CN105162745A - Short training field design method used for wireless local area network communication system - Google Patents
Short training field design method used for wireless local area network communication system Download PDFInfo
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Abstract
The invention discloses a short training sequence design method used for a wireless local area network communication system. First, related parameters of a field to be designed are determined. Then multiple times of iteration are performed. In one time of iteration, fields, which are the sums of a plurality of elements obeying a Bernoulli distribution of predetermined probability density parameters, of determined lengths and configuration, are generated according to the parameters, and the generated fields are screened according to SELF of the fields and parameters for next iteration are updated. Finally, after the iteration is ended, the fields with good self-relevance and periodically repeated time domains are set as the designed short training fields. According to the invention, short training fields of any lengths can be designed. The fields only contains elements of (1+i), -(1+i) and 0 and has good self-relevance and periodically repeated time domains and wave shapes. According to the invention, on the condition that specific values are assigned to specific positions of the fields, the fields with good wave shapes can also be obtained, so that application scene and application range are increased further. The invention can be applied but is no limited to the design of short training fields for OFDM systems.
Description
Technical Field
The invention belongs to the technical field of wireless communication, and particularly relates to a Short Training Field (STF) design method of a wireless local area network communication system.
Background
A typical physical layer transmission mode of a wireless lan communication system is as follows: the short training Sequence (STF) is used for frame detection, Automatic Gain Control (AGC), coarse frequency synchronization, coarse time synchronization, etc. of the wireless local area network communication system; the STF is followed by a long training sequence (LTF) for channel estimation and more accurate frequency offset estimation and time synchronization; the LTF is followed by a signaling field containing rate and length information of the communication packet; followed by a data field.
Compared with a single carrier system, in the OFDM system, all subcarriers added after IFFT (inverse fast fourier transform) operation result in a high peak value of a time-domain transmission signal. In fact, a high PAPR reduces both the efficiency of the transmitter power amplifier and the signal to quantization noise ratio (SQNR) of the digital-to-analog converter (ADC) and the analog-to-digital converter (DAC), so it is one of the most unfavorable factors in an orthogonal frequency division multiple access (OFDM) system. In addition, the subcarriers in the OFDM system are completely orthogonal to each other, and the system output is parallel-to-serial conversion of the parallel data of a plurality of subcarriers, which results in some disadvantages of the OFDM system, mainly manifested by sensitivity to synchronization offset and high PAPR of the time domain signal. The OFDM technique modulates data onto each subcarrier at a transmitting end using IFFT transform, and demodulates data from the subcarriers at a receiving end using corresponding FFT transform, and a starting point of each OFDM symbol must be known for FFT transform, and accurate timing synchronization is required. And because the frequency spectrum of the sub-carriers of the OFDM system is overlapped, strict orthogonality needs to be kept between the sub-carriers, and once frequency deviation exists, the orthogonality is destroyed, so that inter-carrier interference occurs.
Automatic gain detection is also an important part in a wireless local area network communication system, and due to fading of electromagnetic waves transmitted in space, the power of signals received at a receiving end fluctuates along with the change of channel environment. The receiving end needs to adjust the signal power amplifier configuration of the receiving end through an automatic gain control mechanism. Automatic gain control generally comprises the following steps: coarse gain control, fine gain control, gain setting time period and gain adjusted dc offset estimation. In order to realize automatic gain control, coarse time-frequency synchronization, etc., the time-domain waveform of the STF is generally periodic, and the amplitude variation of the time-domain signal is within a certain range.
For the above reasons, a short training sequence is often desired to have good time-domain autocorrelation characteristics and a smooth time-domain waveform. Based on the requirements, the invention provides a design method of the STF sequence, which has flexible configuration and is suitable for communication systems limited by various specific conditions.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the problems in the prior art, the invention provides a short training Sequence (STF) design method for an OFDM wireless local area network communication system, which requires that elements in the sequence contain 1+ i, - (1+ i) or 0, and has the advantages of simple realization and flexible application.
For better understanding of the present invention, the related technical background related to the technical solution of the present invention is first introduced: in an OFDM system, a high rate data stream is divided into N low rate data streams for simultaneous transmission by subcarriers. Each subcarrier is independently modulated with a typical modulation scheme (e.g., PSK or QAM). Beta ═ X for one OFDM symbol0,…,XN-1]TWhere N is the number of subcarriers, the corresponding time-domain baseband signal can be expressed as:
Where L is the oversampling factor.
The autocorrelation function of the time domain sequence is defined as follows:
rx(n)(k)＝E{x(n+k)x*(n) } (equation 2)
Wherein x (n) represents time domain signal, E { } is statistical average operator, x*And (n) is the conjugate transpose of x (n). In order to examine the quality of the autocorrelation characteristic of the time domain waveform of the sequence, the following autocorrelation characteristic measures are defined:
Wherein E { } is a statistical average operator, max { } represents taking the maximum value, and a larger SELF means a better correlation property.
A randomly generated sequence cannot guarantee good autocorrelation characteristics and time-domain waveform shapes, and the signals are clipped or compressed by an excessive analog front end in transmission, so that the characteristics of the sequence are distorted.
In the present optimal design method, each element of the initial sequence can be regarded as a random variable, and obeys a certain probability distribution, such as bernoulli distribution, and the probability distribution function is as follows:
(formula 4)
Wherein p is a random variable and u is a probability distribution parameter. N elements of the sequence were generated by N independent bernoulli experiments, each element obeying the probability distribution function as above. Each test consists of distribution parametersAnd u is a parameter vector. u. ofnRepresenting the probability that the nth element in the sequence is 1, 1-unIndicating the probability that the nth element in the sequence is 0. Since each element of the sequence is generated independently, the probability of a particular sequence being generated is:
In order to ensure that the time domain waveform has a periodic repetition characteristic, the following conditions need to be satisfied according to the up-down sampling law and definition of DFT:
first, assuming that the time domain waveform period repeats M times within one DFT symbol time, it is required that M, N satisfy nmmod M0.
Second, the frequency domain signal is x (n). X (n) satisfies:
The technical scheme is as follows: a short training sequence design method for wireless local area network communication system, the elements of the good autocorrelation characteristic, the periodic repetitive sequence of the time domain waveform have 1+ i, - (1+ i) and 0, the method is as follows: firstly, setting related parameters of a designed sequence, then carrying out multiple iterations until the related parameters meet termination conditions, generating sequences with specified lengths and configurations of 0 and 1 of multiple elements of Bernoulli distribution obeying specified probability density parameters in one iteration according to the parameters, screening the generated sequences according to SELF of the sequences, updating parameters of the next iteration based on the screened sequences, and finally mapping a random sequence corresponding to a SELF maximum value to obtain a sequence with 1+ i, - (1+ i) and 0 low SELF after the iteration is terminated. The method specifically comprises the following steps:
step 1: setting parameters of the designed sequence, including: the sequence length N (namely the sequence is subjected to N-point DFT conversion), the repetition frequency M of the sequence time domain waveform in one DFT period, the number J of random sequences generated each time, the sampling coefficient S, 0 < S < 1, and the initial probability density function parameter(i.e., the probability density function parameter calculated for the first iteration), the iteration termination condition: number of iterations T or convergence condition threshold, and initial SELF value
Further, if there is a need to have conditional restrictions on the designed sequence, for example, there are often dc subcarriers in OFDM communications, reserved subcarriers, and carriers forced to be zeroed for satisfying the periodicity of the signal time domain, the designed sequence needs to be a specific value at some positions, and then, in step 1, a restriction condition parameter may also be set: the positions of the restricted location field C and the restricted location value W, such as the dc subcarrier, the reserved subcarrier, and the carrier that is forced to be zeroed for obtaining the time domain periodicity are the restricted location field C, and the values of these positions are usually set to 0, that is, the restricted location value W is 0.
Step 2: using the Monte Carlo method to generate J obedient parameters asBernoulli-distributed random sequences, the J sequences generated can be represented as follows:
In the case where the constraint parameter is set in step 1, a constraint is applied to the generated sequence, and the sequence can be expressed as follows:
Wherein C is a limiting position domain, wnE W is the value of the constraint location element.
And step 3: computationally generated random sequence Pj∈{0,1}NMapping sequence Q ofj∈{-(1+i)，1+i}NThe SELF of (3), the specific steps are:
step 3.1: as the non-zero value elements of the sequence required to be designed by the invention are 1+ i and- (1+ i), and the values of the random variable of the Bernoulli model are 0 and 1, the mapping is required, and the mapping function can be Qj＝(1-2Pj)·(1+i)，Pj、QjAnd 1 are N-dimensional vectors;
step 3.2: for mapping sequence QjPerforming IFFT to transform the signals into time domain signals;
step 3.3: calculating SELF of the time domain signal, wherein the specific calculation formula is as follows:
(formula 9) wherein x ((1-2P)j) (1+ i)) represents the time domain signal of the mapped sequence,an autocorrelation function representing the time domain signal, obtained by equation 9Is marked asj＝1,…,J。
And 4, step 4: the highest SELF value is selected from J SELFs and recorded asAnd setting a threshold gamma of SELF, wherein the threshold is used for screening sequences participating in updating iterative parameter calculation, and the specific steps comprise:
step 4.1: to pairJ — 1, …, J, sort in descending order, i.e.:
(formula 10)
Wherein down () is a function of sorting the sequences in descending order;
step 4.2: selecting the highest SELF value obtained this time as
Step 4.3: setting SELF threshold as:
(formula 11)
Wherein,is an rounding-up function.
And 5: judging whether iteration termination conditions are met, if so, going to step 7, otherwise, going to step 6; two termination conditions can be set, namely, the termination can be stopped when the iteration is carried out for the preset times, and the termination can be stopped when the iteration reaches the preset threshold. Under the condition of setting the iteration times, the termination condition is that the iteration times are reached; in the case of setting the convergence condition threshold, the termination condition is that the absolute value of the difference between the highest SELF values of the two iteration generated sequences before and after is less than a certain threshold, which can be expressed as follows:
Step 6: according to the result obtained in step 4And gamma updating the iterative parametersAndturning to the step 2 to enter the next iteration, and concretely, turning to the stepIs transmitted toUpdatingNamely, it isAnd updating u according to the value distribution condition of the nth bit of all sequences meeting the SELF threshold conditionn，The updated calculation formula is as follows:
(formula 13)
Where α () is an indication function: if and only ifIf so, equal to 1, otherwise, equal to 0; pjFor the j-th sequence generated at a time, Pj,nFor the value of the nth element of the jth sequence produced, the bernoulli parameter updated this time is taken as the parameter for the next iteration to generate a random sequence:
(formula 14)
And 7: the mapping sequence corresponding to the highest SELF value obtained in step 4 is a designed sequence, that is, a random sequence corresponding to the maximum value of SELF obtained in step 4The mapping is Q e { - (1+ i), 1+ i }NObtained byFor the designed sequence, the mapping function is Qj＝(1-2Pj)·(1+i)。
Has the advantages that: compared with the prior art, the invention has the following advantages: first, the elements of the sequence of the present invention have the same modulus value and only two phases, and the sequence elements are composed of 1+ i, - (1+ i) and 0, which is easy to implement at both the transmitting end and the receiving end. Secondly, the length of the sequence can be set through a parameter N, the length of the sequence is controllable, the limitation of the gray sequence on the length of the sequence is overcome, and the method is very flexible in application. The invention can also design the sequence of the restriction condition, the value of the element on some positions of the fixed sequence; the global optimization can still be carried out under the conditions that a plurality of limitations such as direct current carriers, reserved subcarriers and the like exist, and zero subcarriers are forced to be set under the condition that the periodicity of a time domain waveform of the sequence is met, so that the sequence with good autocorrelation characteristics can be designed. Thirdly, the designed sequences have low PAPR through actual measurement, which is a very important advantage in related applications of the OFDM communication system.
Drawings
FIG. 1 is a general flow diagram of the process of the present invention;
FIG. 2 is a graph of the highest SELF value for a sequence generated each time for a sequence of 256 bits, trained 70 times, using the algorithm of the present invention;
FIG. 3 is a time domain waveform of the generated sequence of the present invention over one DFT period;
fig. 4 is a time domain autocorrelation diagram of the generated sequence of the present invention.
Detailed Description
The present invention is further illustrated by the following figures and specific examples, which are to be understood as illustrative only and not as limiting the scope of the invention, which is to be given the full breadth of the appended claims and any and all equivalent modifications thereof which may occur to those skilled in the art upon reading the present specification.
In the communication scene of the millimeter wave wireless local area network, design parameters are determined by taking an IEEE802.11aj protocol architecture as a reference. In consideration of the scene, the implementation directly sets the training iteration number T to 70, does not perform convergence judgment successively, and visually displays the convergence process by drawing a curve graph. The sequence length N is 256, the number of sequences generated in each iteration is J is 200, and the STF time domain waveform is required to satisfy M-4 repetitions of the waveform according to the constraint conditions of ieee802.11aj direct current subcarriers and virtual subcarriers.
As shown in fig. 1, the present invention provides a STF sequence design method for a wireless local area network communication system, which comprises the following specific steps:
(1) setting parameters of the designed sequence: the length of the sequence is designed to be 256, the training time T is 70, the number of sequences J generated each time is 200, the sampling coefficient S is 0.2, and the initialized Bernoulli parameter is as follows:initial SELF valueThe restricted location field when applied in this scenario can be expressed as: c (-128, -90) — 1, +1 $ (90, +127), where (-128, -90 $ (90, +127) is the position of the reserved subcarrier and is set to 0, and (-1,1) is the position of the three dc subcarriers and is set to 0. Meanwhile, in order to satisfy the STF time-domain waveform M being 4 waveform repetitions, the sequence should also satisfy the following condition:
(formula 15)
Under the condition that the above-mentioned limitation is satisfied, J random sequences of compliance parameters are generated.
(2) Generating a sequence according to the parameters: using the Monte Carlo method to generate 200 obedient parameters asThe random sequences of the bernoulli distribution, the 200 sequences generated can be represented as follows:
(formula 16)
(3) SELF values were calculated for the generated sequence: for each random sequence P generatedjMapping to Qj＝(1-2Pj) Performing IFFT after (1+ i) to transform the signals into time domain signals, and calculating SELF of the time domain signals. Calculating SELF of 200 generated sequences according to formula 7 to obtainAnd sorting the SELF values of the sequence in descending order, setting the sampling coefficient to be 0.2, after sorting in descending order, setting the 1 st SELF value as the highest SELF value, and setting the 1 stThe individual SELF values are the threshold values γ for this secondary sequence SELF,is an rounding-up function.
(4) And (5) judging whether the iteration times are up to 70, if so, going to the step (6), and otherwise, going to the step (5). In order to obtain a comparison result with the conventional algorithm, the number of iterations is used as a condition for judging the termination of the iterations, and a convergence condition that the absolute value of the difference between the highest SELF values of the two iteration generated sequences before and after the iteration generation is smaller than a certain threshold value can also be used as a condition for judging the termination of the iterations.
(5) The iteration parameter u is updated by the generation sequence according to the following criterionn：
(formula 17)
Where α () is an indication function: if and only ifIf so, equal to 1, otherwise, equal to 0; pjFor the j-th sequence generated at a time, Pj,nSetting the parameters of the next iteration for the value of the nth element of the generated jth sequenceEntering the step (2) for next iteration。
(6) The sequence corresponding to the minimum value of SELF in the step (3)Is mapped as Qj＝(1-2Pj) (1+ i) to produce sequences of better correlation properties.
Through each iteration, the probability distribution function has a sequence with higher probability and better autocorrelation property, and the technical purpose of designing the STF sequence is achieved through multiple iterations. After the iteration is terminated, the sequence of the highest SELF is selected. Fig. 2 shows a graph of the highest SELF value of the sequence generated each time by applying the algorithm of the present invention and training 70 times, it can be seen that the convergence is very fast, which is reported about 40, and at the same time, the PAPR value of the sequence is only 2.7dB by calculation, which also has good low peak-to-average ratio characteristic. FIG. 3 is a time domain waveform of the final generated design sequence of the present invention over one DFT period. Fig. 4 is a time-domain autocorrelation diagram of the finally generated design sequence of the present invention.
Table-1256 bit sequence part position first 30 training probability parameter changes
The STF frequency domain sequence of the repetition of the time domain waveform obtained in the training process is as follows:
Claims (8)
1. A short training sequence design method for a wireless local area network communication system is characterized by comprising the following steps:
1) setting parameters of the designed sequence, including: the sequence length N, the repetition times M of a sequence time domain waveform in a DFT period, the number J of random sequences generated each time, a sampling coefficient S, S is more than 0 and less than 1, and initial probability density function parametersIteration end conditions, and initiationSELF value
2) Generating J Bernoulli-distributed random sequences P obeying parameter u by using Monte Carlo methodj；
3) Computationally generated random sequence Pj∈{0,1}NMapping sequence Q ofj∈{-(1+i)，1+i}NSELF of (2);
4) the highest SELF value is selected from J SELFs and recorded asSetting a threshold gamma of SELF;
5) judging whether iteration termination conditions are met, if so, going to step 7, otherwise, going to step 6;
6) according to the result obtained in step 4And gamma updating the iterative parametersAnd u, turning to the step 2 to enter the next iteration;
7) and 4, the mapping sequence corresponding to the highest SELF value obtained in the step 4 is the designed sequence.
2. The method as claimed in claim 1, wherein when there is a conditional restriction on the designed sequence, said step 1 further sets a restriction parameter including a restriction location field C and a restriction location value W.
3. The short training sequence design method for wireless local area network communication system of claim 1, wherein the random sequence P generated in step 2 is not limited by conditionsjExpressed as:
Wherein, Pj,nIs a random sequence PjValue of (a) element (u)nIs the element value of the Bernoulli distribution parameter u, N is the sequence length, J is the number of random sequences;
when there is a conditional restriction, the random sequence P generated in step 2jExpressed as:
Wherein, Pj,nIs a random sequence PjValue of (a) element (u)nIs the element value of the Bernoulli distribution parameter u, C is the limiting position field, wnE.W is the value of the element for limiting the position, N is the sequence length, and J is the number of random sequences.
4. The method of claim 1, wherein the step 3 of calculating SELF of the mapping sequence specifically comprises the steps of:
3.1) generating each random sequence PjMapping to QjThe mapping function is Qj＝(1-2Pj)·(1+i)；
3.2) mapping sequence QjPerforming IFFT to transform the signals into time domain signals;
3.3) calculating SELF of the time domain signal, wherein the specific calculation formula is as follows:
wherein, x ((1-2P)j) (1+ i)) represents the time domain signal of the mapped sequence,and E { } is a statistical average operator, and max { } represents taking the maximum value.
5. The method for designing a short training sequence for a wireless local area network communication system according to claim 1, wherein the step 4 of selecting the highest SELF value and SELF threshold specifically comprises the steps of:
4.1) performing descending sorting processing on the generated J SELF, namely:
wherein down () is a function of sorting the sequences in descending order,is a random sequence PjThe SELF value of the mapping sequence of (2),the jth SELF value in descending order, wherein J is the number of random sequences;
4.2) selecting the highest SELF value obtained this time as
4.3) setting the SELF threshold as:
wherein,the SELF values in descending order, J is the number of random sequences, S is the sampling coefficient,is an rounding-up function.
6. The method as claimed in claim 1, wherein the iteration termination condition set in step 1 is an iteration number or a convergence condition threshold.
7. The method of claim 6, wherein the termination condition is that the number of iterations is reached when the number of iterations is set; when the convergence condition threshold is set, the termination condition isWhereinFor the highest SELF value of the last iteration,the highest SELF value of the iteration is the convergence condition threshold.
8. The short training sequence design method for wireless local area network communication system of claim 1, wherein said step 6 is to design a short training sequence for a wireless local area networkIs transmitted toUpdatingNamely, it isAnd updating u according to the value distribution condition of the nth bit of all sequences meeting the SELF threshold condition gamma, wherein the specific calculation formula is as follows:
wherein,for the element values of the updated bernoulli distribution parameter u, α () is an indication function: if and only ifIf so, equal to 1, otherwise, equal to 0; pjFor every j random sequence generated, Pj,nTo generate the value of the nth element of the jth random sequence,is a random sequence PjSELF values of the mapping sequence of (1).
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