 0 | 0.15 | 0.85 |
| … | … | … |
Specifically, the weighted average process may be based on the formula
Wherein the content of the first and second substances,
is the phase variance of the white noise,
is the first noise phase variance value and is,
is the second noise phase variance value.
If the snr of the received signal is-1, it can be known from table 1 that the weight value α is 0.1 and the weight value β is 0.9, and the phase variance of the white noise can be obtained by substituting the two weight values into the above formula.
The signal-to-noise ratio weight value mapping table can be obtained by a Monte Carlo numerical simulation method, and specifically, for received signals with different signal-to-noise ratios, the phase variance of the received signals, a first noise phase variance value and a second noise phase variance value are calculated; then fitting weighted values corresponding to different signal-to-noise ratios based on the phase variance of the received signals corresponding to different signal-to-noise ratios, the first noise phase variance value and the second noise phase variance value by utilizing a Monte Carlo numerical simulation method; and finally, mapping to obtain a signal-to-noise ratio weight value mapping table according to the corresponding relation between different signal-to-noise ratios and weight values.
Wherein the calculation of the phase variance of the received signal, the first noise phase variance value and the second noise phase variance value may be based on
The signal-to-noise ratio of the received signal may be expressed as SNR PS/σ2。
Specifically, when the monte carlo value is simulated, the useful signal and the noise in the received signal are known, so that the phase component of the useful signal (i.e., the phase modulation signal) and the phase component of the white noise are also known in the phase domain, and the value is directly used for statistical calculation. It should be noted that, for specific details, reference may be made to a monte carlo numerical simulation method in the related art, which is not described herein again.
In this embodiment, a first noise phase variance value and a second noise phase variance value of the white noise are determined based on a first average power of the received signal and a second average power of the phase modulation signal in the received signal, and the first noise phase variance value and the second noise phase variance value are weighted and averaged according to a preset weighting value to obtain a phase variance of the white noise, so that the advanced signal detection and estimation method can further improve the performance of the receiver of the phase modulation system by using the white noise phase variance obtained by estimation.
Example two
Fig. 2 is a schematic diagram of a determination process of a noise phase estimation algorithm according to a second embodiment of the present application.
As shown in fig. 2, the determining process of the noise phase estimation algorithm provided by this embodiment may include:
In the foregoing embodiment, it has been described that the received signal corresponds to the expression y (t) ═ Aejφ(t)+ n (t). In this step, n (t) can be projected towards phi (t) to obtain a component u of n (t) parallel to phi (t)I(n) and a component u perpendicular to phi (t)Q(n)，uI(n) and uQ(n) are all mean values of 0 and variance σ2White noise of/2.
Will uI(n) and uQ(n) substitution into y (t) ([ A + u (n))]ejφ(t)Wherein u (n) uI(n)+juQ(n), then, y (t) ═ A + u (n) can be obtained]ejφ(t)＝[A+uI(n)+juQ(n)]ejφ(t). Where a represents amplitude.
Based on the formula, the white noise has the following two expressions, wherein the first expression is
The second expression is
It should be noted that the first approximation condition is a high signal-to-noise ratio
And arctan (x) x; wherein u isI(n) is the noise component parallel to phi (t), uQ(n) is the noise component perpendicular to φ (t), φ (t) is the time-varying phase, and A is the amplitude.
Based on the first approximation condition, white noise can be approximated as
Therefore, the corresponding first noise phase estimation algorithm has a phase variance of σ2/2A2。
And step 203, performing approximate conversion on the second expression based on a second approximate condition, and determining a second noise phase estimation algorithm according to the result of the approximate conversion.
In this step, the second approximation condition is
Based on the second approximation condition, white noise can be approximated as
Therefore, the corresponding second noise phase estimation algorithm has a phase variance of σ2/2|y(t)|2。
EXAMPLE III
Fig. 3 is a schematic structural diagram of a white noise phase variance determining apparatus according to a third embodiment of the present application. The device for determining the white noise phase variance provided by the embodiment of the application can execute the method for determining the white noise phase variance provided by any embodiment of the application, and has corresponding functional modules and beneficial effects of the execution method. The device can be implemented by software and/or hardware, and as shown in fig. 3, the device for determining the white noise phase variance specifically includes: an average power determination module 301, a variance value determination module 302, and a weighted average module 303.
The average power determining module is configured to determine a first average power of a received signal and a second average power of a phase modulation signal in the received signal, where the phase modulation signal is a phase signal carrying bit information in the received signal;
a variance value determining module for determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and the weighted average module is used for carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value and determining the obtained weighted average value as the phase variance of the white noise.
In this embodiment, a first noise phase variance value and a second noise phase variance value of the white noise are determined based on a first average power of the received signal and a second average power of the phase modulation signal in the received signal, and the first noise phase variance value and the second noise phase variance value are weighted and averaged according to a preset weighting value to obtain a phase variance of the white noise, so that the advanced signal detection and estimation method can further improve the performance of the receiver of the phase modulation system by using the white noise phase variance obtained by estimation.
Further, the average power determination module comprises:
and the average power determining unit is used for acquiring a conjugate signal corresponding to the local reference signal and determining a second average power of the phase modulation signal in the received signal based on the conjugate signal and the received signal.
Further, the variance value determining module includes:
a first determining unit for determining a difference between the first average power and the second average power as an average power of white noise and determining an average power of the white noise as a variance of the white noise;
the first acquisition unit is used for inputting the variance of the white noise and the second average power into a first noise phase estimation algorithm and acquiring a first noise phase variance value output by the first noise phase estimation algorithm;
and the second acquisition unit is used for inputting the variance of the white noise and the first average power into a second noise phase estimation algorithm and acquiring a second noise phase variance value output by the second noise phase estimation algorithm.
Further, the apparatus further comprises:
the expression determining module is used for determining a first expression and a second expression of a noise component corresponding to white noise on a phase domain;
the first algorithm determining module is used for performing approximate conversion on the first expression based on a first approximate condition and determining a first noise phase estimation algorithm according to the result of the approximate conversion;
and the second algorithm determining module is used for performing approximate conversion on the second expression based on a second approximate condition and determining a second noise phase estimation algorithm according to the result of the approximate conversion.
Further, the first approximation condition is a high signal-to-noise ratio
And arctan (x) x; wherein u isI(n) is the noise component parallel to phi (t), uQ(n) is the noise component perpendicular to phi (t);
the second approximation condition is
Further, the weighted average module comprises:
the weight determining unit is used for determining a weight value corresponding to the signal-to-noise ratio of the received signal from a predetermined signal-to-noise ratio weight value mapping table;
and the weighted average unit is used for carrying out weighted average on the first noise phase variance value and the second noise phase variance value based on the weight value and determining the obtained weighted average value as the phase variance of the white noise.
Further, the apparatus further comprises:
the table determining module is used for determining a signal-to-noise ratio weight value mapping table in advance;
the table determination module includes:
the calculating unit is used for calculating the phase variance of the received signals, the first noise phase variance value and the second noise phase variance value for the received signals with different signal-to-noise ratios;
the fitting unit is used for fitting weighted values corresponding to different signal-to-noise ratios based on the phase variance of the received signals corresponding to the different signal-to-noise ratios, the first noise phase variance value and the second noise phase variance value by using a Monte Carlo numerical simulation method;
and the mapping unit is used for mapping to obtain a signal-to-noise ratio weight value mapping table according to the corresponding relation between different signal-to-noise ratios and weight values.
Example four
Fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present disclosure, as shown in fig. 4, the electronic device includes a processor 410, a memory 420, an input device 430, and an output device 440; the number of the processors 410 in the electronic device may be one or more, and one processor 410 is taken as an example in fig. 4; the processor 410, the memory 420, the input device 430 and the output device 440 in the electronic apparatus may be connected by a bus or other means, and the bus connection is exemplified in fig. 4.
The memory 420 serves as a computer-readable storage medium for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the determination method of white noise phase variance in the embodiment of the present invention (for example, the average power determination module 301, the variance value determination module 302, and the weighted average module 303 in the determination device of white noise phase variance). The processor 410 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the memory 420, that is, the method for determining the white noise phase variance as described above is implemented:
determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, wherein the phase modulation signal is a phase signal carrying bit information in the received signal;
determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
Further, determining a second average power of the phase modulated signal in the received signal comprises:
and acquiring a conjugate signal corresponding to the local reference signal, and determining a second average power of the phase modulation signal in the received signal based on the conjugate signal and the received signal.
Further, determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power includes:
determining the difference between the first average power and the second average power as the average power of the white noise, and determining the average power of the white noise as the variance of the white noise;
inputting the variance of the white noise and the second average power into a first noise phase estimation algorithm to obtain a first noise phase variance value output by the first noise phase estimation algorithm;
and inputting the variance of the white noise and the first average power into a second noise phase estimation algorithm to obtain a second noise phase variance value output by the second noise phase estimation algorithm.
Further, the method further comprises:
determining a first expression and a second expression of a noise component corresponding to white noise on a phase domain;
performing approximate conversion on the first expression based on a first approximate condition, and determining a first noise phase estimation algorithm according to the result of the approximate conversion;
the second expression is approximately converted based on a second approximation condition, and a second noise phase estimation algorithm is determined according to a result of the approximate conversion.
Further, the first approximation condition is a high signal-to-noise ratio
And arctan (x) x; wherein u isI(n) is the noise component parallel to phi (t), uQ(n) is the noise component perpendicular to phi (t);
the second approximation condition is
Further, performing weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise, including:
determining a weight value corresponding to the signal-to-noise ratio of the received signal from a predetermined signal-to-noise ratio weight value mapping table;
and carrying out weighted average on the first noise phase variance value and the second noise phase variance value based on the weight value, and determining the obtained weighted average value as the phase variance of the white noise.
Further, the method further comprises:
predetermining a signal-to-noise ratio weight value mapping table;
predetermining a signal-to-noise ratio weight value mapping table comprising:
for received signals with different signal-to-noise ratios, calculating a phase variance of the received signals, a first noise phase variance value and a second noise phase variance value;
fitting weighted values corresponding to different signal-to-noise ratios based on phase variances of received signals corresponding to different signal-to-noise ratios, the first noise phase variance value and the second noise phase variance value by using a Monte Carlo numerical simulation method;
and mapping to obtain a signal-to-noise ratio weight value mapping table according to the corresponding relation between different signal-to-noise ratios and weight values.
The memory 420 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 420 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 examples, memory 420 may further include memory located remotely from processor 410, which may be connected to an electronic device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
EXAMPLE five
A storage medium containing computer-executable instructions for performing a method for determining white noise phase variance when executed by a computer processor, the method comprising:
determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, wherein the phase modulation signal is a phase signal carrying bit information in the received signal;
determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
Further, determining a second average power of the phase modulated signal in the received signal comprises:
and acquiring a conjugate signal corresponding to the local reference signal, and determining a second average power of the phase modulation signal in the received signal based on the conjugate signal and the received signal.
Further, determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power includes:
determining the difference between the first average power and the second average power as the average power of the white noise, and determining the average power of the white noise as the variance of the white noise;
inputting the variance of the white noise and the second average power into a first noise phase estimation algorithm to obtain a first noise phase variance value output by the first noise phase estimation algorithm;
and inputting the variance of the white noise and the first average power into a second noise phase estimation algorithm to obtain a second noise phase variance value output by the second noise phase estimation algorithm.
Further, the method further comprises:
determining a first expression and a second expression of a noise component corresponding to white noise on a phase domain;
performing approximate conversion on the first expression based on a first approximate condition, and determining a first noise phase estimation algorithm according to the result of the approximate conversion;
the second expression is approximately converted based on a second approximation condition, and a second noise phase estimation algorithm is determined according to a result of the approximate conversion.
Further, the first approximation condition is a high signal-to-noise ratio
And arctan (x) x; wherein u isI(n) is the noise component parallel to phi (t), uQ(n) is the noise component perpendicular to phi (t);
the second approximation condition is
Further, performing weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise, including:
determining a weight value corresponding to the signal-to-noise ratio of the received signal from a predetermined signal-to-noise ratio weight value mapping table;
and carrying out weighted average on the first noise phase variance value and the second noise phase variance value based on the weight value, and determining the obtained weighted average value as the phase variance of the white noise.
Further, the method further comprises:
predetermining a signal-to-noise ratio weight value mapping table;
predetermining a signal-to-noise ratio weight value mapping table comprising:
for received signals with different signal-to-noise ratios, calculating a phase variance of the received signals, a first noise phase variance value and a second noise phase variance value;
fitting weighted values corresponding to different signal-to-noise ratios based on phase variances of received signals corresponding to different signal-to-noise ratios, the first noise phase variance value and the second noise phase variance value by using a Monte Carlo numerical simulation method;
and mapping to obtain a signal-to-noise ratio weight value mapping table according to the corresponding relation between different signal-to-noise ratios and weight values.
Of course, the storage medium provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the above method operations, and may also perform related operations in the method for determining a white noise phase variance provided in any embodiments of the present application.
From the above description of the embodiments, it is obvious for those skilled in the art that the present application can be implemented by software and necessary general hardware, and certainly can be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods of the embodiments of the present application.
It should be noted that, in the embodiment of the above search apparatus, each included unit and module are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only used for distinguishing one functional unit from another, and are not used for limiting the protection scope of the application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments illustrated herein, and that various obvious changes, rearrangements and substitutions may be made therein by those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. A method for determining a white noise phase variance, the method comprising:
determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, wherein the phase modulation signal is a phase signal carrying bit information in the received signal;
determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and performing weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
2. The method of claim 1, wherein determining the second average power of the phase modulated signal in the received signal comprises:
acquiring a conjugate signal corresponding to a local reference signal, and determining a second average power of a phase modulation signal in the received signal based on the conjugate signal and the received signal.
3. The method of claim 1, wherein determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power comprises:
determining a difference between the first average power and the second average power as an average power of the white noise, and determining the average power of the white noise as a variance of the white noise;
inputting the variance of the white noise and the second average power into a first noise phase estimation algorithm to obtain a first noise phase variance value output by the first noise phase estimation algorithm;
and inputting the variance of the white noise and the first average power into a second noise phase estimation algorithm to obtain a second noise phase variance value output by the second noise phase estimation algorithm.
4. The method of claim 3, further comprising:
determining a first expression and a second expression of a noise component corresponding to white noise on a phase domain;
performing approximate conversion on the first expression based on a first approximate condition, and determining a first noise phase estimation algorithm according to the result of the approximate conversion;
and performing approximate conversion on the second expression based on a second approximate condition, and determining a second noise phase estimation algorithm according to the result of the approximate conversion.
5. The method of claim 4, wherein the first approximation condition is a high signal-to-noise ratio
And arctan (x) x; wherein u isI(n) is the noise component parallel to phi (t), uQ(n) is the noise component perpendicular to phi (t), which is the time-varying phaseAnd A is amplitude;
the second approximation condition is
6. The method according to claim 1, wherein the performing a weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining a resulting weighted average as the phase variance of the white noise comprises:
determining a weight value corresponding to the signal-to-noise ratio of the received signal from a predetermined signal-to-noise ratio weight value mapping table;
and carrying out weighted average on the first noise phase variance value and the second noise phase variance value based on the weight value, and determining the obtained weighted average value as the phase variance of the white noise.
7. The method of claim 6, further comprising:
predetermining a signal-to-noise ratio weight value mapping table;
the predetermined signal-to-noise ratio weight value mapping table comprises:
for received signals with different signal-to-noise ratios, calculating a phase variance of the received signals, a first noise phase variance value and a second noise phase variance value;
fitting weighted values corresponding to different signal-to-noise ratios based on the phase variance of the received signals corresponding to the different signal-to-noise ratios, the first noise phase variance value and the second noise phase variance value by using a Monte Carlo numerical simulation method;
and mapping to obtain the signal-to-noise ratio weight value mapping table according to the corresponding relation between different signal-to-noise ratios and weight values.
8. An apparatus for determining a white noise phase variance, the apparatus comprising:
the device comprises an average power determining module, a phase modulation module and a power control module, wherein the average power determining module is used for determining a first average power of a received signal and a second average power of a phase modulation signal in the received signal, and the phase modulation signal is a phase signal carrying bit information in the received signal;
a variance value determining module for determining a first noise phase variance value and a second noise phase variance value based on the first average power and the second average power;
and the weighted average module is used for carrying out weighted average on the first noise phase variance value and the second noise phase variance value according to a preset weighted value, and determining the obtained weighted average value as the phase variance of the white noise.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method for determining white noise phase variance as recited in any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method for determining a white noise phase variance according to any one of claims 1 to 7.
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