CN109981513B - Time-frequency synchronization method and communication platform of indoor high-speed large-capacity MIMO-OFDM system - Google Patents

Time-frequency synchronization method and communication platform of indoor high-speed large-capacity MIMO-OFDM system Download PDF

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CN109981513B
CN109981513B CN201910066397.7A CN201910066397A CN109981513B CN 109981513 B CN109981513 B CN 109981513B CN 201910066397 A CN201910066397 A CN 201910066397A CN 109981513 B CN109981513 B CN 109981513B
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frequency offset
training sequence
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synchronization
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CN109981513A (en
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王勇
杨琳
田阗
宫丰奎
张南
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Xidian University
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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
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2656—Frame synchronisation, e.g. packet synchronisation, time division duplex [TDD] switching point detection or subframe synchronisation
    • 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
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2657—Carrier synchronisation
    • H04L27/2659—Coarse or integer frequency offset determination and synchronisation
    • 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
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2657—Carrier synchronisation
    • H04L27/266—Fine or fractional frequency offset determination and synchronisation
    • 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
    • H04L27/2647—Arrangements specific to the receiver only
    • H04L27/2655—Synchronisation arrangements
    • H04L27/2689—Link with other circuits, i.e. special connections between synchronisation arrangements and other circuits for achieving synchronisation
    • H04L27/2695—Link with other circuits, i.e. special connections between synchronisation arrangements and other circuits for achieving synchronisation with channel estimation, e.g. determination of delay spread, derivative or peak tracking
    • 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
    • H04L27/3845—Demodulator circuits; Receiver circuits using non - coherent demodulation, i.e. not using a phase synchronous carrier
    • H04L27/3854—Demodulator circuits; Receiver circuits using non - coherent demodulation, i.e. not using a phase synchronous carrier using a non - coherent carrier, including systems with baseband correction for phase or frequency offset

Abstract

The invention belongs to the technical field of wireless communication, and discloses a time and frequency synchronization method of an indoor high-speed large-capacity MIMO-OFDM system, which comprises the following steps: grouping by utilizing a PN1 training sequence, and dividing into five groups of adjacent groups for self-correlation to carry out frame synchronization; according to the principle of frequency offset estimation, the phase difference between adjacent groups of PN1 training sequences is utilized to carry out coarse frequency offset estimation synchronization; after estimating the coarse frequency offset, performing coarse frequency offset compensation on data on each receiving antenna; performing cross correlation by using a PN2 training sequence and a local PN2 training sequence to successfully avoid the influence of pseudo multipath and finish fine timing synchronization; carrying out fine frequency offset estimation by utilizing the autocorrelation of the PN2 training sequence and the cyclic prefix and the phase difference of front and back data; and after the fine frequency offset is estimated, performing fine frequency offset compensation on data on each receiving antenna. The fine timing synchronization processing of the invention can accurately detect the starting point, avoid introducing ISI and ensure the orthogonality among the subcarriers.

Description

Time-frequency synchronization method and communication platform of indoor high-speed large-capacity MIMO-OFDM system
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a time and frequency synchronization method of an indoor high-speed large-capacity MIMO-OFDM system.
Background
Currently, the current state of the art commonly used in the industry is such that: with the rapid development of information science and technology and the increasing number of electronic products such as portable mobile communication equipment, people continuously demand high information data, and more people urgently require that communication such as real-time and efficient data, voice and video can be carried out at any time and any place. For each individual using mobile internet technology, over 80% of users are in indoor environments. The indoor signal is obtained by considering the signals of the penetration loss and the reflection path, the reflection and refraction signals are not negligible for the limited indoor environment, and the multipath effect is more serious due to the increase of the signal reflection times in the indoor environment. The characteristics and analog methods of indoor wireless propagation channels have been of great interest in the field of wireless communications for many years. Neither of the commercially operated systems can ignore the coverage of the indoor environment and the indoor communication quality is receiving increasing attention.
In the future, wireless communication will have higher information transmission rate, and the design of high-speed wireless communication system has many challenges: the bandwidth is increased sharply, the channel environment is complex, and the system has low time delay and high reliability requirements. Orthogonal Frequency-Division Multiplexing (OFDM) technology can well overcome Frequency selective fading of a wireless channel, and due to the simplicity and high efficiency of implementation, OFDM has become one of the most core technologies in realizing future high-speed wireless communication. A mimo (Multiple Input Multiple output) system can easily obtain a spatial diversity gain of a wireless channel and realize a capacity gain of the wireless channel. The OFDM and MIMO technologies have become two major cornerstones of advanced wireless transmission technologies, and the combination of the OFDM and MIMO technologies is an obvious way to realize high-speed, large-capacity and reliable transmission of wireless data.
Synchronization is a problem to be solved for any digital communication system, and without an accurate synchronization algorithm, data cannot be received efficiently and reliably. OFDM systems are very sensitive to synchronization, and inaccurate synchronization can lead to degradation of system performance. For high-speed and large-capacity MIMO-OFDM systems, the fast, accurate and efficient time and frequency synchronization is a key and difficulty for improving the system performance. Currently, there are many research results for synchronization algorithms of siso (Single Input Single output) -OFDM system, and many synchronization algorithms are proposed in the industry so far, which are roughly divided into four types, that is, synchronization based on pilot frequency, synchronization based on guard interval, and synchronization based on training sequence. For an indoor high-speed and large-capacity MIMO-OFDM system, if a pilot frequency is used for synchronization processing, data needs to be converted from a time domain into a frequency domain, so that the complexity is increased, and the precision cannot be improved. Guard interval based synchronization requires processing in the data domain and does not meet the requirement of high speed for completion of the synchronization process before useful data arrives. Therefore, the training sequence based synchronization is selected to be used, and the synchronization is completed in the time domain before the valid data is received. Synchronization algorithms have received a lot of attention, for example, in 2015, a synchronization method is proposed, whose basic idea is to divide the synchronization process into two phases: a first coarse autocorrelation-based stage and a second fine differential correlation-based stage. Coarse synchronization is intended for coarse positioning by preamble autocorrelation, but autocorrelation presents a platform, leading to uncertainty in the accuracy of time detection, because the structure of cyclic repetition of the training sequence is large in the output of decision variables for the duration of the training symbols, and the position of the maximum value does not necessarily appear at the frame header. In the second stage, to mitigate the platform effect, the differentiation performs correlation using correlation shifts that are different from the preamble subsequence length. In the fine adjustment stage, the calculation load of the differential correlation operation is reduced by processing at short time intervals centering on the coarse time estimation, but a secondary peak occurs, the multipath effect is more serious due to the increase of the number of signal reflections in the indoor environment, and in the case of multiple transmitting antennas in the indoor MIMO-OFDM system, other antennas perform cyclic shift processing on data relative to the first antenna to avoid the beam forming effect, but a pseudo multipath effect is formed in the timing stage, so that isi (inter Symbol interference) is introduced into the deviation of the timing position, which may cause the deviation of the timing position and affect the overall performance of the receiver of the MIMO-OFDM system.
In summary, the problems of the prior art are as follows: the existing time and frequency synchronization algorithm has low precision and large error.
The difficulty of solving the technical problems is as follows:
in the indoor environment, due to the increase of the signal reflection times, the multipath effect is more serious, and due to the existence of multipath, data parts between the front symbol and the rear symbol are mutually overlapped to cause intersymbol interference. In the MIMO-OFDM system, since the transmission signal is affected by the same interference as that of the conventional single antenna system due to the increase of the number of transmission antennas and also has inter-antenna interference, the synchronization problem of the MIMO-OFDM system is much more difficult than that of the single antenna system.
The significance of solving the technical problems is as follows:
OFDM systems are very sensitive to synchronization and inaccurate synchronization can lead to degradation of system performance and introduce ISI. The synchronization process is the first operation to be performed by the MIMO-OFDM receiver, and is the basis for subsequent channel estimation and signal detection. For high-speed and large-capacity MIMO-OFDM systems, the fast, accurate and efficient time and frequency synchronization is a key and difficulty for improving the system performance.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a time and frequency synchronization method of an indoor high-speed large-capacity MIMO-OFDM system.
The invention is realized in such a way that a time and frequency synchronization method of an indoor high-speed large-capacity MIMO-OFDM system comprises the following steps:
firstly, grouping by utilizing a PN1 training sequence, and dividing into five groups of adjacent groups for self-correlation to carry out frame synchronization;
secondly, according to the principle of frequency offset estimation, the phase difference between adjacent groups of the PN1 training sequence is utilized to carry out coarse frequency offset estimation synchronization;
thirdly, after estimating the coarse frequency offset, performing coarse frequency offset compensation on data on each receiving antenna;
fourthly, cross-correlation is carried out by utilizing a PN2 training sequence and a local PN2 training sequence, so that the influence of pseudo multipath is successfully avoided, and fine timing synchronization is completed;
fifthly, performing fine frequency offset estimation by utilizing the autocorrelation of the PN2 training sequence and the cyclic prefix and the phase difference of front and back data;
and sixthly, performing fine frequency offset compensation on the data on each receiving antenna after estimating the fine frequency offset.
Further, the method for synchronizing time and frequency of the indoor high-speed large-capacity MIMO-OFDM system specifically comprises the following steps:
the method comprises the following steps: carrying out frame synchronization on the received data, and carrying out the frame synchronization process;
step two: performing coarse frequency offset estimation, wherein the coarse frequency offset estimation is completed in the frame synchronization process, and phase difference receiving antennas among the second group, the third group and the fourth group of adjacent groups are solved while the frame synchronization is performed, and MRC operation summation and averaging are performed to obtain coarse frequency offset delta fcoarseThe formula is;
Figure GDA0002981613770000041
wherein L isS2Representing the distance length between the packets, i representing the ith receiving antenna i-1, …, NrK (k is 2, …,4) represents the number of packets Ri,nRepresents the conjugate correlation window, n (n ═ 1, …, len) represents the length of the search window, and m (m ═ 1, … Ls2) A window length representing an autocorrelation;
the formula for solving the coarse frequency offset is as follows:
Figure GDA0002981613770000042
wherein arg (-) represents the phase value, Δ fcoarseIs the estimated coarse frequency offset;
step three, the coarse frequency offset compensation is carried out in the step, and the coarse frequency offset compensation formula of each antenna is as follows:
rk＝rk.*exp(j*2*pi*(-Δfcoarse)*(0:len-1)/Nfft)；
wherein r iskIs the k (k is 1, …, N)r) Signals of a receiving antenna, where NfftRepresenting the length of an OFDM symbol, NrNumber of receiving antennas,. DELTA.fcoarseIs estimated coarse frequency offset, j imaginary unit;
step four, pseudo multipath effect can be formed in the timing stage, which causes the deviation of the timing position to introduce ISI, and the error of frame synchronization is corrected;
step five, performing fine frequency offset estimation, wherein the fine frequency offset estimation adopts a PN2 training sequence;
and step six, performing frequency offset compensation by using the obtained fine frequency offset, wherein the formula of the frequency offset compensation is as follows:
rk＝rk.*exp(j*2*pi*(-Δffine)*(0:len-1)/Nfft)；
wherein r iskIs the k (k is 1, …, N)r) Signals of one receiving antenna,. DELTA.ffineIs the estimated fine frequency offset, len is the signal length, NfftIs the length of FFT, and the MIMO-OFDM system is synchronously completed.
Further, the first step specifically includes:
(1) dividing the received data into five groups and each group has length Ls2；
(2) For grouped data, each group of data is self-correlated with adjacent group to obtain conjugate correlation window Ri,nAnd an energy window Ci,nThe operation is performed on each receiving antenna, and finally, the decision variables on all the antennas are summed and averaged to perform mrc (maximum ratio combining) operation, wherein the formula is as follows:
Figure GDA0002981613770000051
Figure GDA0002981613770000052
wherein i (i ═ 1, …, N)r) Represents a receiving antenna, k represents the number of packets, k is 1, …,5, n (n is 1, …, len) represents the length of the search window, and m (m is 1, … L)s2) Window length representing autocorrelation, j is an imaginary unit, | · | is the modulo operator, Ri,nIs the conjugate correlation window, Ci,nIs the energy window, n represents the position n-L of the first set of PN1 training sequencess2；
(3) Obtaining energy window and conjugate correlation window to further solve decision variable MnThe formula is as follows:
Figure GDA0002981613770000053
wherein n is 1, …, len, MnRepresenting a decision variable, | · | is a modulo operator;
(4) when the continuous 30 values of the statistical decision variable are all larger than the decision threshold, the frame synchronization is considered to be successful, the position of the maximum value is kept and continuously updated in the statistical process, and the formula is as follows:
fram_pos＝max(Mn)；
where fram _ pos represents the location where a frame of data begins, frame synchronization, i.e., coarse timing, the location where the data begins is within a range of Δ τ e [ -L [ - ]cp,Lcp]The frame synchronization is successful as soon as the burst data frame arrives.
Further, the fourth step specifically includes:
(1) after correction of the coarse frequency offset, the backward shift is moved to L before the PN2 training sequencecpPoint;
(2) the received data is correlated with the local PN2 training sequence to obtain a correlation window Ci(n) the formula is:
Figure GDA0002981613770000061
wherein i (i ═ 1 … N)r) Which is representative of a receiving antenna or antennas,
Figure GDA0002981613770000062
representing the length of the cross-correlation window, pPN2(m) the local PN2 training sequences are processed on different antennas in a precise synchronization manner, ri(n) represents data received by the i-th receiving antenna, LPN2Represents the length of the PN2 training sequence;
(3) subtracting the previous correlation window from the obtained correlation window, and observing a subtracted term by a formula M (n), wherein the formula is as follows:
Figure GDA0002981613770000063
pos＝max(M(n))；
m (n) stands for decision variable
Figure GDA0002981613770000064
The position where pos represents the maximum value of the fine timing position is the position at the fine timing, and max (. circle-solid.) represents the maximum value.
Further, the fifth step specifically includes:
(1) fine frequency offset estimation at locations other than the beginning of the PN2 training sequence uses a forward shift in the position of the PN2 training sequence
Figure GDA0002981613770000065
And
Figure GDA0002981613770000066
(2) in that
Figure GDA0002981613770000067
And
Figure GDA0002981613770000068
respectively carrying out autocorrelation of PN2 training sequences to obtain Ri,1And Ri,2The PN2 training sequence is a sequence formed by adding GI to two sequences with equal length to obtain two frequency offsets of delta fi,1And Δ fi,2The formula is as follows:
Figure GDA0002981613770000069
Figure GDA00029816137700000610
Figure GDA00029816137700000611
Figure GDA00029816137700000612
wherein R isi,1(i＝1,…,Nr) Represents the autocorrelation of the first segment of the PN2 training sequence, and n represents the position where the PN1 training sequence ends
Figure GDA0002981613770000071
Ri,2(i＝1,…,Nr) Represents the autocorrelation, r, of the second segment of the PN2 training sequencei,n(m)m＝1,…,LPN2Represents the ith (i ═ 1, …, N)r) Data received by a receiving antenna, NfftIs the length arg (-) of an OFDM symbol represents the phase value;
(3) after obtaining two frequency offsets, summing and averaging, finally performing MRC operation on each antenna, and estimating fine frequency offset delta ffineThe formula is as follows:
Figure GDA0002981613770000072
wherein N isrFor the number of receiving antennas, i is 1, …, Nr。
Another object of the present invention is to provide a wireless communication platform applying the time and frequency synchronization method of the indoor high-speed large-capacity MIMO-OFDM system.
In summary, the advantages and positive effects of the invention are: in the frame synchronization stage, the autocorrelation of the PN1 training sequence is divided into five groups to achieve frame synchronization, a coarse frequency offset can be obtained by utilizing the phase difference of the front sequence and the rear sequence in the frame synchronization process by utilizing the grouping characteristic, compared with other synchronization processes, the frame synchronization and the coarse frequency offset can be completed together, resources are saved, and then in the fine timing stage, due to the fact that the MIMO-OFDM system carries out cyclic shift processing on data under the condition of multiple transmitting antennas, pseudo multipath effect is caused, and ISI is introduced due to the deviation of the timing position.
The invention can completely avoid the problem, corrects the frame synchronization error, ensures the initial position of OFDM symbols to carry out FFT demodulation, can accurately detect the initial point by fine timing synchronization processing to avoid introducing ISI, finally divides the PN2 training sequence into two parts in the fine frequency offset process to ensure the precision and not introduce ISI, ensures the orthogonality between subcarriers, and can improve the integral performance of the receiver synchronization of the MIMO-OFDM system based on the training sequence by the synchronization processing.
Drawings
Fig. 1 is a flowchart of a time and frequency synchronization method for an indoor high-speed large-capacity MIMO-OFDM system according to an embodiment of the present invention.
Fig. 2 is a format of a training sequence used according to an embodiment of the present invention.
Fig. 3 is a format of a PN1 training sequence used according to an embodiment of the present invention.
Fig. 4 shows a format of a PN2 training sequence when MIMO-OFDM system 2 is used for transmission 2 according to an embodiment of the present invention.
Fig. 5 shows the format of the PN2 training sequence when the MIMO-OFDM system 4 is used to transmit 4 according to an embodiment of the present invention.
Fig. 6 is a flowchart of frame synchronization of a MIMO-OFDM system based on a training sequence according to an embodiment of the present invention.
Fig. 7 is a simulation diagram of a training sequence-based indoor B channel fine timing method and an existing algorithm of a MIMO-OFDM system according to an embodiment of the present invention.
Fig. 8 is a simulation diagram of a B channel fine timing decision variable in an MIMO-OFDM system based on a training sequence according to an embodiment of the present invention.
Fig. 9 is a simulation diagram of a training sequence-based fine frequency offset estimation method for an indoor B channel of a MIMO-OFDM system and an existing algorithm according to an embodiment of the present invention.
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 with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The invention aims to solve the problems of low precision and large error of the existing time and frequency synchronization algorithm, and accurately, quickly and efficiently completes the time and frequency synchronization of the MIMO-OFDM system.
The following detailed description of the principles of the invention is provided in connection with the accompanying drawings.
As shown in fig. 1, the method for synchronizing time and frequency of an indoor high-speed large-capacity MIMO-OFDM system according to an embodiment of the present invention includes the following steps:
s101: grouping by utilizing a PN1 training sequence, and dividing into five groups of adjacent groups for self-correlation to carry out frame synchronization;
s102: according to the principle of frequency offset estimation, the phase difference between adjacent groups of PN1 training sequences is utilized to carry out coarse frequency offset estimation synchronization;
s103: after estimating the coarse frequency offset, performing coarse frequency offset compensation on data on each receiving antenna;
s104: performing cross correlation by using a PN2 training sequence and a local PN2 training sequence to successfully avoid the influence of pseudo multipath and finish fine timing synchronization;
s105: carrying out fine frequency offset estimation by utilizing the autocorrelation of the PN2 training sequence and the cyclic prefix and the phase difference of front and back data;
s106: and after the fine frequency offset is estimated, performing fine frequency offset compensation on data on each receiving antenna.
The time and frequency synchronization method of the indoor high-speed large-capacity MIMO-OFDM system provided by the embodiment of the invention specifically comprises the following steps:
the signal received by the receiver is
Figure GDA0002981613770000091
NrRepresenting the number of receiving antennas NtRepresenting the number of transmitting antennas, k being 1, …, Nr，rk(n) is a signal of the kth receiving antenna, and len is a received signal length defined as follows for each parameter: n is a radical offftRepresents the length of an OFDM symbol, LPN1Representing the length of the PN1 training sequence
Figure GDA0002981613770000092
LS1Representing the length of each data in the PN1 training sequence 10 array
Figure GDA0002981613770000093
Ls2Length of every two groups of data in training sequence 10 array
Figure GDA0002981613770000094
LPN2Length L representing PN2 training sequencePN2＝Nfft，LcpLength of cyclic prefix equal to
Figure GDA0002981613770000095
pPN2(m) stands for local training sequence m-1, … LPN2；
The method comprises the following steps: performing frame synchronization on the received data, and performing a frame synchronization process, as shown in fig. 6;
(1) firstly, received data is divided into five groups, and the length of each group of data is Ls2；
(2) For grouped data, each group of data is self-correlated with adjacent group to obtain conjugate correlation window Ri,nAnd an energy window Ci,nThe operation is performed on each receiving antenna, and finally, the decision variables on all the antennas are summed and averaged to perform mrc (maximum ratio combining) operation, wherein the formula is as follows:
Figure GDA0002981613770000096
Figure GDA0002981613770000097
wherein i (i ═ 1, …, N)r) Represents a receiving antenna, k represents the number of packets, k is 1, …,5, n (n is 1, …, len) represents the length of the search window, and m (m is 1, … L)s2) Window length representing autocorrelation, j is an imaginary unit, | · | is the modulo operator, Ri,nIs the conjugate correlation window, Ci,nIs the energy window, n represents the position n-L of the first set of PN1 training sequencess2；
(3) Obtaining energy window and conjugate correlation window to further solve decision variable MnThe formula is as follows:
Figure GDA0002981613770000101
wherein n is 1, …, len, MnRepresenting a decision variable, | · | is a modulo operator;
(4) when the continuous 30 values of the statistical decision variable are all larger than the decision threshold, the frame synchronization is considered to be successful, the position of the maximum value is kept and continuously updated in the statistical process, and the formula is as follows:
fram_pos＝max(Mn)；
where fram _ pos represents the location where a frame of data begins, frame synchronization, i.e., coarse timing, the location where the data begins is within a range of Δ τ e [ -L [ - ]cp,Lcp]When the burst data frame arrives, the frame synchronization is successful;
step two: performing coarse frequency offset estimation, wherein the coarse frequency offset estimation is completed in the frame synchronization process, and phase difference receiving antennas among the second group, the third group and the fourth group of adjacent groups are solved while the frame synchronization is performed, and MRC operation summation and averaging are performed to obtain coarse frequency offset delta fcoarseThe formula is;
Figure GDA0002981613770000102
wherein L isS2Representing the distance length between the packets, i representing the ith receiving antenna i-1, …, NrK (k is 2, …,4) represents the number of packets Ri,nRepresents the conjugate correlation window, n (n ═ 1, …, len) represents the length of the search window, and m (m ═ 1, … Ls2) A window length representing an autocorrelation;
the formula for solving the coarse frequency offset is as follows:
Figure GDA0002981613770000103
wherein arg (-) represents the phase value, Δ fcoarseIs the estimated coarse frequency offset;
step three, the coarse frequency offset compensation is carried out in the step, and the coarse frequency offset compensation formula of each antenna is as follows:
rk＝rk.*exp(j*2*pi*(-Δfcoarse)*(0:len-1)/Nfft)；
wherein r iskIs the k (k is 1, …, N)r) Signals of a receiving antenna, where NfftRepresenting the length of an OFDM symbol, NrNumber of receiving antennas,. DELTA.fcoarseIs estimated coarse frequency offset, j imaginary unit;
in the fine timing stage, due to the fact that the MIMO-OFDM system is under the condition of multiple transmitting antennas, other antennas can perform cyclic shift processing on data relative to the first antenna so as to avoid beam forming effect, however, pseudo multipath effect can be formed in the timing stage, ISI is introduced due to deviation of timing position, and the algorithm can completely avoid correcting frame synchronization error.
(1) After correction of the coarse frequency offset, the backward shift is moved to L before the PN2 training sequencecpPoints to avoid the impact of frame synchronization;
(2) the received data is correlated with the local PN2 training sequence to obtain a correlation window Ci(n) the formula is:
Figure GDA0002981613770000111
wherein i (i ═ 1 … N)r) Which is representative of a receiving antenna or antennas,
Figure GDA0002981613770000112
representing the length of the cross-correlation window, pPN2(m) the local PN2 training sequences are processed on different antennas in a precise synchronization manner, ri(n) represents data received by the i-th receiving antenna, LPN2Represents the length of the PN2 training sequence;
(3) in order to avoid the pseudo multipath effect caused by the cyclic shift, the obtained correlation window is subtracted from the previous obtained correlation window, and because other transmitting antennas are in cyclic right shift operation relative to the first transmitting antenna, the pseudo multipath is equivalent to the position of the real path when the correlation window reaches the pseudo multipath, and no peak appears at this time, and the formula m (n) can be used to observe that the subtracted term plays a role at this time, so that the pseudo multipath effect can be avoided by suppressing the peak, wherein the formula is as follows:
Figure GDA0002981613770000113
pos＝max(M(n))；
m (n) stands for decision variable
Figure GDA0002981613770000114
pos represents the position of the maximum value of the fine timing position, namely the position of the fine timing, and max (·) represents the maximum value;
step five, performing fine frequency offset estimation, wherein the fine frequency offset estimation adopts a PN2 training sequence;
(1) to avoid the ISI effect on the fine frequency offset estimation, the fine frequency offset estimation not performed at the beginning of the PN2 training sequence is performed by moving forward at the position of the PN2 training sequence
Figure GDA0002981613770000121
And
Figure GDA0002981613770000122
(2) in that
Figure GDA0002981613770000123
And
Figure GDA0002981613770000124
respectively carrying out autocorrelation of PN2 training sequences to obtain Ri,1And Ri,2Because the PN2 training sequence is composed of two sequences with equal length and GI, this operation results in two frequency offsets Δ fi,1And Δ fi,2Compared with other algorithms, the method ensures the precision and does not introduce ISI, and the formula is as follows:
Figure GDA0002981613770000125
Figure GDA0002981613770000126
Figure GDA0002981613770000127
Figure GDA0002981613770000128
wherein R isi,1(i＝1,…,Nr) Represents the autocorrelation of the first segment of the PN2 training sequence, and n represents the position where the PN1 training sequence ends
Figure GDA0002981613770000129
Ri,2(i＝1,…,Nr) Represents the autocorrelation, r, of the second segment of the PN2 training sequencei,n(m)m＝1,…,LPN2Represents the ith (i ═ 1, …, N)r) Data received by a receiving antenna, NfftIs the length arg (-) of an OFDM symbol represents the phase value;
(3) after the two frequency offsets are obtained, summing and averaging are carried out, the operation is carried out on each antenna, and finally MRC operation is carried out, so that fine frequency offset delta f is estimatedfineThe formula is as follows:
Figure GDA00029816137700001210
wherein N isrFor the number of receiving antennas, i is 1, …, Nr；
And step six, performing frequency offset compensation by using the obtained fine frequency offset, wherein the formula of the frequency offset compensation is as follows:
rk＝rk.*exp(j*2*pi*(-Δffine)*(0:len-1)/Nfft)；
wherein r iskIs the k (k is 1, …, N)r) Signals of one receiving antenna,. DELTA.ffineIs the estimated fine frequency offset, len is the signal length, NfftIs the length of FFT, and the MIMO-OFDM system is synchronously completed.
The application effect of the present invention will be described in detail with reference to the simulation.
1. Simulation conditions are as follows: the MIMO-OFDM system has two transmissions and two receptions, and the number of OFDM subcarriers is Nfft64, the number of useful subcarriers is Lsub＝52；
2. Simulation content and results:
simulation 1, in an indoor B channel, comparing a fine timing algorithm with the existing and Leil algorithms, it can be seen that the advantages of the present invention are shown in fig. 7, it can be seen that although the Leil algorithm has good performance in a gaussian channel, the MIMO-OFDM communication system has no good performance of the present algorithm in the indoor B channel, however, in an actual communication system, multipath channels must be considered, especially under an indoor channel condition, signals of penetration loss and reflection paths are considered for indoor obtained signals, reflection and refraction signals are not negligible for a limited indoor environment, and the multipath effect is more serious due to the increase of the number of signal reflections in the indoor environment, so the algorithm of the patent invention has obvious advantages compared with the Leil algorithm, and better meets the requirements of the actual indoor MIMO-OFDM communication system.
Simulation 3, in an indoor channel B, a simulation diagram of a fine timing decision variable is shown in fig. 8, it can be seen that an obvious correlation peak is located at a correct synchronization position, and the decision variable is negative at a point of a pseudo path caused by cyclic shift, so that it is obvious that the algorithm of the present invention can effectively avoid the problem of the pseudo path caused by cyclic shift between transmit antenna data of the MIMO-OFDM system.
Simulation 4, in an indoor B channel, the fine frequency offset method compares the present invention with the existing Schmidl algorithm and its improved algorithm 1, and it can be seen that the advantages of the present invention are shown in fig. 9, the algorithm has higher accuracy than the Schmidl algorithm under the same signal-to-noise ratio, and the algorithm has higher accuracy than the improved algorithm 1 under the high signal-to-noise ratio because the improved algorithm 1 does not consider the influence of multipath, and introduces ISI using the information of cyclic prefix, however, in the actual communication system, the multipath channel must be considered, especially under the indoor channel condition, so the algorithm of the patent invention has obvious advantages over the Schmidl algorithm and its improved algorithm 1, and better conforms to the requirements of the actual MIMO-OFDM communication system;
as can be seen from fig. 7, 8 and 9, the MIMO-OFDM system time and frequency synchronization method based on the training sequence of the present invention has more advantages in overall performance both in an additive white gaussian noise channel and in an indoor multipath channel, and the success probability of fine timing synchronization can be 1 even in a poor multipath channel with a low signal-to-noise ratio. In the fine frequency offset estimation, under an indoor multipath channel, the algorithm can ensure higher precision and simultaneously does not introduce ISI.
Simulation figure 7 sets the Monte Carlo simulation times to 10000 times under the environment that the channel in the indoor MIMO-OFDM system with two-transmission and two-reception is the indoor standard B channel, and the probability of successful fine synchronization is 100% when the signal-to-noise ratio is 6 dB. As can be seen from the simulation fig. 8, in the MIMO-OFDM system with two transmitters and two receivers, the decision variable is not affected by the pseudo multipath effect caused by the cyclic shift of the transmitting antenna, and the decision result is not affected by the sub-peak. In the simulation figure 9, the Monte Carlo simulation times are set to 10000 times in the environment that the channel in the two-transmission and two-reception indoor MIMO-OFDM system is an indoor standard B channel, and the indoor B channel is a multipath channel, so that the mean square error is 2.92e-06 when the algorithm of the patent improves the precision frequency offset estimation and avoids the influence of pseudo multipath on the signal-to-noise ratio to be 15 dB.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.

Claims (2)

1. A time and frequency synchronization method of an indoor high-speed large-capacity MIMO-OFDM system is characterized by comprising the following steps:
firstly, grouping the trained sequences by utilizing a PN1 training sequence, and dividing the sequences into five groups of adjacent groups for self-correlation to carry out frame synchronization;
secondly, according to the principle of frequency offset estimation, the phase difference between adjacent groups of the PN1 training sequence is utilized to carry out coarse frequency offset estimation synchronization;
thirdly, after estimating the coarse frequency offset, performing coarse frequency offset compensation on data on each receiving antenna;
fourthly, cross-correlation is carried out by utilizing a PN2 training sequence and a local PN2 training sequence, so that the influence of pseudo multipath is successfully avoided, and fine timing synchronization is completed;
fifthly, performing fine frequency offset estimation by utilizing the autocorrelation of the PN2 training sequence and the cyclic prefix and the phase difference of front and back data;
sixthly, performing fine frequency offset compensation on data on each receiving antenna after estimating the fine frequency offset;
the time and frequency synchronization method of the indoor high-speed large-capacity MIMO-OFDM system specifically comprises the following steps:
the method comprises the following steps: carrying out frame synchronization on the received data, and carrying out the frame synchronization process; the method specifically comprises the following steps:
(1) dividing the received data into five groups and each group has length Ls2；
(2) For grouped data, each group of data is self-correlated with adjacent group to obtain conjugate correlation window Ri,nAnd an energy window Ci,nAnd finally, summing the decision variables of all the antennas to average and perform MRC operation, wherein the formula is as follows:
Figure FDA0003207185610000011
Figure FDA0003207185610000012
where i denotes a receiving antenna, where i is 1, …, NrAnd k represents the number of packets k equal to 1, …5, n represents the length of the search window, where n1, …, len, m represents the window length of the autocorrelation, where m 1, … Ls2(ii) a j is an imaginary unit, | · | is a modulo operator, Ri,nIs the conjugate correlation window, Ci,nIs the energy window, n represents the position n-L of the first set of PN1 training sequencess2；
(3) Obtaining energy window and conjugate correlation window to further solve decision variable MnThe formula is as follows:
Figure FDA0003207185610000021
wherein n is 1, …, len, MnRepresenting a decision variable, | · | is a modulo operator;
(4) when the continuous 30 values of the statistical decision variable are all larger than the decision threshold, the frame synchronization is considered to be successful, the position of the maximum value is kept and continuously updated in the statistical process, and the formula is as follows:
fram_pos＝max(Mn)；
where fram _ pos represents the location where a frame of data begins, frame synchronization, i.e., coarse timing, the location where the data begins is within a range of Δ τ e [ -L [ - ]cp,Lcp]When the burst data frame arrives, the frame synchronization is successful;
step two: performing coarse frequency offset estimation, wherein the coarse frequency offset estimation is completed in the frame synchronization process, and phase difference receiving antennas among the second group, the third group and the fourth group of adjacent groups are solved while the frame synchronization is performed, and MRC operation summation and averaging are performed to obtain coarse frequency offset delta fcoarseThe formula is;
Figure FDA0003207185610000022
wherein L isS2Representing the distance length between the packets, i representing the ith receiving antenna i-1, …, NrK represents the number of packets Ri,nRepresents the conjugate correlation window, where k is 2, …,4, and n represents the length of the search window, where n is1, …, len, m stands for window length of autocorrelation, where m is 1, … Ls2；
The formula for solving the coarse frequency offset is as follows:
Figure FDA0003207185610000023
wherein arg (-) represents the phase value, Δ fcoarseIs the estimated coarse frequency offset;
step three, the coarse frequency offset compensation is carried out in the step, and the coarse frequency offset compensation formula of each antenna is as follows:
rk＝rk.*exp(j*2*pi*(-Δfcoarse)*(0:len-1)/Nfft)；
wherein r iskIs the signal of the kth receiving antenna, where k is 1, …, NrIn which N isfftRepresenting the length of an OFDM symbol, NrNumber of receiving antennas,. DELTA.fcoarseIs estimated coarse frequency offset, j imaginary unit;
step four, pseudo multipath effect can be formed in the timing stage, which causes the deviation of the timing position to introduce ISI, and the error of frame synchronization is corrected;
step five, performing fine frequency offset estimation, wherein the fine frequency offset estimation adopts a PN2 training sequence;
and step six, performing frequency offset compensation by using the obtained fine frequency offset, wherein the formula of the frequency offset compensation is as follows:
rk＝rk.*exp(j*2*pi*(-Δffine)*(0:len-1)/Nfft)；
wherein r iskIs the signal of the kth receiving antenna, where k is 1, …, Nr，ΔffineIs the estimated fine frequency offset, len is the signal length, NfftThe length of FFT, MIMO-OFDM system is completed synchronously;
the fourth step specifically comprises:
(1) after correction of the coarse frequency offset, the backward shift is moved to L before the PN2 training sequencecpPoint;
(2) the received data is correlated with the local PN2 training sequenceCorrelation window Ci(n) the formula is:
Figure FDA0003207185610000031
where i denotes a receiving antenna, where i is 1, …, NrAnd n represents the length of the cross-correlation window, wherein
Figure FDA0003207185610000032
pPN2(m) the local PN2 training sequences are processed on different antennas in a precise synchronization manner, ri(n) represents data received by the i-th receiving antenna, LPN2Represents the length of the PN2 training sequence;
(3) subtracting the previous correlation window from the obtained correlation window, and observing a subtracted term by a formula M (n), wherein the formula is as follows:
Figure FDA0003207185610000033
pos＝max(M(n))；
m (n) stands for decision variable
Figure FDA0003207185610000041
pos represents the position of the maximum value of the fine timing position, namely the position of the fine timing, and max (·) represents the maximum value;
the fifth step specifically comprises:
(1) fine frequency offset estimation at locations other than the beginning of the PN2 training sequence uses a forward shift in the position of the PN2 training sequence
Figure FDA0003207185610000042
And
Figure FDA0003207185610000043
(2) in that
Figure FDA0003207185610000044
And
Figure FDA0003207185610000045
respectively carrying out autocorrelation of PN2 training sequences to obtain Ri,1And Ri,2The PN2 training sequence is a sequence formed by adding GI to two sequences with equal length to obtain two frequency offsets of delta fi,1And Δ fi,2The formula is as follows:
Figure FDA0003207185610000046
Figure FDA0003207185610000047
Figure FDA0003207185610000048
Figure FDA0003207185610000049
wherein R isi,1Represents the autocorrelation of the first segment of the PN2 training sequence, where i ═ 1, …, NrAnd n represents the position where the PN1 training sequence ends
Figure FDA00032071856100000410
Ri,2Autocorrelation representing the second segment of the PN2 training sequence, where i ═ 1, …, Nr，ri,n(m)m＝1,…,LPN2Representing data received by the ith receiving antenna, where i is 1, …, Nr，NfftIs the length arg (-) of an OFDM symbol represents the phase value;
(3) after obtaining two frequency offsets, summing and averaging, finally performing MRC operation on each antenna, and estimating fine frequency offset delta ffineThe formula is as follows:
Figure FDA00032071856100000411
wherein N isrFor the number of receiving antennas, i is 1, …, Nr。
2. A wireless communication platform applying the time and frequency synchronization method of the indoor high-speed large-capacity MIMO-OFDM system of claim 1.
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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101083647A (en) * 2006-05-30 2007-12-05 中兴通讯股份有限公司 Method for realizing synchronization in multi-input multi-output OFDM system
CN105847211A (en) * 2016-03-15 2016-08-10 东南大学 Carrier frequency offset estimation method suitable for MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) system

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8064528B2 (en) * 2003-05-21 2011-11-22 Regents Of The University Of Minnesota Estimating frequency-offsets and multi-antenna channels in MIMO OFDM systems
CN103259757B (en) * 2013-05-22 2015-10-21 西南石油大学 A kind of synchronous new method of Time And Frequency of effective MIMO-OFDM system

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101083647A (en) * 2006-05-30 2007-12-05 中兴通讯股份有限公司 Method for realizing synchronization in multi-input multi-output OFDM system
CN105847211A (en) * 2016-03-15 2016-08-10 东南大学 Carrier frequency offset estimation method suitable for MIMO-OFDM (Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing) system

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
MIMO-OFDM系统的同步、信道估计和自适应算法;蔡斌;《中国优秀博硕士学位论文全文数据库 (硕士) 信息科技辑》;20070510;全文 *

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