CN110830398A - Frequency domain average channel estimation method in symbol applied in optical fiber DMT system - Google Patents

Frequency domain average channel estimation method in symbol applied in optical fiber DMT system Download PDF

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CN110830398A
CN110830398A CN201911106031.4A CN201911106031A CN110830398A CN 110830398 A CN110830398 A CN 110830398A CN 201911106031 A CN201911106031 A CN 201911106031A CN 110830398 A CN110830398 A CN 110830398A
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陈明
张龙
刘刚
周慧
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Hunan Normal University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0224—Channel estimation using sounding signals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04B10/00—Transmission systems employing electromagnetic waves other than radio-waves, e.g. infrared, visible or ultraviolet light, or employing corpuscular radiation, e.g. quantum communication
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/0204—Channel estimation of multiple channels
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/022—Channel estimation of frequency response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/0202—Channel estimation
    • H04L25/024—Channel estimation channel estimation algorithms
    • H04L25/025—Channel estimation channel estimation algorithms using least-mean-square [LMS] method

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Abstract

The invention discloses a method for estimating an average channel in a frequency domain in a symbol, which is applied to a fiber DMT system.A small amount of TS is adopted to obtain initial channel estimation on each data subcarrier based on an LS channel estimation method; then, the obtained estimation information is subjected to average processing, so that the noise interference of the system is suppressed, and the accuracy of channel estimation is improved; and finally, performing improved ISFA channel estimation processing on the averaged estimation information, and when channel estimation on the edge data subcarrier is calculated, reducing the size of a frequency domain average window and ensuring the symmetry of the frequency domain average window to realize accurate estimation.

Description

Frequency domain average channel estimation method in symbol applied in optical fiber DMT system
Technical Field
The invention relates to the field of optical fiber communication, in particular to an intra-symbol frequency domain average channel estimation method applied to an optical fiber DMT system.
Background
Improving data transmission rate and transmission distance has been a research hotspot of optical fiber communication technology. The OFDM technology has a high spectrum utilization rate and an excellent multi-path effect resistance, and has been widely applied to conventional wired and wireless communication systems, such as ADSL and 4G communication systems. In recent years, the OFDM technology is applied to an optical fiber communication system to improve the system spectrum efficiency and resist the optical fiber dispersion, so as to realize large-capacity and long-distance data transmission, and has received great attention from both academic and industrial fields. The optical fiber DMT technology is a special optical fiber OFDM technology, digital or analog up/down conversion is not needed for generation and demodulation of baseband DMT signals, the system structure is simple, and the implementation complexity is low, so that the method is very suitable for application scenes sensitive to cost, such as optical interconnection of a data center and an optical fiber access network.
In fiber DMT systems, channel estimation is a critical Digital Signal Processing (DSP) technique, and its estimation accuracy is directly related to the error performance of the receiver, especially for high order Quadrature Amplitude Modulation (QAM) fiber DMT systems, which are sensitive to amplitude and phase deviations. Least Squares (LS) is a commonly used channel estimation method with low hardware implementation complexity. However, under the condition of large system noise interference, the accuracy of channel estimation is not high, a DMT transmitter often needs to transmit more Training Symbols (TS), and the receiving end performs time domain or frequency domain averaging on the received TSs to improve the accuracy of channel estimation. But the overhead of this approach is large. In order to reduce the TS overhead, the related literature proposes an ISFA channel estimation method based on a single TS (see the literature Liu, x.and f.buchai. "Intra-symbol frequency-domain estimation based channel estimation for coherent ofdm," opt.express 16(26):21944 21957, 2008). The method is based on a single TS LS estimation method, selects a proper average window size for channel estimation obtained primarily by using LS, averages channel estimation on a plurality of adjacent data subcarriers, reduces noise interference and improves estimation accuracy.
Although the ISFA estimation method can reduce the TS usage amount and improve the data transmission rate of the system, the method has the problem of inaccurate channel estimation of the edge subcarriers because the average window is asymmetric when estimating the channel estimation on the edge subcarriers, thereby possibly influencing the error code performance of a receiver. In addition, the selection of the average window size is dependent on system noise and the flatness of the channel response on each data subcarrier. Theoretically, the average window is increased, the noise suppression capability is enhanced, and the estimation accuracy is ultrahigh, but if the channel response correlation on the adjacent data subcarriers is low (or the channel response difference on the adjacent data subcarriers is large), the increase of the average window may cause the decrease of the channel estimation accuracy, and further increase the error rate of the receiver. If this problem is taken into account and only a small averaging window is used, the noise suppression capability is limited and the channel estimation accuracy is to be further improved.
Disclosure of Invention
In order to solve the above technical problem, the present invention provides an intra-symbol frequency domain average channel estimation method applied in a fiber DMT system, which has a simple algorithm and high accuracy.
The technical scheme for solving the problems is as follows: an intra-symbol frequency domain average channel estimation method applied in a fiber DMT system, comprising the steps of:
s1: estimating the channel frequency response on each data subcarrier by adopting a received training symbol based on a least square method channel estimation method, and preliminarily obtaining the channel estimation on each data subcarrier
Figure BDA0002271323070000021
i and k respectively represent the number of the training symbol and the index number of the corresponding subcarrier;
s2: to pair
Figure BDA0002271323070000031
Performing an averaging process to obtain HLS(k)；
S3: performing traditional ISFA channel estimation processing on channel estimation on non-edge data subcarriers;
s4: the ISFA channel estimation processing for improving the channel estimation on the edge data sub-carriers is carried out to finally obtain the channel estimation H on all the data sub-carriersmISFA(k)。
In the above method for estimating the frequency-domain average channel in the symbol applied in the DMT over fiber system, in step S1, the channel characteristics estimated by the least squares method are represented as:
Figure BDA0002271323070000032
in the formula (I), the compound is shown in the specification,
Figure BDA0002271323070000033
it represents that the receiver receives the frequency domain data with index number k in the ith training symbol, and t (k) is the locally stored frequency domain data of the reference training symbol, and its value is ± 1.
In the above method for estimating channel in frequency domain averaging in symbol in the DMT over fiber system, in step S2, the channel estimate after averaging is:
Figure BDA0002271323070000034
wherein N isTSIs the number of training symbols TS.
In the above method for estimating the frequency-domain average channel in the symbol applied in the DMT over fiber system, in step S3, the conventional ISFA channel estimation is defined as follows:
Figure BDA0002271323070000035
wherein k isminAnd k ismaxRespectively representing the minimum and maximum data subcarrier index numbers; m is the number of adjacent data sub-carrier channel estimates used to the left or right of the current sub-carrier when calculating the channel estimate on the current sub-carrier, and the average window size of the ISFA method is defined as 2m + 1.
In the above method for estimating the frequency-domain average channel in the symbol in the DMT over fiber system, in step S4, the improved ISFA channel estimation is defined as follows:
Figure BDA0002271323070000041
the above applicationsIn the intra-symbol frequency domain average channel estimation method in the DMT system, in the step S4, when calculating the channel estimation on the edge data subcarriers, the accurate estimation is achieved by reducing the size of the frequency domain average window and ensuring the symmetry thereof, wherein the index number satisfies k<kmin+ m and k>kmaxThe data subcarriers of-m are all referred to as edge data subcarriers.
In the above method for estimating the frequency domain average channel in the symbol applied in the fiber DMT system, the optimal value of m is related to the channel response and the signal-to-noise ratio of the system, and before using the method, the optimal value of m or the optimal average window size needs to be determined to obtain the optimal channel estimation.
The invention has the beneficial effects that:
the invention firstly adopts a small amount of TS to obtain preliminary channel estimation on each data subcarrier based on an LS channel estimation method; then, the obtained estimation information is subjected to average processing, so that the noise interference of the system is suppressed, and the accuracy of channel estimation is improved; and finally, performing improved ISFA channel estimation processing on the averaged estimation information, and when channel estimation on the edge data subcarrier is calculated, reducing the size of a frequency domain average window and ensuring the symmetry of the frequency domain average window to realize accurate estimation.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention is further described below with reference to the figures and examples.
As shown in fig. 1, a method for estimating an intra-symbol frequency domain average channel in a DMT over fiber system includes the following steps:
s1: estimating the channel frequency response on each data subcarrier by adopting a received training symbol based on a least square method channel estimation method, and preliminarily obtaining the channel estimation on each data subcarrieri and k represent the number of the training symbol and the index number of the corresponding subcarrier, respectively.
The channel characteristics estimated by the least squares method are expressed as:
Figure BDA0002271323070000052
in the formula (I), the compound is shown in the specification,
Figure BDA0002271323070000053
it represents that the receiver receives the frequency domain data with index number k in the ith training symbol, and t (k) is the locally stored frequency domain data of the reference training symbol, and its value is ± 1. The LS channel estimation method can be simplified accordingly.
S2: computing channel estimates using each TS
Figure BDA0002271323070000054
Then, the two are aligned
Figure BDA0002271323070000055
Performing an averaging process to obtain HLS(k) And the system noise interference is suppressed, and the accuracy of channel estimation is improved.
The averaged channel estimate is:
Figure BDA0002271323070000056
wherein N isTSIs the number of training symbols TS. It should be noted that although this method can provide accurate channel estimation, the number of required TSs is large, and the overhead is large. On the premise of ensuring the estimation performance, in order to reduce the TS number, the channel estimation of the traditional ISFA can be used on the basis of the LS method.
S3: the conventional ISFA channel estimation process is performed on the channel estimates on the non-edge data subcarriers.
The conventional ISFA channel estimation is defined as follows:
Figure BDA0002271323070000057
wherein k isminAnd k ismaxRespectively representing the minimum and maximum data subcarrier index numbers; m is the number of adjacent data sub-carrier channel estimates used to the left or right of the current sub-carrier when calculating the channel estimate on the current sub-carrier, and the average window size of the ISFA method is defined as 2m + 1. For conventional ISFA, the channel estimate on the edge data subcarrier, e.g., H, is calculatedISFA(kmin) And HISFA(kmax) When due to HLS(kmin-1) with HLS(kmax+1) is absent (or 0), resulting in asymmetry of the ISFA averaging window. When there is a difference in amplitude or phase in the channel response on these edge subcarriers, using the conventional ISFA method will result in inaccuracy in the channel estimation of the edge data subcarriers. This degree of inaccuracy becomes more pronounced as the averaging window increases, degrading the performance of the receiver.
S4: the ISFA channel estimation processing for improving the channel estimation on the edge data sub-carriers is carried out to finally obtain the channel estimation H on all the data sub-carriersmISFA(k)。
The improved ISFA channel estimation is defined as follows:
Figure BDA0002271323070000061
in calculating channel estimates on edge data subcarriers, accurate estimation is achieved by reducing the frequency domain average window size and ensuring its symmetry, where the index number satisfies k<kmin+ m and k>kmaxThe data subcarriers of-m are all referred to as edge data subcarriers.
The optimal value of m is related to the channel response and the signal-to-noise ratio of the system, and the optimal value of m or the optimal average window size needs to be determined before the method is used to obtain the optimal channel estimation.
By applying the embodiment of the invention, the received signal under the optical fiber DMT channel is processed, the initial channel estimation on each data subcarrier is obtained by adopting a small amount of TS based on an LS channel estimation method, then the obtained estimation information is averaged, and finally the averaged estimation information is subjected to improved ISFA channel estimation processing.

Claims (7)

1. An intra-symbol frequency domain average channel estimation method applied in a fiber DMT system, comprising the steps of:
s1: estimating the channel frequency response on each data subcarrier by adopting a received training symbol based on a least square method channel estimation method, and preliminarily obtaining the channel estimation on each data subcarrier
Figure FDA0002271323060000011
i and k respectively represent the number of the training symbol and the index number of the corresponding subcarrier;
s2: to pair
Figure FDA0002271323060000012
Performing an averaging process to obtain HLS(k)；
S3: performing traditional ISFA channel estimation processing on channel estimation on non-edge data subcarriers;
s4: the ISFA channel estimation processing for improving the channel estimation on the edge data sub-carriers is carried out to finally obtain the channel estimation H on all the data sub-carriersmISFA(k)。
2. The method of claim 1, wherein the channel characteristics of the least-squares estimation in step S1 are expressed as:
Figure FDA0002271323060000013
in the formula (I), the compound is shown in the specification,
Figure FDA0002271323060000014
it represents that the receiver receives the frequency domain data with index number k in the ith training symbol, and t (k) is the locally stored frequency domain data of the reference training symbol, and its value is ± 1.
3. The method of claim 2, wherein in step S2, the averaged channel estimate is obtained by:
Figure FDA0002271323060000015
wherein N isTSIs the number of training symbols TS.
4. The method of claim 3, wherein in-symbol frequency domain average channel estimation applied in the DMT over fiber system, in the step S3, the conventional ISFA channel estimation is defined as follows:
Figure FDA0002271323060000021
wherein k isminAnd k ismaxRespectively representing the minimum and maximum data subcarrier index numbers; m is the number of adjacent data sub-carrier channel estimates used to the left or right of the current sub-carrier when calculating the channel estimate on the current sub-carrier, and the average window size of the ISFA method is defined as 2m + 1.
5. The method of claim 4, wherein in-symbol frequency domain average channel estimation applied in DMT system over fiber, the improved ISFA channel estimation in step S4 is defined as follows:
Figure FDA0002271323060000022
6. root of herbaceous plantThe method of claim 5, wherein the step S4 is performed by reducing the size of the frequency domain averaging window and ensuring the symmetry thereof when calculating the channel estimation on the edge data subcarriers, wherein the index number satisfies k<kmin+ m and k>kmaxThe data subcarriers of-m are all referred to as edge data subcarriers.
7. The method of claim 5, wherein the optimal value of m is related to channel response characteristics and system SNR, and the optimal value of m or the optimal average window size is determined before using the method to obtain the optimal channel estimation.
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