CN106330806A - Fine frequency deviation estimation algorithm and fine frequency deviation estimation system based on cyclic prefix and long training sequence field - Google Patents

Abstract

The invention provides a fine frequency deviation estimation algorithm and a fine frequency deviation estimation system based on a cyclic prefix and long training sequence field. The fine frequency deviation estimation method comprises steps that timing synchronization of received frame data is carried out, and the frame data is located to the 17th data sampling point of the long training sequence field; the 64 data sampling points are delayed, and the autocorrelation values of the 80 sampling points are calculated sequentially from the 17th sampling point; the autocorrelation values of the calculated 80 sampling points are accumulated; frequency deviation values are estimated by using a accumulated sum. Problems such as low precision of fine frequency deviation estimation caused by only using the cyclic prefix and multipath time delay easily interfered by other symbols are overcome, and the DFT calculation quantity of the training sequence is reduced, and at the same time, errors are reduced to a certain extent, and estimation precision is further improved.

Description

Based on Cyclic Prefix and the thin frequency excursion algorithm of long training sequence field and system

Technical field

The present invention relates to wireless mobile communications transmission field, more particularly, to one based on Cyclic Prefix and long training The thin frequency excursion algorithm of sequence field and system.

Background technology

Since the eighties in 20th century, orthogonal frequency division multiplexi (OFDM, Orthogonal Frequency Division Multiplexing) technology development more and more ripe, will be widely applied in multiple fields.Such as non- Symmetric digital subscriber line, WLL, digital audio broadcasting, high-definition television and WLAN have extensively Application.Along with people are to communication data, broadband, the individualized and enhancing of mobile demand, more research worker collection In increasing energy OFDM technology application in mobile communication system is researched and developed.

Why OFDM so can be widely applied in each field of information transmission, is based primarily upon its spectrum efficiency High, bandwidth expansion strong, anti-multipath fading, frequency spectrum resource flexible allocation and be easily achieved multi-antenna technology, a but OFDM symbol Number being made up of multiple orthogonal sub-carriers, the orthogonality of its subcarrier is affected very big by frequency spectrum deviation, this quickest to frequency departure Perception is one shortcoming the biggest of OFDM technology, therefore how to eliminate frequency deviation and the impact of system is just seemed most important.

OFDM multicarrier system has many good qualities such as: can reduce the intersymbol brought due to the temporal dispersion of wireless channel Interference, can utilize frequency spectrum resource to greatest extent, and this is a biggest advantage in the most nervous communication system of frequency spectrum resource, Support to realize different transfer rates in different subchannels, can be combined with plurality of access modes, form OFDM system System etc..But shortcoming is also it will be apparent that owing to an OFDM symbol is comprised of a plurality of orthogonal subcarriers, it is to frequency departure Impact is also very sensitive, and often has higher papr, the frequency spectrum of signal can be made to produce change, destroy son The orthogonality of carrier wave, causes the biggest impact to the performance of system.

Frequency deviation is typically caused by three below reason:

In reality, the crystal oscillator frequency producing carrier wave of transmitter and receiver can not be completely the same, and this may result in transmitting There is certain deviation in the carrier frequency for modulation and demodulation of machine and receiver, broken sub-carriers orthogonality, and to phase place Impact also have additive, cause serious impact to system.

Transmitter is directly frequently not static with receiver, but there is relative velocity, and this results in Doppler frequency shift, Produce frequency deviation.

The crystal oscillator of the digital to analog converter of transmitter and the analog-digital converter of receiver can not have identical sample frequency, This causes the sampling interval of signal to produce deviation, and deviation runs up to certain degree and can produce serious influence system.

Subcarrier frequency deviation frequency departure is divided into integer frequency offset and fractional part of frequency offset, and integer frequency offset refers to system and produces Frequency deviation value more than subcarrier spacing, this kind of frequency deviation is accomplished by utilizing thick frequency deviation both integer frequency offset value algorithm for estimating Estimating, fractional part of frequency offset refers to the less of the value generation of frequency deviation, typically within the scope of a subcarrier spacing, little Several times frequency offset algorithm estimation range is little but precision is higher, and the frequency deviation in system estimates that being often combined both in compensating is carried out jointly Frequency deviation is estimated.Fractional part of frequency offset can cause the orthogonality between subcarrier, and integer frequency offset then can cause the OFDM letter received Number the cyclic shift of sequence of symhols and phase place rotate.Frequency deviation is estimated can be divided on the frequency excursion algorithm in time domain and frequency domain Frequency deviation estimates algorithm for estimating, and carrier wave frequency deviation can have a strong impact on the communication performance of wireless communication system, causes service disruption to make signal Can not normal transmission.The frequency deviation value produced is referred to as fractional part of frequency offset less than the frequency deviation of subcarrier spacing, and fractional part of frequency offset algorithm is estimated Meter scope is little but precision is higher, it is contemplated that generally frequency deviation value is little, therefore the present invention mainly discusses thin frequency deviation.

And, only with Cyclic Prefix carry out frequency deviation estimate to be easily subject to multipath to affect precision relatively low, combined cycle prefix The contaminated problem of Cyclic Prefix and more traditional the algorithm for estimating utilizing long training sequence field can be overcome with long training sequence There is higher precision.As it is shown in figure 1, the data frame structure of 802.11a comprises leading code domain, signaling field, service field sum According to field and afterbody and filling.Lead code comprises short training sequence (STF, Short Train Field), long training sequence (LTF, Long Train Field) and signaling field.Short training sequence is ten sections of symbols repeated, and long training sequence comprises and follows Ring prefix, long training sequence field 1 and long training sequence field 2.Long training sequence 1 and sequence 2 are repetitive sequence field. 802.11a agreement one OFDM symbol of regulation has 64 data sampled points, and long training sequence has 160 data sampled points, Cyclic Prefix has 32, and long training field 1 and field 2 are respectively 64.The present invention is exactly to utilize the circulation of long training sequence Mutual relation between prefix and training sequence field 1, sequence field 2 three completes thin frequency deviation and synchronizes；The Frame of 802.11n Structure contains the legacy preamble code that 802.11a data frame structure is identical.

Summary of the invention

The present invention provides a kind of based on Cyclic Prefix with the thin frequency excursion algorithm of long training sequence field, and this algorithm can carry The Frequency Synchronization precision of high existing wireless communications system.

A further object of the present invention is to provide a kind of thin frequency deviation based on Cyclic Prefix and long training sequence field to estimate System.

In order to reach above-mentioned technique effect, technical scheme is as follows:

A kind of based on Cyclic Prefix with the thin frequency excursion algorithm of long training sequence field, comprise the following steps:

S1: the frame data received are timed synchronization, navigates to the 17th data sampled point of long training sequence field；

64 data sampled points of S2: time delay, from the 17th autocorrelation value using point to start to carry out successively 80 sampled points Calculate；

S3: the autocorrelation value of calculate 80 sampled points is added up；

S4: utilize cumulative sum, estimate frequency deviation value.

Further, the detailed process of described step S1-S2 is as follows:

The symbol initial time point of the lead code long training sequence field of the frame data received is navigated to by Symbol Timing, Time delay between the replicator that Cyclic Prefix is corresponding with long training sequence 1 is 64 sampled points and long training sequence 1 and long instruction The time delay practiced between the replicator of sequence 2 correspondence is also 64 data sampled point length, from the 17th data of long training sequence Sampled point start with 64 sampled points of time delay after data point carry out time delay auto-correlation, carry out the most successively the time delay of 80 from Correlation computations.

Preferably, described step S4 being estimated, the algorithm of frequency deviation value uses Coordinate Rotation Digital computational algorithm.

A kind of based on Cyclic Prefix with the thin frequency deviation estimation system of long training sequence field, including:

Time delay autocorrelation calculation module, is made up of a FIFO and multiplier, and FIFO is by static random access memory cell structure Becoming, use as data buffer, the degree of depth is set to 64, completes the delay operation of 64 point data；First FIFO is initialized Being 0, it is the FIFO of 64 that current data enters the degree of depth, after time delay 64 point data, current data and delay data synchronism output is arrived Multiplier carries out complex multiplication operation, it is ensured that the synchronism output of long training sequence same position, it is achieved that the autocorrelative meter of time delay Calculate function；

Autocorrelation value accumulator module, is made up of an adder and depositor, and first depositor carries out 0 value initialization, The autocorrelation value of time delay auto-correlation module output is input simultaneously in adder be added with currency temporary in depositor, The result that will add up is kept in depositor, until 80 time delay autocorrelation value have added up, accumulation result is input to frequency deviation Estimation module；

Frequency deviation estimating modules, uses Coordinate Rotation Digital computational algorithm that accumulation result is carried out arctan function calculating, enters And complete that frequency deviation value is carried out estimation and calculate.

Further, described auto-correlation module uses fifo queue, it is achieved the synchronization of long training sequence correspondence position Output, and then carry out the autocorrelation calculation of corresponding sampled point.

Compared with prior art, technical solution of the present invention provides the benefit that:

The present invention is timed synchronization to the frame data received, and navigates to the 17th data sampling of long training sequence field Point；64 data sampled points of time delay, calculate from the 17th autocorrelation value using point to start to carry out successively 80 sampled points；Will meter The autocorrelation value of 80 sampled points calculated adds up；Utilize cumulative sum, estimate frequency deviation value；Overcome and only use circulation It is low that prefix carries out thin frequency offset estimation accuracy, owing to multidiameter delay is easily carried out the problem disturbed by other symbols, and decreases instruction Practice sequence and carry out the amount of calculation of DFT, also reduce error to a certain extent simultaneously, further improve estimated accuracy.

Accompanying drawing explanation

Fig. 1 is the structure chart of frame data of 802.11a；

Fig. 2 is inventive algorithm flow chart；

Fig. 3 is present system structure chart；

Fig. 4 is that signal sends and receives schematic diagram.

Detailed description of the invention

Accompanying drawing being merely cited for property explanation, it is impossible to be interpreted as the restriction to this patent；

In order to the present embodiment is more preferably described, some parts of accompanying drawing have omission, zoom in or out, and do not represent actual product Size；

To those skilled in the art, in accompanying drawing, some known features and explanation thereof may be omitted is to be appreciated that 's.

With embodiment, technical scheme is described further below in conjunction with the accompanying drawings.

Embodiment 1

If source signal is through a series of process of transmitting terminal, forming signal x (t), signal x (t), after up-conversion, is sent out The complex baseband signal that machine of penetrating is launched is:

$y_t\left(t\right)=x\left(t\right)e^{j2{\mathrm{\πf}}_{t}t}+n\left(t\right)---\left(1\right)$

Ft represents transmission carrier frequency.Owing to the sampling period of transmitter with receiver there are differences, if the connecing of receiver Recording wave frequency is fr, and the complex baseband signal that signal receives after down coversion is:

$y_r\left(t\right)=x\left(t\right)e^{j2\mathrm{\π}(f_t-f_r)t}+w\left(t\right)---\left(2\right)$

W (t) represents Gaussian noise, because can only process digital signal in communication system modules, down-conversion signal is again Through analog digital conversion, obtain receiving the discrete expression of signal:

$y_n=x_n{e}^{j2{\mathrm{\πf}}_{\mathrm{\Δ}}{\mathrm{nT}}_s}+w\left(n\right)---\left(3\right)$

F Δ represents that signal through channel, then is carried out after analog digital conversion relative to launching the frequency deviation value that signal produces, to formula (3) the frequency deviation estimated value in is normalized:

$y_n=x_n{e}^{j2\mathrm{\π\ϵ\Δfn}{T}_s}+w\left(n\right)---\left(4\right)$

F Δ=ε × Δ f, ε are normalization frequency deviation, and Δ f is subcarrier spacing, according to IEEE 802.11n WLAN PHY layer Standard, arranges Δ f=312.5KHz, and Ts=0.05us is the sampling period, N=64, then formula (4) can abbreviation following formula further:

$y_n=x_n{e}^{\frac{j2\mathrm{\π}n}{N}\mathrm{\ϵ}}+w\left(n\right)---\left(5\right)$

The step of inventive algorithm is as follows:

The symbol initial time point of lead code long training sequence field is navigated to, it is assumed that Cyclic Prefix by Symbol Timing 17th point is corresponding to moment d, and the time delay between the replicator that Cyclic Prefix is corresponding with long training sequence 1 is D=64 and adopts Time delay between the replicator of sampling point and long training sequence 1 and long training sequence 2 correspondence is also 64 data sampled point length. Therefore from the 17th data sampled point of long training sequence start with 64 sampled points of time delay after data point carry out time delay auto-correlation, press Order carries out the time delay autocorrelation calculation of 80 successively.

$Y_n=y_n{y}_{n+D}^{*}---\left(6\right)$

Calculate this time delay auto-correlation of 80 and:

$Y=\underset{n=d}{\overset{d+79}{\Σ}}{Y}_n---\left(7\right)$

Formula (5) is substituted into formula (7) obtain:

$\begin{array}{c}Y=\underset{n=d}{\overset{d+79}{\Σ}}\left(x\right(n)e^{j\frac{2\mathrm{\π}n}{N}\mathrm{\ϵ}}+w(n\left)\right){\left(x\right(n+D)e^{j\frac{2\mathrm{\π}(n+D)}{N}\mathrm{\ϵ}}+w(n+D\left)\right)}^{*}\\ =\underset{n=d}{\overset{d+79}{\Σ}}\left[\begin{array}{c}x\left(n\right)x{(n+D)}^{*}{e}^{j\frac{2\mathrm{\π}D}{N}\mathrm{\ϵ}}+x\left(n\right)w{\left(n+D\right)}^{*}{e}^{j\frac{2\mathrm{\π}n}{N}\mathrm{\ϵ}}+\\ x{\left(n+D\right)}^{*}w\left(n\right)e^{-j\frac{2\mathrm{\π}(n+D)}{N}}+w\left(n\right)w{\left(n+D\right)}^{*}\end{array}\right]\end{array}---\left(8\right)$

Because signal and Gaussian noise are incoherent, be also incoherent between Gaussian noise signal, thus signal with make an uproar The cross-correlation function of sound is equal to zero, and the auto-correlation function between Gaussian noise is also zero, therefore Y can be write as:

$Y=\underset{n=d}{\overset{d+79}{\Σ}}x\left(n\right)x{(n+D)}^{*}{e}^{j\frac{2\mathrm{\π}D}{N}\mathrm{\ϵ}}---\left(9\right)$

Formula (10) is utilized to estimate thin frequency deviation:

$\mathrm{\ϵ}=-\frac{1}{2\mathrm{\π}}arctan\left(\frac{\mathrm{Im}\left(Y\right)}{\mathrm{Re}\left(Y\right)}\right)---\left(10\right)$

Accompanying drawing 4 is the structure chart of present system, and this hardware configuration is made up of three modules, is time delay auto-correlation meter respectively Calculate module, autocorrelation value accumulator module and frequency deviation estimating modules.Time delay autocorrelation calculation module is by a FIFO and multiplier group Become.FIFO is made up of static random access memory cell, uses as data buffer, and the degree of depth is set to 64, can complete 64 point data Delay operation.First FIFO is initialized as 0, and it is the FIFO of 64 that current data enters the degree of depth, after time delay 64 point data, Current data and delay data synchronism output are carried out complex multiplication operation to multiplier, thus can guarantee that long training sequence is same The synchronism output of one position, it is achieved that the autocorrelative computing function of time delay.

Autocorrelation value accumulator module is made up of an adder and depositor, is the most also that depositor is carried out 0 value is initial Changing, the currency kept in autocorrelation value and the depositor of time delay auto-correlation module output is input simultaneously in adder carry out phase Adding, the result that will add up is kept in depositor, until 80 time delay autocorrelation value have added up, by defeated for final accumulation result Enter to frequency deviation estimating modules.

The essence being understood estimation frequency deviation value by formula (10) is to calculate arctan function.Frequency deviation estimating modules uses CORDIC to calculate Method calculates arctan function, and then estimates frequency deviation value.Cordic algorithm, also known as Coordinate Rotation Digital computational algorithm, utilizes The thought of two way classification, by changing the ordinate value of coordinate points, obtaining final cumulative angle value is i.e. estimated arc tangent Value.Concrete principle is as follows:

Obtain by formula (9) that the auto-correlation of 80 is cumulative and Y, Y be plural, using the imaginary values of Y as the vertical seat of rectangular coordinate Punctuate, value of real part is as abscissa point.The angle value of the arc tangent that summary is estimated is φ.By vector D (Im (Y), Re (Y)) up time Pin rotates θ (k=0)=45 degree, checks the ordinate value of new coordinate after rotating, if the value of vertical coordinate is more than zero, illustrates that φ is more than 45 degree, continue according to clockwise vector D being rotated θ (k) degree.If the value of vertical coordinate is less than zero, illustrate that φ, less than 45 degree, continues Continuous according to counterclockwise vector D being rotated θ (k) degree.The angle the most every time rotated all follows | tan [θ (k)] |=2-k, its Middle k=1,2 ....Angle value corresponding for 2-k can pass through look-up tables'implementation, and adding absolute value is that to represent that angle can take positive and negative, i.e. Correspondence is clockwise or counterclockwise.Rotating for kth time, computational methods are as follows:

(a+bi) (cos [θ (k)]+sin [θ (k)] i)=cos [θ (k)] × [a tan [θ (k)] b+i × (tan [θ (k)] a +b)]

Wherein, cos [θ (k)] also can be preserved by LUT Method.Above-mentioned rotation make the value of vertical coordinate constantly close to 0, actual In, as long as the value of vertical coordinate is less than some accuracy value.Being added up by the angle value of multiple rotary, accumulated result is i.e. It it is the angle value of arctan function to be calculated.Obviously, cordic algorithm can calculate by the way of displacement and plus-minus Arc-tangent value, it is to avoid complicated multiplying.

The corresponding same or analogous parts of same or analogous label；

Described in accompanying drawing, position relationship is used for the explanation of being merely cited for property, it is impossible to be interpreted as the restriction to this patent；

Obviously, the above embodiment of the present invention is only for clearly demonstrating example of the present invention, and is not right The restriction of embodiments of the present invention.For those of ordinary skill in the field, the most also may be used To make other changes in different forms.Here without also cannot all of embodiment be given exhaustive.All at this Any amendment, equivalent and the improvement etc. made within the spirit of invention and principle, should be included in the claims in the present invention Protection domain within.

Claims (5)

1. one kind based on Cyclic Prefix and the thin frequency excursion algorithm of long training sequence field, it is characterised in that include following step Rapid:

S1: the frame data received are timed synchronization, navigates to the 17th data sampled point of long training sequence field；

64 data sampled points of S2: time delay, calculate from the 17th autocorrelation value using point to start to carry out successively 80 sampled points；

S3: the autocorrelation value of calculate 80 sampled points is added up；

S4: utilize cumulative sum, estimate frequency deviation value.

The most according to claim 1 based on Cyclic Prefix with the thin frequency excursion algorithm of long training sequence field, its feature Being, the detailed process of described step S1-S2 is as follows:

The symbol initial time point of the lead code long training sequence field of the frame data received is navigated to, circulation by Symbol Timing Time delay between the replicator that prefix is corresponding with long training sequence 1 is 64 sampled points and long training sequence 1 and long training sequence Time delay between the replicator of row 2 correspondence is also 64 data sampled point length, from the 17th data sampling of long training sequence Data point after some beginning and 64 sampled points of time delay carries out time delay auto-correlation, carries out the time delay auto-correlation of 80 the most successively Calculate.

The most according to claim 3 based on Cyclic Prefix with the thin frequency excursion algorithm of long training sequence field, its feature It is, described step S4 being estimated, the algorithm of frequency deviation value uses Coordinate Rotation Digital computational algorithm.

4. one kind utilizes thin frequency excursion algorithm based on Cyclic Prefix and long training sequence field as claimed in claim 3 System, it is characterised in that including:

Time delay autocorrelation calculation module, is made up of a FIFO and multiplier, and FIFO is made up of static random access memory cell, makees Using for data buffer, the degree of depth is set to 64, completes the delay operation of 64 point data；First FIFO is initialized as 0, when It is the FIFO of 64 that front data enter the degree of depth, after time delay 64 point data, by current data and delay data synchronism output to multiplier Carry out complex multiplication operation, it is ensured that the synchronism output of long training sequence same position, it is achieved that the autocorrelative computing function of time delay；

Autocorrelation value accumulator module, is made up of an adder and depositor, and first depositor carries out 0 value initialization, time delay The autocorrelation value of auto-correlation module output is input simultaneously in adder be added, by phase with currency temporary in depositor The result added is kept in depositor, until 80 time delay autocorrelation value have added up, accumulation result is input to frequency deviation and estimates Module；

Frequency deviation estimating modules, uses Coordinate Rotation Digital computational algorithm that accumulation result is carried out arctan function calculating, and then complete Paired frequency deviation value carries out estimation and calculates.

The most according to claim 4 based on Cyclic Prefix with the thin frequency deviation estimation system of long training sequence field, its feature Being, described auto-correlation module uses fifo queue, it is achieved the synchronism output of long training sequence correspondence position, and then carries out The autocorrelation calculation of corresponding sampled point.