CN110176977B - High-order QAM soft decision method based on AGC in OFDM data chain - Google Patents

High-order QAM soft decision method based on AGC in OFDM data chain Download PDF

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CN110176977B
CN110176977B CN201910417717.9A CN201910417717A CN110176977B CN 110176977 B CN110176977 B CN 110176977B CN 201910417717 A CN201910417717 A CN 201910417717A CN 110176977 B CN110176977 B CN 110176977B
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bit width
soft information
agc
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signal
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CN110176977A (en
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闫朝星
罗翔
王先朋
付林罡
李辉
李响
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Beijing Research Institute of Telemetry
Aerospace Long March Launch Vehicle Technology Co Ltd
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Aerospace Long March Launch Vehicle Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0054—Maximum-likelihood or sequential decoding, e.g. Viterbi, Fano, ZJ algorithms
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/04—TPC
    • H04W52/52—TPC using AGC [Automatic Gain Control] circuits or amplifiers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L27/00—Modulated-carrier systems
    • H04L27/32—Carrier systems characterised by combinations of two or more of the types covered by groups H04L27/02, H04L27/10, H04L27/18 or H04L27/26
    • H04L27/34—Amplitude- and phase-modulated carrier systems, e.g. quadrature-amplitude modulated carrier systems
    • H04L27/38—Demodulator circuits; Receiver circuits

Abstract

The invention discloses a high-order QAM soft decision method based on AGC in OFDM data chain, firstly estimating OFDM frame frequency domain pilot signal rp(k) Signal power P ofSAnd noise power PNAnd for the received service data signal rd(k) Performing automatic gain control processing to obtain zd(k) (ii) a Then z isd(k) And performing soft decision demapping to obtain corresponding soft information for subsequent decoding. The invention accurately estimates the signal power of the frequency domain signal through the pilot frequency carrier or the virtual subcarrier in the OFDM receiver, sets the target power value of the received signal AGC according to the signal power, calculates the quantized soft information of the received signal after the gain adjustment, and associates the quantization format of the soft information with the AGC target power value, thereby improving the accuracy of the soft information with lower calculation complexity.

Description

High-order QAM soft decision method based on AGC in OFDM data chain
Technical Field
The invention relates to a high-order QAM soft decision method based on AGC in an OFDM data chain, belonging to the technical field of digital wireless communication transmission.
Background
In an aircraft data link system, as the on-board mission load capacity increases, the ground-to-air data link needs to provide high-speed traffic data transmission. Meanwhile, the ground-air link has large multipath interference, and a communication system is required to have the capability of resisting frequency selective interference. Therefore, the aircraft data link usually uses Orthogonal Frequency Division Multiplexing (OFDM) technology, high-order Quadrature Amplitude Modulation (QAM) and high-efficiency channel error correction codes such as Turbo codes or LDPC codes to achieve high-speed transmission and anti-interference capability. However, in an OFDM data chain receiver, high-order QAM modulation requires accurate soft-decision computation likelihood information to ensure decoding performance.
The document "improved 16QAM soft decision demodulation algorithm [ J ] in OFDM system modern electronic technology, 2012,35(3): 119-. The document "algorithm for fast generation of QAM bit confidence soft decision metrics [ J ]. journal of electronics and informatics, 2009,31(4): 985-. The soft information extraction and frequency domain equalization technology research of signals in short wave number transmission is carried out by the west ampere electronic technology university 2014, and the square 16QAM signals and the non-square 16APSK signals are simplified. The document "Look-up table based low complexity LLR calculation for high-order amplitude phase shift signalling [ J ]. IEICE Transactions on Communications,2012, E95(B (9)): 2936-.
However, the above documents mostly analyze, simplify and improve the algorithm itself, and do not comprehensively consider the specific implementation technology in the actual receiver to optimize the demodulation and decoding performance.
Disclosure of Invention
The technical problem solved by the invention is as follows: the high-order QAM soft decision method based on AGC in the OFDM data chain is provided, soft information calculation and AGC are combined, and the accuracy of soft information is improved with low calculation complexity.
The technical solution of the invention is as follows:
the high-order QAM soft decision method based on AGC in the OFDM data chain comprises the following steps:
step one, estimating OFDM frame frequency domain pilot signal rp(k) Signal power P ofSAnd noise power PNAnd are combinedFor received service data signal rd(k) Performing automatic gain control processing to obtain zd(k)；
Step two, mixing zd(k) And performing soft decision demapping to obtain corresponding soft information for subsequent decoding.
In the first step, P is estimatedSThe method comprises the following steps:
using a pilot signal r according to the following formulap(k) Obtaining a signal power estimate PS：
Figure BDA0002064960720000021
NpIs a pilot signal rp(k) Length of (1), xp(k) Indicating a pilot signal transmitted by a transmitting end.
In the first step, noise power:
Figure BDA0002064960720000022
in the first step, when the number of virtual sub-carriers NuNot less than pilot signal rp(k) Length N ofpUsing the virtual subcarrier ru(k) Deriving a noise power estimate PN：
Figure BDA0002064960720000023
In the first step, when the number of virtual sub-carriers NuNot less than pilot signal rp(k) Length N ofpWhen the temperature of the water is higher than the set temperature,
Figure BDA0002064960720000024
wherein N isdAnd calculating the number of signals of the total power of the received signals.
In the first step, z is obtained by the following methodd(k)：
Format of quantization<Ld,Li,Lf>R ofd(k) Carrying out AGC gain adjustment to obtain a quantization format<Ld,Li,Lf>Z of (a)d(k)：
Figure BDA0002064960720000031
Wherein L isd＝Li+Lf+1 denotes signed data rd(k) Quantization bit width of LiRepresents an integer bit width, LfRepresents the decimal bit width; eta is a gain adjustment factor, eta is P0/PS，P0Is a target power value of AGC; target power value P0Corresponding to a virtual constellation point, the real part and imaginary part are set as
Figure BDA0002064960720000032
And is provided with
Figure BDA0002064960720000033
In the second step, when the signal sent by the sending end is 16QAM, for zd(k) Performing soft-decision demapping to obtain soft information corresponding to 4 bits b1, b2, b3, and b4, which is specifically implemented as follows:
using zd(k) Computational quantization format<Ld,Li,Lf>Soft information of (2):
Lb1(k)＝Re{zd(k)}
Figure BDA0002064960720000034
Lb3(k)＝Im{zd(k)}
Figure BDA0002064960720000035
wherein, 16QAM modulation constellation points are setThe real part and imaginary part coordinates are a and 3a, then
Figure BDA0002064960720000036
Representing the middle value of the constellation point, | | cn| | represents the rounding operation; l isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
To Lb1(k)、Lb2(k)、Lb3(k)、Lb4(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Nd＝Ni+Nf+1, quantization format of<Nd,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
In the second step, when the signal sent by the sending end is 64QAM, the z is correctedd(k) Performing soft-decision demapping to obtain soft information corresponding to 6 bits b1, b2, b3, b4, b5, and b6, wherein the specific implementation manner is as follows:
using zd(k) Computational quantization format<Ld,Li,Lf>Soft information of (2):
Lb1(k)＝Re{zd(k)}
Figure BDA0002064960720000041
Figure BDA0002064960720000042
Lb4(k)＝Im{zd(k)}
Figure BDA0002064960720000043
Figure BDA0002064960720000044
wherein L isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
To L is paired withb1(k)、Lb2(k)、Lb3(k)、Lb4(k)、Lb5(k)、Lb6(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Nd＝Ni+Nf+1, quantization format of<Nd,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
Compared with the prior art, the invention has the advantages that:
(1) the invention combines soft information calculation and AGC to improve the accuracy of soft information calculation, and the target power value P is0To the power of 2, the gain adjustment factor computation complexity can be reduced.
(2) In the high-order QAM soft decision method based on AGC in the OFDM data chain, an algorithm for calculating signal power estimation by using pilot frequency or virtual subcarrier signals in the AGC is not influenced by carrier synchronization of an OFDM receiver;
(3) the high-order QAM soft decision method based on AGC in the OFDM data chain is suitable for high-order QAM modulation, the likelihood information quantization format combines the characteristics of constellation points, and the method has the characteristics of low implementation complexity and low performance loss.
Drawings
FIG. 1 is a block diagram of a high-order QAM soft decision method based on AGC in an OFDM data chain according to the present invention;
fig. 2 is a schematic diagram of the present invention adopting 16QAM and 64QAM mapping schemes, wherein (a) is a 16QAM mapping scheme, and (b) is a 64QAM mapping scheme;
FIG. 3 shows AGC signal constellation points in an OFDM data chain based on the AGC high-order QAM soft decision method of the present invention;
FIG. 4 is a diagram illustrating the statistical distribution of LLR calculated by the AGC-based high-order QAM soft decision method in the OFDM data chain according to the present invention;
FIG. 5 shows the LDPC decoding performance of the AGC-based high-order QAM soft decision method in the OFDM data chain according to the present invention.
Detailed Description
The invention will be further explained with reference to the drawings.
The invention discloses a high-order QAM soft decision method based on AGC in an OFDM data chain, which mainly comprises the following steps:
step one, estimating OFDM frame frequency domain pilot signal rp(k) Signal power P ofSAnd noise power PNAnd for receiving service data signal rd(k) Performing Automatic Gain Control (AGC) processing to obtain zd(k)。
Frequency domain OFDM frame consists of length NpQPSK modulated pilot signal rp(k) And length NrM-QAM modulated traffic data signal rd(k) The components are usually 4QAM or high-order modulation 16QAM and 64 QAM. OFDM frame length of Ns＝Nu+Nr+Np，NuIs the number of virtual subcarriers.
First using a pilot signal rp(k) Obtaining a signal power estimate PS，
Figure BDA0002064960720000051
Noise power
Figure BDA0002064960720000052
Or when N isu≥NpTime-of-flight using virtual sub-carriers ru(k) Deriving a noise power estimate PN，
Figure BDA0002064960720000053
Figure BDA0002064960720000061
Where | represents solving for absolute value, xp(k) Indicating the pilot signal sent by the originator.
Then, a target power value P of AGC is set0And calculating a gain adjustment factor eta as P0/PSIn implementation, quantizing the format<Ld,Li,Lf>R ofd(k) Carrying out AGC gain adjustment to obtain quantization format<Ld,Li,Lf>Z of (a)d(k)：
Figure BDA0002064960720000062
Wherein L isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
Set target power value P0Corresponding to a virtual constellation point, the real part and imaginary part are set as
Figure BDA0002064960720000063
And is provided with
Figure BDA0002064960720000064
At this time, the factor is adjusted
Figure BDA0002064960720000065
Only P needs to be changed in the implementation processSThe integer bit and the decimal bit length.
Step (II) of adjusting the gain of the z obtained in the step (I)d(k) And performing soft decision demapping to obtain corresponding soft information.
When the signal transmitted by the transmitting end is 16QAM, for zd(k) Performing soft-decision demapping to obtain soft information corresponding to 4 bits b1, b2, b3, and b4, which is specifically implemented as follows:
using zd(k) Computational quantization format<Ld,Li,Lf>Soft information of (2):
Lb1(k)＝Re{zd(k)}
Figure BDA0002064960720000066
Lb3(k)＝Im{zd(k)}
Figure BDA0002064960720000067
wherein, the real part and imaginary part coordinates of the 16QAM modulation constellation point are set as a and 3a, then
Figure BDA0002064960720000068
Representing the intermediate value of the constellation point, | | | |, represents the rounding operation; l isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
To L is paired withb1(k)、Lb2(k)、Lb3(k)、Lb4(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Nd＝Ni+Nf+1, quantization format of<Nd,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
When the signal transmitted by the transmitting end is 64QAM, for zd(k) Performing soft-decision demapping to obtain soft information corresponding to 6 bits b1, b2, b3, b4, b5, and b6, wherein the specific implementation manner is as follows:
using zd(k) Computational quantization format<Ld,Li,Lf>The soft information of (2):
Lb1(k)＝Re{zd(k)}
Figure BDA0002064960720000071
Figure BDA0002064960720000072
Lb4(k)＝Im{zd(k)}
Figure BDA0002064960720000073
Figure BDA0002064960720000074
then, for Lb1(k)、Lb2(k)、Lb3(k)、Lb4(k)、Lb5(k)、Lb6(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Nd＝Ni+Nf+1, quantization format of<Nd,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
A typical desirable quantization format is <6,2,3 >.
Fig. 1 is a block diagram of a high-order QAM soft decision method based on AGC in an OFDM data chain, which extracts pilot and service data from an OFDM signal after frequency domain synchronization and equalization, performs signal power estimation and AGC gain control, calculates soft information (soft decision likelihood information), and finally sends the soft information to an LDPC decoder.
Fig. 2 is a schematic diagram of a 16QAM mapping scheme adopted in the frequency domain.
The performance simulation results of the AGC-based high-order QAM soft decision method in the OFDM data chain of the present invention are analyzed in the following by an embodiment.
FIG. 3 shows a quantization format of<9,3,5>The time service data is at a constellation point under 20dB, and the set target signal power is P0＝22×5+1＝2048。
Figure BDA0002064960720000081
Fig. 4 shows the statistical distribution of OFDM signals with a snr of 7.5dB for a frame when the quantization format of soft information is <6,2,3>, and it can be seen that the signal amplitude is substantially less than or equal to 20.
Fig. 5 shows the performance of the LDPC code decoded by the LDPC code having the code length 4000 and the coding efficiency 1/2, and it is found from the simulation result analysis that the BER is 3 × 10-5The theoretical simulation is 7.2dB, and the method of the invention is about 7.5dB, so the performance of the soft decision method after quantization is about 0.3dB less than the simulation performance loss.
The invention accurately estimates the signal power of the frequency domain signal through the pilot frequency carrier or the virtual subcarrier in the OFDM receiver, sets the target power value of the AGC of the received signal according to the signal power, then calculates the quantized soft information (likelihood information) of the received signal after the gain adjustment, and associates the quantization format of the soft information with the target power value of the AGC, thereby improving the accuracy of the soft information with lower calculation complexity.
The present invention has not been described in detail in part as is known in the art.

Claims (9)

  1. A high-order QAM soft decision method based on AGC in OFDM data chain is characterized by comprising the following steps:
    step one, estimating OFDM frame frequency domain pilot signal rp(k) Signal power P ofSAnd noise power PNAnd for the received service data signal rd(k) Performing automatic gain control processing to obtain zd(k)；
    Z is obtained by the following methodd(k)：
    Format of quantization<Ld,Li,Lf>R ofd(k) Carrying out AGC gain adjustment to obtain quantization format<Ld,Li,Lf>Z of (a)d(k)：
    Figure FDA0003576382890000011
    Wherein L isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfRepresents the decimal bit width; eta isGain adjustment factor, η ═ P0/PS，P0Is a target power value of AGC; target power value P0Corresponding to a virtual constellation point, the real part and imaginary part are set as
    Figure FDA0003576382890000015
    And is provided with
    Figure FDA0003576382890000012
    Step two, mixing zd(k) And performing soft decision demapping to obtain corresponding soft information for subsequent decoding.
  2. 2. The method of claim 1, wherein the method comprises: in the first step, P is estimatedSThe method comprises the following steps:
    using a pilot signal r according to the following formulap(k) Obtaining a signal power estimate PS：
    Figure FDA0003576382890000013
    NpIs a pilot signal rp(k) Length of (1), xp(k) Indicating a pilot signal transmitted by a transmitting end.
  3. 3. The method of claim 2, wherein the method comprises: in the first step, noise power:
    Figure FDA0003576382890000014
    wherein N isdThe number of signals for calculating the total power of the received signals.
  4. 4. The method of claim 1 for high-order QAM soft decision in an OFDM data chain based on AGCThe method is characterized in that: in the first step, when the number of virtual sub-carriers NuNot less than pilot signal rp(k) Length N ofpUsing virtual sub-carriers ru(k) Deriving a noise power estimate PN：
    Figure FDA0003576382890000021
  5. 5. The method of claim 4, wherein the method for high-order QAM soft decision based on AGC in OFDM data chain comprises: in the first step, when the number of virtual sub-carriers NuNot less than pilot signal rp(k) Length N ofpWhen the temperature of the water is higher than the set temperature,
    Figure FDA0003576382890000022
    wherein N isdThe number of signals for calculating the total power of the received signals.
  6. 6. The method of claim 1, wherein the method comprises: in the second step, when the signal sent by the sending end is 16QAM, for zd(k) Performing soft-decision demapping to obtain soft information corresponding to 4 bits b1, b2, b3, and b4, which is specifically implemented as follows:
    using zd(k) Computational quantization format<Ld,Li,Lf>Soft information of (2):
    Lb1(k)＝Re{zd(k)}
    Figure FDA0003576382890000023
    Lb3(k)＝Im{zd(k)}
    Figure FDA0003576382890000024
    wherein, the real part and imaginary part coordinates of the 16QAM modulation constellation point are set as a and 3a, then
    Figure FDA0003576382890000025
    Representing the intermediate value of the constellation point, | | | |, represents the rounding operation; l isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
  7. 7. The method of claim 6, wherein the method for high-order QAM soft decision based on AGC in OFDM data chain comprises: to Lb1(k)、Lb2(k)、Lb3(k)、Lb4(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Md＝Ni+Nf+1, quantization format of<Md,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
  8. 8. The method of claim 1, wherein the method comprises: in the second step, when the signal sent by the sending end is 64QAM, the z is adjustedd(k) Performing soft-decision demapping to obtain soft information corresponding to 6 bits b1, b2, b3, b4, b5, and b6, wherein the specific implementation manner is as follows:
    using zd(k) Computational quantization format<Ld,Li,Lf>Soft information of (2):
    Lb1(k)＝Re{zd(k)}
    Figure FDA0003576382890000031
    Figure FDA0003576382890000032
    Lb4(k)＝Im{zd(k)}
    Figure FDA0003576382890000033
    Figure FDA0003576382890000034
    wherein L isd＝Li+Lf+1 denotes signed data rd(k) Is quantized bit width, LiRepresents an integer bit width, LfIndicating a small bit width.
  9. 9. The method of claim 8, wherein the method for high-order QAM soft decision based on AGC in OFDM data chain comprises: to Lb1(k)、Lb2(k)、Lb3(k)、Lb4(k)、Lb5(k)、Lb6(k) The bit truncation obtains soft information for decoding, and the bit width of the soft information is Md＝Ni+Nf+1, quantization format of<Md,Ni,Nf>，NiRepresenting the bit width, N, of integer bits of soft informationfIndicating the soft information decimal place bit width.
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