CN109067691B

CN109067691B - OFDM data processing method and device

Info

Publication number: CN109067691B
Application number: CN201810983245.9A
Authority: CN
Inventors: 王亚军; 谢爽; 王蒙萌
Original assignee: Jiangsu University of Science and Technology
Current assignee: Wuxi Bofan Technology Co ltd
Priority date: 2018-08-27
Filing date: 2018-08-27
Publication date: 2021-03-26
Anticipated expiration: 2038-08-27
Also published as: CN109067691A

Abstract

The embodiment of the invention provides an OFDM data processing method and device, and relates to the technical field of wireless communication. The method comprises the steps of obtaining an OFDM symbol with N subcarriers, obtaining a discrete time baseband OFDM signal and an error vector amplitude based on the OFDM symbol, establishing an error vector amplitude optimization model with infinite series constraint based on the OFDM signal and the error vector amplitude, generating an iteration update expression of the discrete time baseband OFDM signal based on an alternating direction multiplier method and the error vector amplitude optimization model, continuously iterating and calculating the iteration update expression until a preset iteration number is met, and outputting an optimized OFDM time domain signal. The alternative direction multiplier method is used, peak-to-average ratio is reduced, cutting and filtering operations are not needed, an optimal cutting threshold value is not needed, and the method is more efficient.

Description

OFDM data processing method and device

Technical Field

The present invention relates to the field of wireless communication technologies, and in particular, to an OFDM data processing method and apparatus.

Background

Orthogonal Frequency Division Multiplexing (OFDM) has been widely used in many fields due to its inherent stability against multipath fading and suppression of narrow-band interference. However, one major drawback of OFDM signals is that the transmitted signal has a high peak-to-average ratio. In recent years, many methods have been proposed to solve this problem, but these methods have disadvantages. In order to obtain a satisfactory Peak to Average Power Ratio (PAPR), abbreviated as PAPR, the conventional OICF method utilizes a second order cone method (SOCP) to solve the PAPR problem. This method improves the convergence of ICF, but with a computational complexity of O (N)³) (N is the number of subcarriers). Simplified Icf (SICF) and adaptive SICF (AC-SICF) also solve the PAPR problem. Although the above three techniques can achieve better PAPR reduction, they have a common drawback that the selection of the optimal clipping threshold is a very difficult task, because different numbers of subcarriers and modulations can seriously affect the selection of the optimal clipping threshold.

Disclosure of Invention

The present invention is directed to an OFDM data processing method and apparatus to improve the above problem. In order to achieve the purpose, the technical scheme adopted by the invention is as follows:

in a first aspect, an embodiment of the present invention provides an OFDM data processing method, where the method includes obtaining an OFDM symbol having N subcarriers; obtaining a discrete-time baseband OFDM signal based on the OFDM symbol; obtaining an error vector magnitude based on the discrete-time baseband OFDM signal; establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude; generating an iterative update expression of the discrete-time baseband OFDM signal based on an alternating direction multiplier method and the optimization model; and continuously iterating and calculating the iteration updating expression until the preset iteration times are met, and outputting an optimized OFDM time domain signal.

In a second aspect, an embodiment of the present invention provides an OFDM data processing apparatus, which includes a symbol acquisition unit, a signal acquisition unit, an error vector magnitude acquisition unit, a creation unit, a generation unit, and an output unit. A symbol acquisition unit for acquiring an OFDM symbol having N subcarriers. A signal obtaining unit, configured to obtain a discrete-time baseband OFDM signal based on the OFDM symbol. An error vector magnitude obtaining unit, configured to obtain an error vector magnitude based on the discrete-time baseband OFDM signal. And the establishing unit is used for establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude. And the generating unit is used for generating an iteration updating expression of the discrete time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model. And the output unit is used for continuously carrying out iterative computation on the iterative update expression until the preset iteration times are met, and outputting an optimized OFDM time domain signal.

The method comprises the steps of obtaining an OFDM symbol with N subcarriers, obtaining a discrete time baseband OFDM signal based on the OFDM symbol, obtaining an error vector amplitude based on the discrete time baseband OFDM signal, establishing an error vector amplitude optimization model with infinite series constraint based on the OFDM symbol and the error vector amplitude, generating an iteration updating expression of the discrete time baseband OFDM signal based on an alternating direction multiplier method and the optimization model, continuously iterating and calculating the iteration updating expression until preset iteration times are met, and outputting an optimized OFDM time domain signal. The peak-to-average ratio and the in-band distortion are reduced by using the alternating direction multiplier method, and cutting and filtering operations are not required, and an optimal cutting threshold value is not required to be selected. Is more efficient.

Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the embodiments of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.

Fig. 1 is a block diagram of an electronic device applicable to an embodiment of the present invention;

fig. 2 is a flowchart of an OFDM data processing method according to an embodiment of the present invention;

fig. 3 is a schematic diagram illustrating a peak-to-average ratio comparison result in the OFDM data processing method according to an embodiment of the present invention;

fig. 4 is a schematic diagram illustrating a bit error rate comparison result in the OFDM data processing method according to an embodiment of the present invention;

fig. 5 is a block diagram of an OFDM data processing apparatus according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. 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.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.

Fig. 1 shows a block diagram of an electronic device 100 applicable to an embodiment of the present invention. As shown in fig. 1, electronic device 100 may include a memory 102, a memory controller 104, one or more processors 106 (only one shown in fig. 1), a peripherals interface 108, an input output module 110, an audio module 112, a display module 114, a radio frequency module 116, and an OFDM data processing apparatus.

The memory 102, the memory controller 104, the processor 106, the peripheral interface 108, the input/output module 110, the audio module 112, the display module 114, and the radio frequency module 116 are electrically connected directly or indirectly to realize data transmission or interaction. For example, electrical connections between these components may be made through one or more communication or signal buses. The OFDM data processing method includes at least one software functional module that can be stored in the memory 102 in the form of software or firmware (firmware), for example, a software functional module or a computer program included in the OFDM data processing apparatus, respectively.

The memory 102 may store various software programs and modules, such as program instructions/modules corresponding to the OFDM data processing method and apparatus provided in the embodiments of the present application. The processor 106 executes various functional applications and data processing by executing software programs and modules stored in the memory 102, that is, implements the OFDM data processing method in the embodiment of the present application.

The Memory 102 may include, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read Only Memory (PROM), Erasable Read Only Memory (EPROM), electrically Erasable Read Only Memory (EEPROM), and the like.

The processor 106 may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. Which may implement or perform the methods, steps, and logic blocks disclosed in the embodiments of the present application. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The peripherals interface 108 couples various input/output devices to the processor 106 and to the memory 102. In some embodiments, the peripheral interface 108, the processor 106, and the memory controller 104 may be implemented in a single chip. In other examples, they may be implemented separately from the individual chips.

The input-output module 110 is used for providing input data to a user to enable the user to interact with the electronic device 100. The input/output module 110 may be, but is not limited to, a mouse, a keyboard, and the like.

Audio module 112 provides an audio interface to a user that may include one or more microphones, one or more speakers, and audio circuitry.

The display module 114 provides an interactive interface (e.g., a user interface) between the electronic device 100 and a user or for displaying image data to a user reference. In this embodiment, the display module 114 may be a liquid crystal display or a touch display. In the case of a touch display, the display can be a capacitive touch screen or a resistive touch screen, which supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations from one or more locations on the touch display at the same time, and the sensed touch operations are sent to the processor 106 for calculation and processing.

The rf module 116 is used for receiving and transmitting electromagnetic waves, and implementing interconversion between the electromagnetic waves and electrical signals, so as to communicate with a communication network or other devices.

It will be appreciated that the configuration shown in FIG. 1 is merely illustrative and that electronic device 100 may include more or fewer components than shown in FIG. 1 or have a different configuration than shown in FIG. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.

In the embodiment of the invention, the electronic device 100 may be a user terminal or a server. The user terminal may be a pc (personal computer), a tablet computer, a mobile phone, a notebook computer, an intelligent television, a set-top box, a vehicle-mounted terminal, and other terminal devices.

Referring to fig. 2, an embodiment of the present invention provides an OFDM data processing method, which may include step S200, step S210, step S220, step S230, step S240, and step S250.

Step S200: an OFDM symbol having N subcarriers is obtained.

In the present embodiment, N is 256. The OFDM symbol may be 256 subcarriers and a QPSK Quadrature Phase Shift keying (Quadrature Phase Shift key) modulated OFDM symbol. The OFDM system comprising at least one OFDM symbol, e.g. 10⁴For simplicity of description, an OFDM symbol with N subcarriers is taken as an example.

Step S210: obtaining a discrete-time baseband OFDM signal based on the OFDM symbol.

Step S210 may include:

and performing IDFT modulation on the OFDM symbol to obtain a discrete-time baseband OFDM signal with an oversampling factor of J, wherein an IDFT matrix in the IDFT modulation process is determined by N and J, and the product of the OFDM symbol and the IDFT matrix is the discrete-time baseband OFDM signal.

In this embodiment, an OFDM symbol may be denoted as X ═ X₀，...，.X_N-1]^T. The discrete-time baseband OFDM signal may be denoted as x ═ x₀，...，x_JN-1]^TWhere x is FX, F is the IDFT matrix, and F is the JN × N matrix. The PAPR of a discrete-time baseband OFDM signal can be defined as

IDFT, Inverse Discrete Fourier Transform is the Inverse Discrete Fourier Transform.

Step S220: obtaining an error vector magnitude based on the discrete-time baseband OFDM signal.

Error Vector Magnitude (EVM) can be used to measure the in-band distortion of an OFDM signal, denoted as

Wherein

Representing a distorted data signal.

The conventional OICF method solves the EVM optimization problem under PAPR constraint through an SOCP method at present:

in the expression (1), H^KIs the filter coefficient to be optimized and X is the signal in the original frequency domain.

And

are the in-band and out-of-band signal components after the kth cut. Although the proposed SOCP method can achieve optimal PAPR reduction and BER, its computational complexity is O (N)³) So the SOCP method is obviously not suitable for practical application.

Further, order

The improved SICF and AC-SICF schemes solve the following EVM optimization problem by transformation:

s.t.d(^k+1)＝IFFT(D^k)

in expression (2), SICF and AC-SICF schemes with O (jnlog (jn)) complexity result in a significant reduction in computational complexity compared to oic f. However, the optimum limiting ratio must be carefully selected among the three techniques

However, in practical use, the optimum limit is selectedThe amplitude ratio is very difficult because many factors, such as the number of subcarriers, modulation mode, etc., are closely related to the optimal amplitude limit ratio. To overcome this limitation, the present embodiment proposes an OFDM data processing method in the present embodiment, considering EVM optimization different from the above three methods.

Step S230: and establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude.

To simplify the calculation, step S230 may include:

establishing an original optimization model:

deleting | X | non calculation in the original optimization model₂ ²Establishing an error vector magnitude optimization model with infinite series constraint:

wherein X is the OFDM symbol,

in order to optimize the time-domain signal vector,

for the error vector magnitude, μ is a penalty regularization parameter, F is an IDFT matrix, F is a JN × N matrix, and the (m, j) th term of the IDFT matrix F

An infinite series constraint characterizing the discrete-time baseband OFDM signal.

Since directly constraining PAPR will result in complex non-convex optimization, it is useful

Instead of PAPR constraints. Due to the fact that

It is a constant in the optimization process, i.e. a constant, which can be deleted in order to facilitate the handling of the problem. The EVM optimization problem becomes an equivalent problem, i.e.

Is equivalent to

Step S240: and generating an iterative updating expression of the discrete-time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model.

To obtain better PAPR reduction and Bit Error Rate (BER), an alternative Direction multiplier (ADMM) based processing is proposed

And (5) optimizing.

The Alternating Direction Multiplier Method (ADMM) is mainly used to solve an optimization problem of the form:

minimize f(x)+h(x)，

wherein f and h: r^m→ R { + ∞ } is a suitable convex function of two closes.

ADMM consists of the following iterations

xⁱ⁺¹＝prox_αf(zⁱ-uⁱ)，

zⁱ⁺¹＝prx_ah(ⁱ⁺¹+uⁱ)

uⁱ⁺¹＝uⁱ+xⁱ⁺¹-Zⁱ⁺¹

prox is a near-end operator of a function. Near-end operator prox for a function f with a parameter α_af：R^m→R^mIs defined as:

middle function

The direct calculation of the approximation operator of (a) is a very difficult task. Therefore, it is necessary to

An auxiliary variable y is introduced to simplify the calculation.

Further, step S240 may include:

introducing an auxiliary variable into the error vector magnitude optimization model to obtain an introduced and processed error vector magnitude optimization model:

and is

Order to

And h (y) | | | y | | non-woven phosphor_∞The augmented lagrangian function of the introduced and processed error vector magnitude optimization model is as follows:

wherein z is a dual variable, ρ is a predetermined parameter, and ρ > 0 (·)^HRepresents a conjugate transpose of a vector;

generating an iterative expression according to an iterative composition principle of an alternating direction multiplier method:

will be provided with

Replacing in said augmented Lagrangian function

And modifying the iterative expression

Generating an iterative update expression of the discrete-time baseband OFDM signal:

λ 1/ρ and

wherein, prox_βfAs a function of the parameter beta

Approximation operator of, prox_λhAn approximation operator for a function h (y) with a parameter λ.

When updating

And yⁱ⁺¹When it is necessary to calculate the function

And h (y) of two approximation operators. If function

Is solved as prox_βf(u) ═ 2 β X + u)/(1+2 β), the iterative update expression is:

λ 1/ρ and

step S250: and continuously iterating and calculating the iteration updating expression until the preset iteration times are met, and outputting an optimized OFDM time domain signal.

Based on the steps S200-S250, a simulation experiment of the algorithm is carried out, the software MATLAB is used for simulation, and the obtained graph verifies the theoretical analysis. The brief algorithm flow is as follows:

inputting original frequency domain signal X, parameter lambda, beta, initial solution

yⁱ，uⁱPresetting iteration times K;

for i 1, 2.. K, perform:

ending the circulation;

output of

In the OFDM data processing method provided in this embodiment, the main calculation cost is composed of the calculation of two approximation operators. Since F is an IDFT matrix, so

The computation of (c) corresponds to an FFT operation of complexity O (jnlog (jn)), and the complexity of the multiplication of coefficients and vectors is O (jn). To obtain

Then, firstly, the

The IFFT operation is performed and then the approximation operator of the function h (y) is estimated, with a complexity of o (jn). In addition, when updating

yⁱ⁺¹And uⁱ⁺¹The addition or subtraction of several phasors is negligible. Therefore, the computational complexity is O (JNLog (JN)). The computational complexity is lower than that of the existing method.

Further, in order to compare the effect of the PARA reduction, after step S250, the method may further include:

obtaining a first peak-to-average ratio of the OFDM time domain signal;

obtaining a second peak-to-average ratio, a third peak-to-average ratio and a fourth peak-to-average ratio which are respectively obtained by optimizing OFDM symbols by an FITRA method, a SICF method and an AC-SICF method;

and comparing the first peak-to-average ratio with the second peak-to-average ratio, the third peak-to-average ratio and the fourth peak-to-average ratio one by one to obtain a peak-to-average ratio comparison result.

Specifically, 10 is generated⁴An OFDM symbol with 256 sub-carriers and QPSK modulation, an oversampling factor of J-4, μ -15, β -0.5, γ -4, and a maximum number of iterations K-3, and performing steps S200-S250 to obtain 10⁴And the OFDM time domain signals respectively corresponding to the OFDM symbols. The PAPR of the OFDM data processing method provided by the ADMM, i.e., the OFDM data processing method provided by this embodiment, obtains PAPR reduction gains of about 0.95dB, 1.7dB, and 1.95dB, respectively, compared with the PAPR obtained by the fast recursive truncation algorithm (FITRA), the simplified recursive filtering (sic f), and the sic f (AC-sic f) algorithm with adaptive cut threshold, where Original OFDM signals are represented by Original signals, and the PAPR reduction gains are obtained by the ADMM, i.e., the OFDM data processing method provided by this embodiment, respectively, as shown in fig. 3.

Further, in order to compare the BER performance of the system, after step S250, the method further includes:

inputting the OFDM time domain signal into a preset solid-state power amplifier, and calculating a first bit error rate through an additive white Gaussian noise channel;

obtaining a second bit error rate, a third bit error rate and a fourth bit error rate which are respectively calculated on an additive white Gaussian noise channel after optimizing OFDM symbols by a FITRA method, a SICF method and an AC-SICF method; and comparing the first bit error rate with the second bit error rate, the third bit error rate and the fourth bit error rate one by one to obtain a bit error rate comparison result.

Wherein, the preset solid-state power amplifier is:

wherein s is₀And s_i＝|s_i|e^jθAre respectively the outputAnd an input signal. Two parameters a-0.4 and p-3 were selected in the simulation.

As shown in fig. 4, the bit error rate comparison result compares BER performances of different methods on an Additive White Gaussian Noise (AWGN) channel, and it can be found that the BER performance of the ADMM, that is, the OFDM data processing method provided by this embodiment, is better than that of the FITRA, SICF and AC-SICF algorithms.

The OFDM data processing method provided by the embodiment of the invention uses the alternative direction multiplier method to reduce the peak-to-average ratio, and does not need cutting and filtering operation and optimal cutting threshold selection. Is more efficient.

Referring to fig. 5, an example of the present invention provides an OFDM data processing apparatus 500, where the apparatus 500 includes a symbol obtaining unit 510, a signal obtaining unit 520, an error vector magnitude obtaining unit 530, a building unit 540, a generating unit 550, and an output unit 560.

A symbol obtaining unit 510 for obtaining an OFDM symbol with N subcarriers

The OFDM symbols are 256 subcarriers and QPSK modulated OFDM symbols.

A signal obtaining unit 520, configured to obtain a discrete-time baseband OFDM signal based on the OFDM symbol.

The signal obtaining unit 520 is configured to perform IDFT modulation on the OFDM symbol to obtain a discrete-time baseband OFDM signal with an oversampling factor of J, where an IDFT matrix in the IDFT modulation process is determined by N and J, and a product of the OFDM symbol and the IDFT matrix is the discrete-time baseband OFDM signal.

An error vector magnitude obtaining unit 530, configured to obtain an error vector magnitude based on the discrete-time baseband OFDM signal.

And the establishing unit 540 is configured to establish an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude.

A establishing unit 540, configured to: establishing an original optimization model:

deleting in the original optimization model

Establishing an error vector magnitude optimization model:

wherein X is the OFDM symbol,

in order to optimize the time-domain signal vector,

A generating unit 550, configured to generate an iterative update expression of the discrete-time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model.

A generating unit 550 configured to: introducing an auxiliary variable into the error vector magnitude optimization model to obtain an introduced and processed error vector magnitude optimization model:

and is

Order to

And h (y) | | | y | | non-woven phosphor_∞Introducing processed errorsThe augmented Lagrangian function of the vector magnitude optimization model is as follows:

z is a dual variable, ρ is a predetermined parameter, and ρ > 0 (·)^HRepresents a conjugate transpose of a vector; generating an iterative expression according to an iterative composition principle of an alternating direction multiplier method:

will be provided with

Replacing in said augmented Lagrangian function

And modifying the iterative expression

λ 1/ρ and

wherein, prox_βfAs a function of the parameter beta

If function

λ 1/ρ and

and an output unit 560, configured to perform continuous iterative computation on the iterative update expression until a preset iteration number is met, and output an optimized OFDM time domain signal.

The output unit 560 is further configured to: obtaining a first peak-to-average ratio of the OFDM time domain signal; obtaining a second peak-to-average ratio, a third peak-to-average ratio and a fourth peak-to-average ratio which are respectively obtained by optimizing OFDM symbols by an FITRA method, a SICF method and an AC-SICF method; and comparing the first peak-to-average ratio with the second peak-to-average ratio, the third peak-to-average ratio and the fourth peak-to-average ratio one by one to obtain a peak-to-average ratio comparison result.

The output unit 560 is further configured to: inputting the OFDM time domain signal into a preset solid-state power amplifier, and calculating a first bit error rate through an additive white Gaussian noise channel; obtaining a second bit error rate, a third bit error rate and a fourth bit error rate which are respectively calculated on an additive white Gaussian noise channel after optimizing OFDM symbols by a FITRA method, a SICF method and an AC-SICF method; and comparing the first bit error rate with the second bit error rate, the third bit error rate and the fourth bit error rate one by one to obtain a bit error rate comparison result.

The above units may be implemented by software codes, and in this case, the above units may be stored in the memory 102. The above units may also be implemented by hardware, for example, an integrated circuit chip.

The implementation principle and the resulting technical effect of the OFDM data processing apparatus 500 according to the embodiment of the present invention are the same as those of the foregoing method embodiment, and for the sake of brief description, the corresponding contents in the foregoing method embodiment may be referred to where no mention is made in the apparatus embodiment.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus implementation examples described above are merely illustrative, and the flowcharts and block diagrams in the figures, for example, illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the use of the phrase "comprising a. -. said" to define an element does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for OFDM data processing, the method comprising:

obtaining an OFDM symbol with N subcarriers;

obtaining a discrete-time baseband OFDM signal based on the OFDM symbol;

obtaining an error vector magnitude based on the discrete-time baseband OFDM signal;

establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude;

generating an iterative update expression of the discrete-time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model;

continuously iterating and calculating the iteration updating expression until the preset iteration times are met, and outputting an optimized OFDM time domain signal;

obtaining a discrete-time baseband OFDM signal based on the OFDM symbol, comprising:

performing IDFT modulation on the OFDM symbol to obtain a discrete-time baseband OFDM signal with an oversampling factor of J, wherein an IDFT matrix in the IDFT modulation process is determined by N and J, and the product of the OFDM symbol and the IDFT matrix is the discrete-time baseband OFDM signal;

establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude, wherein the error vector magnitude optimization model comprises the following steps:

establishing an original optimization model:

deleting | X | non calculation in the original optimization model₂ ²Establishing an error vector magnitude optimization model:

wherein X is the OFDM symbol,

in order to optimize the time-domain signal vector,

Characterizing a peak-to-average ratio constraint of the discrete-time baseband OFDM signal.

2. The method of claim 1, wherein generating an iteratively updated expression of the discrete-time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model comprises:

and is

Order to

wherein z is a dual variable, ρ is a predetermined parameter, and ρ is>0，(·)^HRepresents a conjugate transpose of a vector;

generating an iterative expression according to an iterative principle of an alternating direction multiplier method:

wherein u isⁱ＝(1/ρ)zⁱ；

Will be provided with

Replacing in said augmented Lagrangian function

And modifying the iterative expression

wherein λ is 1/ρ and

prox_βfas a function of the parameter beta

3. The method of claim 2, wherein if the function is

λ 1/ρ and

4. the method of claim 1, wherein after outputting the optimized OFDM time domain signal, the method further comprises:

obtaining a first peak-to-average ratio of the OFDM time domain signal;

5. The method of claim 1, wherein after outputting the optimized OFDM time domain signal, the method further comprises:

obtaining a second bit error rate, a third bit error rate and a fourth bit error rate which are respectively calculated on an additive white Gaussian noise channel after optimizing OFDM symbols by a FITRA method, a SICF method and an AC-SICF method;

and comparing the first bit error rate with the second bit error rate, the third bit error rate and the fourth bit error rate one by one to obtain a bit error rate comparison result.

6. The method according to any of claims 1-5, wherein the OFDM symbols are 256 subcarriers and QPSK modulated OFDM symbols.

7. An OFDM data processing apparatus, characterized in that the apparatus comprises:

a symbol acquisition unit for acquiring an OFDM symbol having N subcarriers;

a signal obtaining unit, configured to obtain a discrete-time baseband OFDM signal based on the OFDM symbol;

an error vector magnitude obtaining unit, configured to obtain an error vector magnitude based on the discrete-time baseband OFDM signal;

the establishing unit is used for establishing an error vector magnitude optimization model with infinite series constraint based on the OFDM symbol and the error vector magnitude;

the generating unit is used for generating an iteration updating expression of the discrete time baseband OFDM signal based on an alternating direction multiplier method and the error vector magnitude optimization model;

the output unit is used for continuously carrying out iterative computation on the iterative update expression until the preset iteration times are met, and outputting an optimized OFDM time domain signal;

the signal obtaining unit is configured to perform IDFT modulation on the OFDM symbol to obtain a discrete-time baseband OFDM signal with an oversampling factor of J, where an IDFT matrix in an IDFT modulation process is determined by N and J, and a product of the OFDM symbol and the IDFT matrix is the discrete-time baseband OFDM signal;

establishing an original optimization model:

wherein X is the OFDM symbol,

in order to optimize the time-domain signal vector,