CN107666457B - Adaptive design method for OFDM/OQAM system waveform - Google Patents

Adaptive design method for OFDM/OQAM system waveform Download PDF

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CN107666457B
CN107666457B CN201711052349.XA CN201711052349A CN107666457B CN 107666457 B CN107666457 B CN 107666457B CN 201711052349 A CN201711052349 A CN 201711052349A CN 107666457 B CN107666457 B CN 107666457B
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CN107666457A (en
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李燕龙
汪星月
宋志群
仇洪冰
王波
李环宇
杨超
刘丽哲
姜晓斐
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Guilin University of Electronic Technology
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2602—Signal structure
    • H04L27/261—Details of reference signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2626—Arrangements specific to the transmitter only
    • H04L27/2627—Modulators
    • H04L27/264—Pulse-shaped multi-carrier, i.e. not using rectangular window
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/26—Systems using multi-frequency codes
    • H04L27/2601—Multicarrier modulation systems
    • H04L27/2697—Multicarrier modulation systems in combination with other modulation techniques
    • H04L27/2698—Multicarrier modulation systems in combination with other modulation techniques double density OFDM/OQAM system, e.g. OFDM/OQAM-IOTA system

Abstract

The invention discloses a waveform self-adaptive design method of an OFDM/OQAM system, which comprises the steps of firstly, establishing the relationship between waveform time-frequency domain intervals and the maximum multipath time delay and the maximum Doppler frequency shift of a channel by introducing a waveform matching coefficient β and utilizing a waveform matching criterion, then calculating and optimizing pulse forming filter parameters by combining a signal-to-interference ratio (SIR) optimization function, generating a filter parameter loading table, and then sending an ACK feedback frame to a sending end by a receiving end of the system for the filter parameters to be fed back to the sending end, thereby adjusting the filter parameters to realize waveform self-adaptation.

Description

Adaptive design method for OFDM/OQAM system waveform
Technical Field
The invention relates to the technical field of communication, in particular to a waveform self-adaptive design method of an OFDM/OQAM system.
Background
In the ground-air unmanned communication system and the adjacent space communication system, while the system faces rich multipath components, the system is also influenced by frequency dispersion fading caused by channel Doppler spread. As one of the alternative modulation schemes of the 5G physical layer, an orthogonal frequency division multiplexing (OFDM/OQAM) technology based on interleaved orthogonal modulation enables a system to have good ISI and ICI resistance under a CP-free condition by introducing a prototype pulse filter with good time-frequency localization characteristics.
The most commonly used prototype pulse filter at present is an Isotropic Orthogonal Transform (IOTA), which is not suitable for the fast fading characteristics of the WSSUS (wide sense stationary uncorrelated scattering) channel in the time-frequency domain, such as air-to-air communication (air-to-ground) because it does not have the time and frequency focus adjustable characteristics.
In the prior art, two channel models of WSSUS characteristics are discussed based on a signal-to-interference ratio (signal-to-interference ratio) expression Channel Scattering Function (CSF) in a WSSUS channel OFDM system: the time-frequency double attenuation channel with the uniform time delay power spectrum and the uniform Doppler power spectrum and the time-frequency double attenuation channel with the exponential type time delay power spectrum and the U-shaped Doppler power spectrum simplify the expression of the signal-to-interference ratio aiming at the scattering functions of the two models. The scattering function provides basis for channel model classification of waveform adaptive design, but the waveform adaptive matching criterion given by the scattering function in the OFDM system based on the gaussian function has limitation on the OFDM/OQAM system based on the EGF filter.
Therefore, in combination with a ground-air channel with characteristics of exponential delay power spectrum and U-shaped Doppler power spectrum, a method for waveform adaptive design of an OFDM/OQAM system for ground-air communication is needed to optimize system performance.
Disclosure of Invention
The invention aims to solve the problems that an IOTA filter of an OFDM/OQAM system does not have time and frequency focusing adjustable characteristics and cannot adapt to a wireless fading channel in real time in a ground-air unmanned aerial vehicle communication system and an adjacent space communication system, and provides a waveform self-adaptive design method of the OFDM/OQAM system.
In order to solve the problems, the invention is realized by the following technical scheme:
an adaptive design method for OFDM/OQAM system waveform comprises the following steps:
step 1, an information source of a system sending end generates a binary random information sequence;
step 2, the system sending end modulates the binary random information sequence to form complex data;
step 3, the system sending end inserts pilot frequency and lead code in the complex data formed by modulation to form data to be transmitted;
step 4, the system sending end adjusts a sending filter bank according to the initial filter parameters, and filters the data to be transmitted by utilizing the sending filter bank;
step 5, the system sending end sends the filtered data to the system receiving end through a channel;
step 6, the system receiving end carries out channel estimation on the received data to obtain the maximum multipath time delay tau under the channel conditionmaxAnd a maximum Doppler shift vmax；
Step 7, the system receiving end adjusts a receiving filter bank according to the initial filter parameters, and receives and filters the data after signal estimation by using the receiving filter bank;
step 8, demodulating the filtered data by the system receiving end and then restoring the data;
step 9, the system receiving end obtains the maximum multipath time delay tau of the current channel according to the step 6maxAnd a maximum Doppler shift vmaxAnd obtaining the optimal filter parameter under the current channel by utilizing a waveform self-adaptive algorithm based on signal-to-interference ratio (SIR) optimization, and adjusting a sending filter bank and a receiving filter bank by utilizing the optimal filter parameter.
In the step 2, the data to be transmitted is modulated by adopting quadrature QAM mapping.
In step 3, the preamble includes a synchronization code and an ACK feedback codeword.
In the above step, the parameters of the reception filter are consistent with the parameters of the transmission filter.
In step 9, the waveform adaptive algorithm based on SIR optimization is as follows:
step 9.1, obtaining the maximum multipath time delay tau of the current channel according to the step 6maxAnd a maximum Doppler shift vmaxAnd spacing v of sub-carriers on a frequency domain by using a waveform self-adaptive matching criterion and a time-frequency relation of an OFDM/OQAM system0And adjacent in time domainTime offset tau of OQAM real-valued symbol0Conversion to a function on waveform matching coefficients β:
Figure BDA0001450450800000021
step 9.2, the sub-carrier wave interval v on the frequency domain is divided0And time offset tau of adjacent OQAM real-valued symbols in time domain0Substituted into the SIR calculation formula, where the SIR is converted into a binary expression with respect to the waveform matching coefficient β and the filter spreading factor α;
and 9.3, obtaining a waveform matching coefficient β and a filter spreading factor α under the current channel by maximizing the signal-to-interference ratio (SIR), wherein the filter spreading factor α is the optimal filter parameter under the current channel.
Compared with the prior art, the method has better performance improvement than a class-EGF function by introducing the waveform matching coefficient adapting to the WSSUS channel model, and is more suitable for the WSSUS channel model similar to a ground-air channel, thereby realizing the waveform adaptation of the OFDM/OQAM system for ground-air communication.
Drawings
FIG. 1 is a schematic block diagram of a waveform adaptive design method of an OFDM/OQAM system.
FIG. 2 is a simulation result of signal-to-interference ratio in four states of ground-to-air channels; (a) parkking (stop); (b) taxi; (c) is En-Route (in flight); (d) is Arrival.
Fig. 3 is an OFDM/OQAM system performance curve under 4QAM baseband modulation of a ground-space channel with 1024 subcarriers and 10 symbols.
Fig. 4 is a performance curve of the OFDM/OQAM system under 16QAM baseband modulation for the ground-space channel with 1024 subcarriers and 10 symbols.
Fig. 5 is a diagram of system error performance under different dopplers under 16QAM baseband modulation in the flight state of the ground-air channel.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings in combination with specific examples.
As shown in fig. 1, in the present embodiment, a waveform adaptive design method for an OFDM/OQAM system is provided, where the channel environment is a ground-space channel model, and the system employs filters (such as EGF and IOTA) having good localization characteristics and good energy focusing characteristics in the time-frequency domain. The system and the channel of the embodiment have the following setting parameters:
TABLE 1 System parameter settings Table
Figure BDA0001450450800000031
TABLE 2 channel parameters
Figure BDA0001450450800000032
The following explains concrete steps of a waveform adaptive design method under an OFDM/OQAM system in the embodiment:
step 1: and generation of a transmitting end source.
1024 rows of 10 columns of frequency domain source data are generated, each column being a symbol. Data on the nth subcarrier of the mth symbol is denoted as am,n，(m∈[1，10]，n∈[1，1024]And m and n are positive integers).
Step 2: and carrying out quadrature QAM mapping on the transmitting end.
And (3) carrying Out Quadrature Amplitude Modulation (OQAM) mapping on the binary source data generated in the step (1), and mapping the binary source data into complex data.
And step 3: the transmitting end inserts a pilot and a preamble.
The pilot frequency is channel estimation code word used for channel estimation and equalization, and the OFDM/OQAM system channel estimation adopts IAM-C comb pilot frequency. And inserting the processed data symbols into an IAM-C pilot structure for channel estimation, that is, inserting three columns of pilots into the front end of the data, setting the first column and the third column to be all zero, and designing the second column to be {1, j, -1, -j,1, j, -1, -j. Then, the block pilots are periodically inserted into the transmission data by being inserted every five columns by one column.
In addition, preamble codes, i.e., 50-bit synchronization code (SYNC) and 4-bit ack-EGF feedback code words, are inserted before the data symbols. A synchronization code (SYNC) is used to wake up the receiving device to synchronize it with the received signal. And the ACK-EGF feedback code word is used for returning the information of the receiving end to the transmitting end.
And 4, step 4: and filtering at a sending end.
At the beginning of the initial operation of the system, the sending end of the system adjusts the sending filter bank according to the initial filter parameters, and the sending filter bank is used for filtering the data to be transmitted. Wherein, the ACK-EGF is initially defaulted to 0000, which is the IOTA filter.
In the operation process of the system, the system sending end carries the feedback optimal filter parameter self-adaptive adjustment filter according to the feedback information of the system receiving end ACK frame and the ACK-EGF in the data frame sent by the system sending end.
And 5: through the channel.
And the system sending end sends the filtered data to the system receiving end through a channel.
Step 6: and estimating a channel of a receiving end.
The channel estimation code word, i.e. the pilot frequency, is used for channel estimation and equalization, and the channel estimation of the OFDM/OQAM system adopts IAM-C comb pilot frequency. And 3, according to the pilot frequency structure designed in the step 3, the transmitting tower on the ground transmits the data frame to the receiving end of the system according to the instruction. The receiving end of the system carries out channel estimation on the received data to obtain the maximum multipath time delay tau under the channel conditionmaxAnd a maximum Doppler shift vmax. And then the system receiving end sends an ACK-EGF frame (acknowledgement-EGF) to the system sending end to tell the system sending end the channel estimation information of the aircraft at the moment, and the system sending end adaptively selects the filter from the filter parameter loading table according to the feedback information.
And 7: and filtering at a receiving end.
At the beginning of the initial operation of the system, the receiving end of the system adjusts the receiving filter bank according to the initial filter parameters, and receives and filters the data after signal estimation by using the receiving filter bank.
And in the running process of the system, the system receiving end adaptively adjusts the filter according to the calculated optimal filter parameter.
And 8: and the receiving end demodulates.
And demodulating the filtered data and then restoring the data.
And step 9: and self-adaptive calculation of the waveform of the receiving end.
And calculating filter parameters of different states of the ground-space channel through a waveform adaptive matching criterion and a waveform adaptive algorithm based on signal-to-interference ratio (SIR) optimization, and generating the filter parameters under a ground-space channel model.
The waveform self-adaptive algorithm based on the signal-to-interference ratio SIR optimization is as follows:
step 9.1, obtaining the maximum multipath time delay tau of the current channel according to the step 6maxAnd a maximum Doppler shift vmaxAnd spacing v of sub-carriers on a frequency domain by using a waveform self-adaptive matching criterion and a time-frequency relation of an OFDM/OQAM system0And time offset tau of adjacent OQAM real-valued symbols in time domain0Conversion to a function on waveform matching coefficients β:
Figure BDA0001450450800000051
step 9.2, the sub-carrier wave interval v on the frequency domain is divided0And time offset tau of adjacent OQAM real-valued symbols in time domain0Substituted into the SIR calculation formula, where the SIR is converted into a binary expression with respect to the waveform matching coefficient β and the filter spreading factor α;
and 9.3, obtaining a waveform matching coefficient β and a filter spreading factor α under the current channel by maximizing the signal-to-interference ratio (SIR), wherein the filter spreading factor α is the optimal filter parameter under the current channel.
The principle of the waveform self-adaptive algorithm based on the signal-to-interference ratio SIR optimization is as follows:
firstly, a model 2 of a WSSUS channel, a time-frequency double attenuation channel with an exponential delay power spectrum and a U-shaped Doppler power spectrum, a scattering function are adopted:
Figure BDA0001450450800000052
wherein, taumaxRepresenting the maximum multipath delay, u, of the channelmaxIndicating the maximum doppler shift.
The invention combines a ground-space channel model to use the model 2 in the OFDM/OQAM system waveform self-adaptive algorithm, introduces a waveform matching coefficient β, and is used for determining the matching relation between an EGF function and channel characteristics.
Figure BDA0001450450800000053
Tau can be obtained by channel estimationmaxAnd upsilonmaxTime-frequency interval tau of waveform0And upsilon0Can be expressed as β, taumaxAnd upsilonmaxThe relational expression (c) of (c).
WtAnd WfDescribing the dispersion of the filter energy along the time axis and the frequency axis, respectively, the Heisenberg parameter satisfies the inequality
Figure BDA0001450450800000061
The larger the Heisenberg parameter, the more concentrated the energy and the better the TFL characteristic, otherwise the larger the energy spread range, the worse the frequency energy focusing (TFL) characteristic.
The time-frequency relation of the OFDM/OQAM system is as follows:
Figure BDA0001450450800000062
wherein v is0And τ0Respectively representing the subcarrier spacing in the frequency domain and the time offset of adjacent OQAM real-valued symbols in the time domain,
Figure BDA0001450450800000063
t is the OFDM symbol period.
The maximum multipath time delay tau of different channel states of the ground-space channelmaxMaximum doppler shift vmaxAnd the matching coefficient β as follows.
Figure BDA0001450450800000064
As can be seen from the above-mentioned relation,
Figure BDA0001450450800000065
in addition, the signal to interference ratio expression is as follows:
Figure BDA0001450450800000066
wherein S isH(τ, upsilon) is the channel scattering function, Ag(α)(τ, v) is the blurring function value of the EGF filter; generally, in the OFDM/OQAM system, due to the application of the EGF filter with better time-frequency focusing performance, the ISI and ICI interference of the desired symbol generally come from adjacent symbols, i.e., (m, n) (± 1,0), (0, ± 1).
In summary, the signal-to-interference ratio can be expressed as:
Figure BDA0001450450800000067
wherein the content of the first and second substances,
Figure BDA0001450450800000071
wherein g (t) represents an EGF filter.
Taken together, the SIR is a binary expression for the waveform matching coefficient β and the filter spreading factor α, i.e., SIR (β)max(β) corresponding (β)opt,αopt) And obtaining the optimized filter suitable for the current channel model.
The results of the signal-to-interference ratio simulation in four states of the ground-to-air channel are shown in fig. 2. By calculating SIRmax(β) corresponding (β)opt,αopt) The optimized filter suitable for the current channel model can be obtained, as shown by the vertex coordinates in the small square boxes in the figure, ZRepresenting SIR, X representing β, and Y representing α, optimal waveform matching coefficients and filter spreading factor for the case of maximum SIR can be obtained (β)opt,αopt) And adjusting the transmit filter bank and the receive filter bank using the optimal filter parameters. The results are given in the following table:
table 3 EGF filter parameter loading table
Figure BDA0001450450800000072
The EGF filter used in this embodiment is introduced as follows:
the Gaussian function has good time-frequency focusing characteristics, but all factors of the Gaussian function are positive numbers, so that the orthogonality condition is not met. The scholars propose that the Gaussian Function is processed by using an orthogonal transformation mode to obtain an Extended Gaussian Function (EGF), and an EGF Function expression is as follows:
Figure BDA0001450450800000073
wherein
Figure BDA0001450450800000074
Figure BDA0001450450800000075
Are real coefficients. gαIs a Gaussian function and has the following expression:
Figure BDA0001450450800000076
the value of the EGF function is constrained by three variables, namely α, v0And τ0。
For the IOTA function, α ═ 1,
Figure BDA0001450450800000081
the isotropic nature of the function gives it equivalent attenuation characteristics in the time and frequency domains.
The implementation utilizes the Bit Error Rate (BER) index to compare the anti-interference performance of the IOTA filter and the waveform self-adaptive EGF filter of the air-ground communication OFDM/OQAM system, and simultaneously carries out comparative analysis on the realizability of the engineering.
(1) And comparing error code performance.
And respectively obtaining an optimized expansion factor and an optimized channel matching coefficient from four states under a ground-air channel based on a signal-to-interference ratio (SIR) waveform self-adaptive algorithm to obtain an optimized EGF filter. Aiming at the effectiveness of the algorithm, the invention provides an OFDM/OQAM system error performance curve under 4QAM and 16QAM baseband modulation as shown in figure 3 and figure 4. It can be seen that:
A. in a 4QAM ground-to-air channel OFDM/OQAM system, the error rate of an optimized EGF filter has about 3.7dB gain compared with an IOTA filter in a field stop state (when the signal-to-noise ratio is set to be 9 dB), about 3.5dB gain in a slide state (when the signal-to-noise ratio is set to be 12 dB), about 1.7dB gain in an arrival state (when the signal-to-noise ratio is set to be 12 dB) and about 1.0dB gain in the slide state (when the signal-to-noise ratio is set to be 12 dB);
B. in the 16QAM ground-to-air channel OFDM/OQAM system, when the signal-to-noise ratio is set to be 30dB, the error rate of the optimized EGF filter in a field stop state has about 23.8dB gain compared with the IOTA filter, the gain in a sliding state is about 13.0dB gain, the gain in an arrival state is about 3.2dB gain, and the gain in a sliding state is about 2.1dB gain, so that the optimized EGF filter in the system performance has good improvement in the system performance compared with the IOTA filter.
(2) The design method has tolerance to the Doppler effect of the ground-air channel.
In this embodiment, in the ground-air unmanned aerial vehicle communication system, while the system faces rich multipath components, the system is also affected by frequency dispersion fading caused by channel doppler spread. The Doppler compensation operation is also needed for the problem of serious Doppler influence in the ground-air communication. The OFDM/OQAM system of the present embodiment has a certain tolerance to doppler spread based on the adaptive design of the waveform optimized by the signal-to-interference ratio, and as can be seen from fig. 5, when the SNR is 30dB, the effect of filter optimization is effective in the range where the doppler is lower than 700 Hz.
The method mainly comprises a waveform self-adaptive parameter generating module and a waveform self-adaptive feedback module, wherein the waveform self-adaptive parameter generating module introduces a waveform matching coefficient β, establishes the relationship between waveform time-frequency domain intervals and the maximum multipath time delay and the maximum Doppler frequency shift of a channel through a waveform matching criterion, and calculates and optimizes pulse forming filter parameters by combining a signal-to-interference ratio (SIR) optimization function to generate a filter parameter loading table.
It should be noted that, although the above-mentioned embodiments of the present invention are illustrative, the present invention is not limited thereto, and thus the present invention is not limited to the above-mentioned embodiments. Other embodiments, which can be made by those skilled in the art in light of the teachings of the present invention, are considered to be within the scope of the present invention without departing from its principles.

Claims (4)

1. An OFDM/OQAM system waveform self-adaptive design method is characterized by comprising the following steps:
step 1, an information source of a system sending end generates a binary random information sequence;
step 2, the system sending end modulates the binary random information sequence to form complex data;
step 3, the system sending end inserts pilot frequency and lead code in the complex data formed by modulation to form data to be transmitted;
step 4, the system sending end adjusts a sending filter bank according to the initial filter parameters, and filters the data to be transmitted by utilizing the sending filter bank;
step 5, the system sending end sends the filtered data to the system receiving end through a channel;
step 6, the system receiving end carries out channel estimation on the received data to obtain the maximum multipath time delay tau under the channel conditionmaxAnd a maximum Doppler shift vmax；
Step 7, the system receiving end adjusts a receiving filter bank according to the initial filter parameters, and receives and filters the data after signal estimation by using the receiving filter bank;
step 8, demodulating the filtered data by the system receiving end and then restoring the data;
step 9, the system receiving end obtains the maximum multipath time delay tau of the current channel according to the step 6maxAnd a maximum Doppler shift vmaxObtaining the optimal filter parameter under the current channel by utilizing a waveform self-adaptive algorithm based on signal to interference ratio (SIR) optimization, and adjusting a sending filter bank and a receiving filter bank by utilizing the optimal filter parameter; the waveform self-adaptive algorithm based on the signal-to-interference ratio SIR optimization is as follows:
step 9.1, obtaining the maximum multipath time delay tau of the current channel according to the step 6maxAnd a maximum Doppler shift vmaxAnd spacing v of sub-carriers on a frequency domain by using a waveform self-adaptive matching criterion and a time-frequency relation of an OFDM/OQAM system0And time offset tau of adjacent OQAM real-valued symbols in time domain0Conversion to a function on waveform matching coefficients β:
Figure FDA0002359302870000011
step 9.2, the sub-carrier wave interval v on the frequency domain is divided0And time offset tau of adjacent OQAM real-valued symbols in time domain0Substituted into the SIR calculation formula, where the SIR is converted into a binary expression with respect to the waveform matching coefficient β and the filter spreading factor α;
and 9.3, obtaining a waveform matching coefficient β and a filter spreading factor α under the current channel by maximizing the signal-to-interference ratio (SIR), wherein the filter spreading factor α is the optimal filter parameter under the current channel.
2. The adaptive design method for OFDM/OQAM system waveform of claim 1, wherein in step 2, the data to be transmitted is modulated by quadrature QAM mapping.
3. The adaptive design method for OFDM/OQAM system waveform of claim 1, wherein in step 3, the preamble comprises a synchronization code and an ACK feedback code.
4. The adaptive design method for OFDM/OQAM system waveform of claim 1, wherein the parameters of the receiving filter are consistent with the parameters of the transmitting filter.
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