CN1665230A - Method of low-complexity frequency deviation estimation based on adjustable time frequency training sequence - Google Patents
Method of low-complexity frequency deviation estimation based on adjustable time frequency training sequence Download PDFInfo
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Abstract
The invention discloses a low-complexity frequency bias estimating method based on a regulable time frequency training sequence, a frequency synchronizing method applied to OFDM system and other blocked transmitting systems, where the regulable time-frequency training sequence is composed of alpha N-long frequency domain sequence TS1 and (1-alpha)N-long time frequency sequence TS2, where the length ratio of the two parts is regulable and the total length keeps invariant; for resisting the interference IS1 between symbols, it inserts a Ng-long circulating prefix in both the two parts; the frequency domain sequence TS1 is composed of K inequi-distant pilot frequencies and the time domain sequence TS2 is composed of P same-length U subsequences; by choosing the parameters, the corresponding frequency bias estimators can obtain different balance of complex property, thus applied to different wireless mobile scenes. Wherein, Ng should be greater than the maximum time delay extension of wireless multipath channel, and PU= (1-alpha)N.
Description
Technical Field
The invention relates to a frequency synchronization method applied to an Orthogonal Frequency Division Multiplexing (OFDM) system and other block transmission systems, belonging to the technical field of synchronization in mobile communication.
Background
Frequency synchronization is a prerequisite for a mobile communication system to be able to communicate properly. To be able to support high-speed data services, future mobile communication systems will be broadband, multi (transmitting, receiving) antenna systems, while OFDM is an important candidate for future mobile communication systems. For future mobile wireless communications, the time-varying nature of the broadband wireless channel can affect the carrier frequency, shifting it, and thus destroying the orthogonality between subcarriers within the OFDM system. Compared with a single carrier system, the OFDM system is more sensitive to carrier frequency offset, and how to reduce the influence of inter-subcarrier interference ICI on system performance is one of the prerequisites that the OFDM system can be widely applied. The conventional frequency synchronization methods, which estimate the carrier frequency offset based on either the frequency domain training sequence or the time domain training sequence, have the following disadvantages: unsuitability for packet data transmission, too high load, small capture range, non-ideal estimation performance and high calculation complexity. The invention overcomes the defects and provides a method for frequency offset estimation based on an adjustable time-frequency training sequence.
Disclosure of Invention
The technical problem is as follows: the invention aims to provide a low-complexity frequency offset estimation method based on an adjustable time-frequency training sequence, and accordingly, the low-complexity frequency offset estimation method is quick and reliable, small in load, large in capture range, high in estimation precision, low in implementation complexity and suitable for continuous data transmission and packet data transmission.
The technical scheme is as follows: the low-complexity frequency offset estimation method based on the adjustable time-frequency training sequence comprises the following steps:
1) carrying out beta-time fast Fourier transform interpolation on the received frequency domain sequence TS 1, and calculating a periodogram thereof according to the interpolation;
2) searching the peak amplitude of the corresponding periodogram by using a bubbling method;
3) determining the peak pilot frequency in the set { i ] according to the predefined lookup tablek}0 K-1The index value of (1);
4) calculating the offset of the found peak frequency domain pilot frequency and normalizing the offset to N, thereby determining a coarse frequency offset estimation value;
5) performing coarse frequency offset correction on the received time domain sequence TS 2;
6) calculating a phase angle rotation component caused by frequency offset for the corrected time domain sequence TS 2 according to P identical subsequences contained in the corrected time domain sequence TS 2;
7) carrying out weighted average and normalization on the phase angle rotation components to obtain corresponding fine frequency offset estimation values;
8) and adding the estimated coarse frequency offset value and the estimated fine frequency offset value to obtain a total frequency offset estimation value.
Where β should be from set {2 }n}0 -log2αIs selected from the set {2 } of-n}1 log2N-1In the selection, N > 0 is the total length of the time-frequency training sequence, and the set { i ^ isk}0 K-1Denotes the index values of K unequally spaced pilots in the frequency domain sequence TS 1, 0 < K □ alpha N.
The adjustable time-frequency training sequence is composed of a frequency domain sequence TS 1 with the length of alpha N and a time domain sequence TS 2 with the length of (1-alpha) N, the ratio of the two parts can be adjusted, but the total length is ensuredRemains unchanged as N; to combat intersymbol interference (ISI), the two partial sequences are preceded by an insertion of length NgThe cyclic prefix of (c); the frequency domain sequence TS 1 consists of K pilot frequencies with unequal intervals, and the time domain sequence TS 2 consists of P subsequences with the same length of U; through the selection of parameters, the corresponding frequency offset estimator can obtain different complexity performance tradeoffs, and therefore the frequency offset estimator can be applied to different wireless mobile scenes. Wherein N isgShould be larger than the maximum delay spread of the wireless multipath channel, PU ═ 1- α) N.
The predefined lookup table has the following storage contents:
| i1-i0 | i2-i0 | … | iK-1-i0 |
| i2-i1 | i3-i1 | … | i0-i1+αN |
| * | * | * | * |
| i0，iK-1+αN | i1-iK-1+αN | … | iK-2-iK-1+αN |
wherein i0，i1，…，iK-1Is the index value of the K unequally spaced pilots contained in the frequency domain sequence TS 1.
Has the advantages that:
1. the concept of the time-frequency training sequence is introduced, and the respective advantages of the time-domain training sequence and the frequency-domain training sequence are fully utilized, so that the optimal estimation performance can be obtained.
2. By adopting the lookup table, the structural characteristics of the frequency domain training sequence are fully utilized, the accuracy probability of the coarse frequency offset estimation is improved, and the time consumption for completing the coarse frequency offset estimation is greatly reduced.
3. According to the actual carrier frequency offset and different specific application scenes, different time-frequency training sequence parameters and structures are selected, and therefore optimal complexity performance compromise balance is obtained.
4. The fine frequency offset estimation algorithm can be selected differently according to different specific application scenes and time-frequency training sequence structures, and the flexibility and the diversity of the specific system implementation are greatly enriched.
The frequency offset estimation algorithm provided by the invention can be used for any block transmission system.
The invention mainly considers how to reduce the system load in the mobile communication system, reduce the complexity of the estimation algorithm, and improve the system performance, so that the system can support the high-speed data service more efficiently.
Drawings
FIG. 1 is a schematic diagram of a time-frequency training sequence structure according to the present invention. Wherein f represents a frequency domain, t represents a time domain, CP represents a cyclic prefix, TS 1 represents a frequency domain sequence, TS 2 represents a time domain sequence, N represents a cyclic prefix, andgfor the length of the cyclic prefix, α N and (1- α) N are the lengths of TS 1 and TS 2, respectively; i.e. i0，i1，…，iK-1Is the index value of K pilot frequencies with unequal intervals contained in TS 1, and U is TS2, each of the P subsequences contained in 2.
Fig. 2 is a schematic diagram of a frequency offset estimation method based on an adjustable time-frequency training sequence.
Fig. 3 is a schematic diagram of an implementation structure of a frequency offset estimation algorithm based on an adjustable time-frequency training sequence (the implementation structure of a fine frequency offset estimation algorithm when α β is 1, and the fine frequency offset estimation algorithm when α β is 1 is a specific example of the fine frequency offset estimation algorithm when α β is less than 1). It includes interpolation device, squaring device, peak amplitude searching device, peak pilot index calculating device, offset calculating and normalizing device, multiplication accumulation device, phase angle calculating device and addition device. The fine frequency offset estimator when α β is 1 is composed of a multiplication accumulation device and a phase angle calculation device.
Detailed Description
Suppose that the number of subcarriers included in one OFDM symbol is N, and the length of the CP is Ng. The length of the frequency domain sequence TS 1 is NFα N, consisting of K non-zero pilots with unequal spacing for use with <math> <mrow> <msub> <mover> <mi>p</mi> <mo>~</mo> </mover> <mi>K</mi> </msub> <mo>=</mo> <msup> <mrow> <mo>[</mo> <msub> <mover> <mi>p</mi> <mo>~</mo> </mover> <msub> <mi>i</mi> <mn>0</mn> </msub> </msub> <mo>,</mo> <msub> <mover> <mi>p</mi> <mo>~</mo> </mover> <msub> <mi>i</mi> <mn>1</mn> </msub> </msub> <mo>,</mo> <mo>·</mo> <mo>·</mo> <mo>·</mo> <msub> <mover> <mi>p</mi> <mo>~</mo> </mover> <msub> <mi>i</mi> <mrow> <mi>K</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </msub> <mo>]</mo> </mrow> <mi>T</mi> </msup> </mrow> </math> Represents; the length of the time domain sequence TS 2 is NT(1- α) N, consisting of P identical subsequences of length U.
After the received training sequence is subjected to beta-time fast Fourier transform interpolation and the periodogram is calculated, peak amplitude search is carried out by using an bubbling method, then the received training sequence passes through a peak pilot index value calculation unit, the offset of the peak pilot is calculated and normalized to N to obtain a corresponding coarse frequency offset estimation value, and then the received time domain sequence is sent to a coarse frequency offset correction unit. According to the difference of time-frequency training sequence structures, the fine frequency offset estimation is divided into two conditions: if alpha beta is 1, the corrected time domain sequence is sequentially sent to a multiplication accumulator and a phase angle calculation module, and finally a corresponding fine frequency offset estimation value is obtained; and if alpha beta is less than 1, the corrected time domain sequence is sequentially sent to a multiplication accumulator, a multiplier, a phase angle calculation module and the multiplication accumulator to obtain a fine frequency offset estimation value. And finally, adding the coarse frequency offset estimation value and the fine frequency offset estimation value to output a total frequency offset estimation value.
The specific algorithm is described as follows:
the received sequence expression affected by the frequency offset epsilon can be written as:
Where φ is the phase offset introduced due to timing error or wiener phase noise, <math> <mrow> <mover> <mi>F</mi> <mo>‾</mo> </mover> <mo>=</mo> <mo>[</mo> <msub> <mi>f</mi> <msub> <mi>i</mi> <mn>0</mn> </msub> </msub> <mo>,</mo> <msub> <mi>f</mi> <msub> <mi>i</mi> <mn>1</mn> </msub> </msub> <mo>,</mo> <mo>·</mo> <mo>·</mo> <mo>·</mo> <mo>,</mo> <msub> <mi>f</mi> <msub> <mi>i</mi> <mrow> <mi>K</mi> <mo>-</mo> <mn>1</mn> </mrow> </msub> </msub> <mo>]</mo> </mrow> </math> is NFAn inverse Fourier transform matrix of xK, w is an additive white Gaussian noise signal.
Then, a periodogram of the received sequence is calculated by a fast fourier transform interpolation technique:
Wherein, <math> <mrow> <msub> <mover> <mi>r</mi> <mo>‾</mo> </mover> <mi>n</mi> </msub> <mo>=</mo> <mfenced open='{' close=''> <mtable> <mtr> <mtd> <msub> <mi>r</mi> <mi>n</mi> </msub> <mo>,</mo> </mtd> <mtd> <mi>n</mi> <mo>=</mo> <mn>0,1</mn> <mo>,</mo> <mo>·</mo> <mo>·</mo> <mo>·</mo> <mo>,</mo> <msub> <mi>N</mi> <mi>F</mi> </msub> <mo>-</mo> <mn>1</mn> </mtd> </mtr> <mtr> <mtd> <mn>0</mn> <mo>,</mo> </mtd> <mtd> <mi>n</mi> <mo>=</mo> <msub> <mi>N</mi> <mi>F</mi> </msub> <mo>,</mo> <msub> <mi>N</mi> <mi>F</mi> </msub> <mo>+</mo> <mn>1</mn> <mo>,</mo> <mo>·</mo> <mo>·</mo> <mo>·</mo> <mo>,</mo> <mi>β</mi> <msub> <mi>N</mi> <mi>F</mi> </msub> <mo>-</mo> <mn>1</mn> </mtd> </mtr> </mtable> </mfenced> <mo>;</mo> </mrow> </math> beta represents the zero interpolation ratio. The interpolated signal is sent to a peak amplitude search unit to find the following maximum values:
The peak pilot signal is then located in the set i according to a predefined look-up tablek}0 K-1The index value of (1), namely:
Therein, IIk，gIndicating the contents of the g column stored in the look-up table at the k row. And sending the result of the formula to an offset calculation and normalization module to obtain a coarse frequency offset estimation value:
δ＝(ζ-βik) /(. alpha. beta.) [ equation five]
Then, the received time domain sequence tn}0 NT-1Sending to a corresponding coarse frequency offset correction module:
Assuming that α β is 1, the corrected time domain sequence is sequentially sent to the multiplication accumulator and the phase angle calculation module, and the corresponding fine frequency offset estimation values are obtained as follows:
Assuming that alpha beta is less than 1, the corrected time domain sequence is sequentially sent to a multiplication accumulator, a multiplier, a phase angle calculation module and the multiplication accumulator to obtain a fine frequency offset estimation value as follows:
[ formula nine)]
Wherein, <math> <mrow> <msub> <mi>Ω</mi> <mi>m</mi> </msub> <mo>=</mo> <mn>3</mn> <mfrac> <mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>-</mo> <mi>m</mi> <mo>)</mo> </mrow> <mrow> <mo>(</mo> <mi>P</mi> <mo>-</mo> <mi>m</mi> <mo>+</mo> <mn>1</mn> <mo>)</mo> </mrow> <mo>-</mo> <mi>M</mi> <mrow> <mo>(</mo> <mi>P</mi> <mo>-</mo> <mi>M</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mi>M</mi> <mrow> <mo>(</mo> <mn>4</mn> <msup> <mi>M</mi> <mn>2</mn> </msup> <mo>-</mo> <mn>6</mn> <mi>PM</mi> <mo>+</mo> <mn>3</mn> <msup> <mi>P</mi> <mn>2</mn> </msup> <mo>-</mo> <mn>1</mn> <mo>)</mo> </mrow> </mrow> </mfrac> <mo>,</mo> <mn>1</mn> <mo>≤</mo> <mi>m</mi> <mo>≤</mo> <mi>M</mi> <mo>;</mo> </mrow> </math> *1＝angle{ρ1}；
and M is P/2. The fine frequency offset estimation algorithm when α β is 1 is a special case of the fine frequency offset estimation algorithm when α β is less than 1; and (4) obtaining the formula eight by changing P in the formula nine to 2.
And finally, sending the estimated coarse frequency offset estimation value and the estimated fine frequency offset estimation value to an adder to obtain a total frequency offset estimation value as follows:
[ equation ten]
According to the above description, the implementation steps of the frequency offset estimation algorithm based on the adjustable time-frequency training sequence can be obtained as follows:
1) carrying out beta-time fast Fourier transform interpolation on the received frequency domain sequence TS 1, and calculating a periodogram thereof according to the interpolation;
2) searching the peak amplitude of the corresponding periodogram by using a bubbling method;
3) determining the peak pilot frequency in the set { i ] according to the predefined lookup tablek}0 K-1The index value of (1);
4) calculating the offset of the found peak frequency domain pilot frequency and normalizing the offset to N, thereby determining a coarse frequency offset estimation value;
5) performing coarse frequency offset correction on the received time domain sequence TS 2;
6) calculating a phase angle rotation component caused by frequency offset for the corrected time domain sequence TS 2 according to P identical subsequences contained in the corrected time domain sequence TS 2;
7) carrying out weighted average and normalization on the phase angle rotation components to obtain corresponding fine frequency offset estimation values;
8) and adding the estimated coarse frequency offset value and the estimated fine frequency offset value to obtain a total frequency offset estimation value.
Where β should be from set {2 }n}0 -log2αIs selected from the set {2 } of-n}1 log2N-1In the selection, N > 0 is the total length of the time-frequency training sequence, and the set { i ^ isk}0 K-1Denotes the index values of K unequally spaced pilots in the frequency domain sequence TS 1, 0 < K □ alpha N.
The interpolation means and the squaring means perform the operation included in the formula [ two ], the peak amplitude searching means performs the formula [ three ], the peak pilot index calculating means performs the formula [ four ], the offset calculating and normalizing means performs the formulas [ five ] and [ six ], the multiplying means performs the coarse frequency offset correcting operation (formula [ seven ]), the two multiplication accumulating means, the multiplying means, and the phase angle calculating means together perform the fine frequency offset estimating operation (formula [ nine ]) when α β is less than 1, and the adding means performs the total frequency offset estimating operation (formula [ ten ]). Wherein, the multiplication accumulation device and the phase angle calculation device finish the fine frequency offset estimation operation (formula [ eight ]) when alpha beta is 1.
Claims (2)
1. A low-complexity frequency offset estimation method based on an adjustable time-frequency training sequence is characterized in that the estimation method comprises the following steps:
1) carrying out beta-time fast Fourier transform interpolation on the received frequency domain sequence TS 1, and calculating a periodogram thereof according to the interpolation;
2) searching the peak amplitude of the corresponding periodogram by using a bubbling method;
3) determining the peak pilot frequency in the set { i ] according to the predefined lookup tablek}0 K-1The index value of (1);
4) calculating the offset of the found peak frequency domain pilot frequency and normalizing the offset to N, thereby determining a coarse frequency offset estimation value;
5) performing coarse frequency offset correction on the received time domain sequence TS 2;
6) calculating a phase angle rotation component caused by frequency offset for the corrected time domain sequence TS 2 according to P identical subsequences contained in the corrected time domain sequence TS 2;
7) carrying out weighted average and normalization on the phase angle rotation components to obtain corresponding fine frequency offset estimation values;
8) and adding the estimated coarse frequency offset value and the estimated fine frequency offset value to obtain a total frequency offset estimation value.
Where β should be from set {2 }n}0 -log2αIs selected from the set {2 } of-n}1 log2N-1In the selection, N > 0 is the total length of the time-frequency training sequence, and the set { i ^ isk}0 K-1Denotes the index values of K unequally spaced pilots in the frequency domain sequence TS 1, 0 < K □ alpha N.
2. The method of claim 1, wherein the adjustable time-frequency training sequence comprises a frequency domain sequence TS 1 with length α N and a time domain sequence TS 2 with length (1- α) N, and the ratio of the two parts can be adjusted, but the total length remains not to be N; to combat inter-symbol interference ISI, the two partial sequences are preceded by an insertion of length NgThe cyclic prefix of (c); the frequency domain sequence TS 1 consists of K pilot frequencies with unequal intervals, and the time domain sequence TS 2 consists of P subsequences with the same length of U; through the selection of parameters, the corresponding frequency offset estimator can obtain different complexity performance tradeoffs, and therefore the frequency offset estimator can be applied to different wireless mobile scenes. Wherein N isgShould be larger than the maximum delay spread of the wireless multipath channel, PU ═ 1- α) N.
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| CNB2005100384958A CN100486238C (en) | 2005-03-21 | 2005-03-21 | Method of low-complexity frequency deviation estimation based on adjustable time frequency training sequence |
| KR1020050123520A KR100754840B1 (en) | 2005-03-21 | 2005-12-14 | Method for Frequency Synchronization of Mobile Telecommunication System Using OFDM |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101312446B (en) * | 2008-07-07 | 2010-10-20 | 苏州中科半导体集成技术研发中心有限公司 | Phase tracking compensation process based on weighting pilot |
| US7830990B2 (en) | 2007-04-02 | 2010-11-09 | Industrial Technology Research Institute | Method for estimating and compensating frequency offset and frequency offset estimation module |
| CN101043231B (en) * | 2007-04-18 | 2010-11-10 | 华为技术有限公司 | Method, equipment and system for realizing deviation correction to access channel leading signal |
| CN102098245A (en) * | 2011-03-24 | 2011-06-15 | 东南大学 | Frequency offset estimation method of low-complexity collaborative relay system |
| CN101184075B (en) * | 2007-12-13 | 2012-01-04 | 华为技术有限公司 | Frequency deviation compensation method and device |
| CN101394391B (en) * | 2008-11-03 | 2012-11-21 | 华北电力大学 | OFDM synchronization method based on four dimensional chaos system |
| CN101473618B (en) * | 2006-06-20 | 2012-12-05 | Nxp股份有限公司 | Method and equipment for estimating carrier frequency offset |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6097776A (en) | 1998-02-12 | 2000-08-01 | Cirrus Logic, Inc. | Maximum likelihood estimation of symbol offset |
| US6807241B1 (en) | 1999-09-15 | 2004-10-19 | Lucent Technologies Inc. | Method and apparatus for partial and course frequency offset estimation in a digital audio broadcasting (DAB) system |
| KR100483020B1 (en) * | 2002-11-12 | 2005-04-15 | 한국전자통신연구원 | A configuration method of frame for reverse random access in an orthogonal frequency division multiple access system |
| US7133479B2 (en) | 2003-04-15 | 2006-11-07 | Silicon Integrated Systems Corp. | Frequency synchronization apparatus and method for OFDM systems |
| KR100626644B1 (en) * | 2004-12-14 | 2006-09-21 | 한국전자통신연구원 | Method for estimating frequency/time offset and its using apparatus in OFDM communication system |
-
2005
- 2005-03-21 CN CNB2005100384958A patent/CN100486238C/en not_active Expired - Fee Related
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101473618B (en) * | 2006-06-20 | 2012-12-05 | Nxp股份有限公司 | Method and equipment for estimating carrier frequency offset |
| US7830990B2 (en) | 2007-04-02 | 2010-11-09 | Industrial Technology Research Institute | Method for estimating and compensating frequency offset and frequency offset estimation module |
| CN101043231B (en) * | 2007-04-18 | 2010-11-10 | 华为技术有限公司 | Method, equipment and system for realizing deviation correction to access channel leading signal |
| CN101184075B (en) * | 2007-12-13 | 2012-01-04 | 华为技术有限公司 | Frequency deviation compensation method and device |
| US8483159B2 (en) | 2007-12-13 | 2013-07-09 | Huawei Technologies Co., Ltd. | Method and apparatus for frequency offset compensation |
| CN101312446B (en) * | 2008-07-07 | 2010-10-20 | 苏州中科半导体集成技术研发中心有限公司 | Phase tracking compensation process based on weighting pilot |
| CN101394391B (en) * | 2008-11-03 | 2012-11-21 | 华北电力大学 | OFDM synchronization method based on four dimensional chaos system |
| CN102098245A (en) * | 2011-03-24 | 2011-06-15 | 东南大学 | Frequency offset estimation method of low-complexity collaborative relay system |
| CN102098245B (en) * | 2011-03-24 | 2013-04-24 | 东南大学 | Frequency offset estimation method of low-complexity collaborative relay system |
Also Published As
| Publication number | Publication date |
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| CN100486238C (en) | 2009-05-06 |
| KR100754840B1 (en) | 2007-09-04 |
| KR20060101850A (en) | 2006-09-26 |
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