CN115664561A - Polarity-metric phase noise communication detection method, communication device, and medium - Google Patents
Polarity-metric phase noise communication detection method, communication device, and medium Download PDFInfo
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Abstract
The polarity-metric phase noise communication detection method, the communication equipment and the medium provided by the invention comprise the steps of simplifying polarity metric and symbol detection into threshold comparison, firstly converting the phase noise of a received signal from Euclidean distance into a coordinate system, analyzing a noise model of the received noise under Gaussian noise, defining polarity metric, and finally adopting a detection rule defined by a maximum likelihood decision standard.
Description
Technical Field
The present invention relates to the field of communications, and in particular, to a method, a device, and a medium for detecting phase noise communications in polar measurement.
Background
With the increasing demand of high-speed communication frequency in the GHz level, such as 5G communication, laser communication between satellites. A high frequency communication clock is generated by an oscillator, but the oscillator may seriously deteriorate communication performance due to phase noise at a high frequency. In order to solve the problem of phase noise of the high-frequency oscillator, additional breakthrough technology is needed. The most advanced approach is to use coherent systems with channel bonding, this type of architecture needs to be further combined with signal processing optimization to mitigate the effects of phase impairments. Therefore, one challenge that needs to be addressed by high frequency communication phase noise is to design a robust communication modem scheme that is subject to strong phase noise.
Disclosure of Invention
In view of the above, embodiments of the present invention provide a method, a communication device, and a medium for detecting phase noise communication of a polarity metric.
In a first aspect, the present invention provides a method for detecting phase noise communication of a polarimetric, including:
converting the phase noise of the received signal from the Euclidean distance into a coordinate system by utilizing a first preset relation;
and analyzing a phase noise model of the received signal under Gaussian noise by using a second preset relation and defining polarity measurement, wherein the polarity measurement adopts symbol-by-symbol detection, and the symbol error probability passes through a maximum likelihood decision standard.
As an alternative, the converting the phase noise of the received signal from the euclidean distance to the coordinate system using the first preset relationship includes:
the likelihood function is written as (1)
α(β|χ)＝α(β ρ ，β θ |χ p ，χ θ ) (1)
Denotes the coordinate system (χ) p ，χ θ ) To a coordinate system (beta) p ，β θ ) The transformation of (1);
amplitude beta of the received symbol ρ Is given by the following formula (2)
And the phase beta of the received symbol θ Is obtained from the following formula (3)
Wherein the phase noise is represented by n
The method represents the circularly symmetric complex Gaussian zero mean under the thermal noise modeling, phi represents the noise phase, and since the complex noise is circularly symmetric, n and n' are distributed in the same way.
As an alternative, the analyzing a noise model of the received signal under gaussian noise by using a second preset relationship and defining a polarity metric, where the polarity metric uses symbol-by-symbol detection, and a symbol error probability passes through a maximum likelihood decision criterion includes:
let equations (2) and (3) be first order approximations, then
Under the assumption of high signal-to-noise ratio, the channel likelihood function is expressed as a binary gaussian distribution, as shown in the following formula (4):
using the phase noise channel model, the maximum likelihood decision criteria rule is given by equation (5) below
Wherein d is γ Is a polarity measure defined by the following formula (6)
Wherein
As an alternative, the probability of correct detection is proportional to the integral of the likelihood function over the Voronoi region of symbols, the larger the area of which, the smaller the probability of symbol error, the smallest the area of which is the optimal detection scheme.
As an alternative, the evaluation criterion of the maximum likelihood decision criterion is a minimum distance in relation to polar coordinates, the detected symbol being the closest received polar symbol, and the polar coordinates being a weighted combination of amplitude and phase of the received symbol.
In a second aspect, the present invention provides a communication device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the polar metric phase noise communication detection method of any one of claims 1 to 5.
In a third aspect, the present invention provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method of phase noise communication detection of a polarity metric of any one of claims 1 to 5.
The polarity-metric phase noise communication detection method, the communication equipment and the medium provided by the invention comprise the steps of simplifying polarity metric and symbol detection into threshold comparison, firstly converting the phase noise of a received signal from Euclidean distance into a coordinate system, analyzing a noise model of the received noise under Gaussian noise, defining polarity metric, and finally adopting a detection rule defined by a maximum likelihood decision standard.
Drawings
Fig. 1 is a flow chart of a method for detecting phase noise communication with polarimetric measurement according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an euclidean distance of quadrature amplitude modulation with 16 signal points in a method for detecting phase noise communication with polarimetric according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a conventional polar coordinate of quadrature amplitude modulation with 16 signal points in a phase noise communication detection method for polar metrology according to an embodiment of the present invention;
fig. 4 is a schematic diagram of polar metric coordinates of quadrature amplitude modulation with 16 signal points in a polar metric phase noise communication detection method according to an embodiment of the present invention;
fig. 5 is a block diagram of a communication device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Referring to fig. 1, the present invention provides a method for detecting phase noise communication of a polarimetric, including:
s101, converting phase noise of a received signal from a Euclidean distance into a coordinate system by utilizing a first preset relation;
s102, analyzing a phase noise model of the received signal under Gaussian noise by using a second preset relation, and defining polarity measurement, wherein the polarity measurement adopts symbol-by-symbol detection, and the symbol error probability passes through a maximum likelihood decision standard.
The invention provides a phase noise communication detection method of polarity measurement, which comprises the steps of simplifying polarity measurement and symbol detection into threshold comparison, firstly converting the phase noise of a received signal from Euclidean distance into a coordinate system, analyzing a noise model of the received noise under Gaussian noise, defining polarity measurement, and finally adopting a detection rule defined by a maximum likelihood decision standard.
In some embodiments, the converting the phase noise of the received signal from the euclidean distance to the coordinate system using the first predetermined relationship includes:
the likelihood function is written as (1)
α(β|χ)＝α(β ρ ，β θ |χ p ，χ θ ) (1)
Denotes the coordinate system (χ) p ，χ θ ) To a coordinate system (beta) p ，β θ ) The transformation of (1);
amplitude beta of the received symbol ρ Is given by the following formula (2)
And the phase beta of the received symbol θ Is obtained from the following formula (3)
Wherein the phase noise is represented by n
n represents the circularly symmetric complex Gaussian zero mean under the thermal noise modeling, phi represents the noise phase, and since the complex noise is circularly symmetric, n and n' are distributed in the same way.
In this embodiment, the first preset relationship may include formulas (1), (2), and (3).
In some embodiments, said analyzing a noise model of said received signal under gaussian noise using a second predetermined relationship and defining a polarity metric, said polarity metric using symbol-by-symbol detection, and a symbol error probability passing a maximum likelihood decision criterion, comprises:
let equations (2) and (3) be first order approximations, then
Under the assumption of high signal-to-noise ratio, the channel likelihood function is expressed as a binary gaussian distribution, as shown in the following formula (4):
using the phase noise channel model, the maximum likelihood decision criteria rule is given by equation (5) below
Wherein d is γ Is a polarity measure defined by the following formula (6)
Wherein
In this embodiment, the second preset relationship may include formulas (4), (5), and (5).
In some embodiments, the probability of correct detection is proportional to the integral of the likelihood function over a Voronoi region of symbols, the larger the area of which the smallest is the optimal detection scheme, the smaller the probability of symbol error.
In some embodiments, the evaluation criterion of the maximum likelihood decision criterion is a minimum distance associated with a polar coordinate, the detected symbol being the closest received polar symbol, the polar coordinate being a weighted combination of amplitude and phase of the received symbol.
The embodiment of the invention also provides a phase noise communication detection method of polarity measurement, which specifically comprises the following steps:
and detecting one symbol by one symbol, wherein the symbol error probability passes through a maximum likelihood decision criterion. The likelihood function can be written as follows
α(β|χ)＝α(β ρ ，β θ |χ p ，χ θ ) (1)
Denotes the coordinate system (χ) p ，χ θ ) To a coordinate system (beta) p ，β θ ) And (4) transforming. Expressing phase noise by n
n represents the circularly symmetric complex Gaussian zero mean under the thermal noise modeling, and phi represents the noise phase. Since the complex noise is circularly symmetric, n and n' are equally distributed. In which symbols beta are received ρ Is given by
And phase beta θ Is derived from the following
The latter two equations consider the transmission of non-zero symbols. If the zero symbol is transmitted, the received signal is only damaged by the gaussian noise, and the following continues to describe the noise model of the received signal under the gaussian noise. The first order approximation of equation (2) and equation (3) is critical at high signal-to-noise ratios. Since the goal of this work is high data rate applications, it is reasonable to assume a high signal-to-noise ratio to allow the use of higher order modulation schemes. Thus, channel and phase noise models can be derived under the assumption of high signal-to-noise ratio.
The channel likelihood function may be expressed as a binary gaussian distribution:
using a phase noise channel model, the decision rule is given by
Wherein d is γ Is a polarity metric defined by
Wherein
The proposed detection criterion is the minimization of the distance associated with the polar coordinates, the detected symbol being the closest received polar symbol, this process being the nearest neighbor search. The measure of polarity being the amplitude of the received symbolAnd a weighted combination of phases.
Specifically, the minimum probability of symbol error of the communication channel under the polarity is calculated, the point number is fixed to M, and the average energy of the polarity is limited to Es. The symbol error probability is defined in terms of its complementary events (probability of correct detection).
Probability of correct detection and for detection rules defined according to maximum likelihood decision criteria
The integrals of likelihood functions over the Voronoi region of symbols (Voronoi) are proportional.
That is
Shown in connection with FIGS. 2, 3 and 4, wherein v s Are the symbols of the Voronoi regions of the χ and α (β | χ) channel likelihood functions. Therefore, the larger the area of the Voronoi region, the smaller the error probability. As can be clearly seen in fig. 2, the euclidean distance does not maximize the Voronoi region area of the polar coordinate system and is therefore not optimized for the communication link. Fig. 3 shows a circular noise distribution of the polar coordinates of the phase noise under the conditions of high snr and strong phase noise at the coordinates defined on the lattice on the amplitude-phase plane. Fig. 4 uses a rectangular polar lattice to define the modulation scheme, which attenuates to simplify decompression implementation. Since the average energy of modulation order and polarity is fixed, the problem of finding the area of the maximized Voronoi region can be seen as finding the densest sphere packing in two dimensions. The highest density in the plane is achieved by a hexagonal lattice. The coordinates based on the hexagonal structure maximize the Voronoi region area, thereby minimizing the symbol error probability.
Under low signal-to-noise ratio conditions, the channel noise is dominated by thermal noise, and even in the presence of strong phase noise, the conventional coordinate system error can be high. In contrast, polar-metric-based coordinate systems achieve significant peak-to-gain and low error rate communications over strong phase noise channels.
The polarity measurement method in the phase noise communication detection method for polarity measurement provided by the embodiment of the invention realizes a high signal-to-noise ratio demodulation scheme in a communication link under strong phase noise in a simpler coordinate axis mode. Including using a polarity metric and symbol detection to reduce to a threshold comparison. Firstly, converting the phase noise of a received signal from Euclidean distance into a coordinate system through a formula (1-3), then analyzing a noise model of the received noise under Gaussian noise through a formula (4-5), defining polarity measurement, and finally adopting a detection rule defined by a maximum likelihood standard rule, wherein the probability of correct detection is in direct proportion to the integral of a likelihood function on a symbol Voronoi area, and the larger the area of the Voronoi area is, the smaller the error probability is, and the smallest area of the Voronoi area is the optimal detection scheme.
Specifically, the polarity metric employs symbol-by-symbol detection, with the symbol error probability passing through a maximum likelihood decision criterion. The evaluation criterion is the minimum distance in relation to the polar coordinates. The detected symbol is the closest received polarity symbol, i.e. the nearest neighbor search, and the polar coordinate is a weighted combination of the amplitude and phase of the received symbol.
Compared with the prior art, the scheme provided by the invention can achieve the following technical effects:
1. as the phase noise becomes stronger, the detection becomes more and more dependent on the amplitude of the received symbol rather than the phase. Using a joint amplitude-phase detector instead of a euclidean detector would yield valuable detection performance gains.
2. By using an appropriate detection criterion, the error layer in the symbol detection caused by phase noise is significantly reduced.
Accordingly, the invention also provides a communication device, a readable storage medium and a computer program product according to the embodiments of the invention.
Fig. 5 is a schematic structural diagram of a communication device 12 provided in an embodiment of the present invention. Fig. 5 illustrates a block diagram of an exemplary communication device 12 suitable for use in implementing embodiments of the present invention. The communication device 12 shown in fig. 5 is only an example and should not impose any limitation on the functionality and scope of use of embodiments of the present invention.
As shown in fig. 5, the communication device 12 is in the form of a general purpose computing device. The communication device 12 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
The components of communication device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. Communication device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The communication device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), with one or more devices that enable a user to interact with the communication device 12, and/or with any devices (e.g., network card, modem, etc.) that enable the communication device 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 22. Also, the communication device 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 20. As shown, the network adapter 20 communicates with the other modules of the communication device 12 via the bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with communication device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes programs stored in the system memory 28 to perform various functional applications and data processing, such as implementing the polarity metric phase noise communication detection method provided by the embodiments of the present invention.
The embodiment of the invention also provides a non-transitory computer readable storage medium which stores computer instructions and stores a computer program, wherein the program is executed by a processor to carry out the polarity-metric phase noise communication detection method provided by all the invention embodiments of the application.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing. Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, or the like, as well as conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
Embodiments of the present invention also provide a computer program product, which includes a computer program that, when executed by a processor, implements a phase noise communication detection method according to the above-described polarity metric.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed herein can be achieved, and the present disclosure is not limited herein.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. A method for polar metric phase noise communication detection, comprising:
converting the phase noise of the received signal from the Euclidean distance into a coordinate system by utilizing a first preset relation;
and analyzing a phase noise model of the received signal under Gaussian noise by using a second preset relation and defining polarity measurement, wherein the polarity measurement adopts symbol-by-symbol detection, and the symbol error probability passes through a maximum likelihood decision standard.
2. The method of claim 1, wherein the transforming the phase noise of the received signal from euclidean distance to a coordinate system using the first predetermined relationship comprises:
the likelihood function is written as (1)
α(β|χ)＝α(β ρ ，β θ |χ p ，χ θ ) (1)
Denotes the coordinate system (χ) p ，χ θ ) To a coordinate system (. Beta.) p ，β θ ) The transformation of (1);
amplitude beta of the received symbol ρ Is given by the following formula (2)
And the phase beta of the received symbol θ Is obtained from the following formula (3)
Wherein n' represents the phase noise n.e -j(χθ+φ) N represents a circularly symmetrical complex Gaussian zero mean value under the thermal noise modeling, phi represents a noise phase, and since the complex noise is circularly symmetrical, n and n' are distributed in the same way.
3. The method of claim 2, wherein the analyzing a noise model of the received signal under gaussian noise using a second predetermined relationship and defining a polarity metric, the polarity metric using symbol-by-symbol detection, and a symbol error probability passing a maximum likelihood decision criterion comprises:
let equations (2) and (3) be first order approximations, then
Under the assumption of high signal-to-noise ratio, the channel likelihood function is expressed as a binary gaussian distribution, as shown in the following formula (4):
using the phase noise channel model, the maximum likelihood decision criteria rule is given by equation (5) below
Wherein d is γ Is a polarity measure defined by the following formula (6)
Wherein
4. The polar-metric phase noise communication detection method according to claim 1, wherein the probability of correct detection is proportional to the integral of the likelihood function over a Voronoi region of symbols, the larger the area of the Voronoi region is, the smaller the probability of symbol error is, and the smallest area of the Voronoi region is the optimal detection scheme.
5. The polar metric phase noise communication detection method of claim 1, wherein the evaluation criterion of the maximum likelihood decision criterion is a minimum distance associated with a polar coordinate, the detected symbol being the closest received polar symbol, the polar coordinate being a weighted combination of amplitude and phase of the received symbol.
6. A communication device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the polar metric phase noise communication detection method of any one of claims 1 to 5.
7. A non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the method of detecting phase noise communication of a polarity metric of any one of claims 1 to 5.
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