CN109714773A - A kind of sequence sets design method based on optimal clustering algorithm - Google Patents
A kind of sequence sets design method based on optimal clustering algorithm Download PDFInfo
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- CN109714773A CN109714773A CN201910026008.8A CN201910026008A CN109714773A CN 109714773 A CN109714773 A CN 109714773A CN 201910026008 A CN201910026008 A CN 201910026008A CN 109714773 A CN109714773 A CN 109714773A
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Abstract
The invention belongs to wireless communication techniques and Radar Technology field, are related to a kind of sequence sets design method based on optimal clustering algorithm.Technical solution of the present invention, before Waveform Design, sub-carrier carries out sub-clustering first.Specifically: find circular difference set relevant to total number of sub-carriers N and sub-clustering number L, one group of circular difference set is generated by the circular difference set again, the carrier notation vector that the identical least L circular difference set of element generates L different optimal clustering algorithms is chosen from these circular difference sets.Then one low PAPR of each carrier notation vector design and optimal relevant sequence sets are directed to.Sequence sets design method proposed by the present invention is capable of the correlation properties and PAPR characteristic of effective optimization collection, is suitable for sub-clustering TDCS and MIMO radar, effectively promotes the multiple access capability of sub-clustering TDCS system and the detection accuracy of radar.
Description
Technical field
The invention belongs to wireless communication techniques and Radar Technology field, are related to a kind of sequence sets based on optimal clustering algorithm
Design method.
Background technique
With the high speed development of Modern wireless communication technology and Radar Technology, frequency spectrum resource becomes more and more precious how
Realized in limited frequency spectrum more multi-functional, the effective utilization efficiency for improving frequency spectrum is modern electronic technology pass to be solved
Keyness problem.Frequency spectrum cluster-based techniques can be reduced different in different user or MIMO radar in TDCS by dividing usable spectrum
Interference between transmitting antenna improves the utilization efficiency of frequency spectrum, lifting system performance.
Traditional TDCS system is not sub-clustering, because each sequence occupies identical frequency spectrum, with sequence number
Increase, will be obviously improved by sequence bring multi-user interference (Multi-User Interference, MUI).Traditional TDCS
High number of users when, have poor bit error rate performance, such as: when number of users be greater than 6 when, the bit error rate (Bit of traditional TDCS
Error Ratio, BER) performance is considered very poor.And in the improved TDCS system based on sub-clustering, can have by sub-clustering
The multiple access capabilities of the raising system of effect.There are mainly three types of traditional frequency spectrum clustering algorithms: continuous frequency spectrum sub-clustering, uniformly discrete
Frequency spectrum sub-clustering and the sub-clustering of Random Discrete frequency spectrum, wherein the Random Discrete frequency spectrum sub-clustering based on Monte Carlo Method is considered as these three
It is optimal in sub-clustering mode.However, this cluster-dividing method is random, it is virtually impossible to real optimal clustering algorithm is obtained, and
And having a higher PAPR characteristic by the sequence sets that pseudo-random sequence generates, it is non-that when high power transmission, will receive power amplifier
The influence of linear distortion.
Summary of the invention
In the presence of solving the problems, such as above-mentioned frequency spectrum sub-clustering sequence sets, the invention proposes one kind to be based on optimal sub-clustering
The sequence sets design method of strategy.
The technical solution of the present invention is as follows:
If sub-carrier number is N, N is prime number, and the number of sub-clustering is L, and the number of users on each group is U, and total number of users is
UL, optimal clustering algorithm are as follows:
S1, searching parameter areCircular difference set, in which:To be rounded downwards, specifically
Steps are as follows:
S11, basis:Known sub-carrier number N and sub-clustering number L is substituted into, is calculated
λ value, thick to judge that (N, N/L, λ) circular difference set whether there is: if λ value is integer, there may be if λ is not whole to circular difference set
Number, then circular difference set is centainly not present, and adjusts sub-carrier number N and sub-clustering number L by above formula and λ is made to be integer.
S12, it is by existing circular difference set generation method searching parameterCircular difference set, and lead to
Cross the circular difference set can construct it is N number ofCircular difference set.L are chosen from this N number of circular difference set, are chosen former
It is then that this identical element of L circular difference set is minimum.
S2, the L circular difference set according to selection, divide the spectrum into L cluster, clustering algorithm is optimal at this time.Specific step
It is rapid as follows:
S21, circular difference set is mapped as to the subcarrier status label vector a that length is Nl=[al(1),al(2),...,al
(N)], in which:Indicate circular difference set in subcarrierMiddle element institute is right
Answer the subcarrier on position available,It represents and is not belonging to circular difference set in subcarrierSubcarrier on position corresponding to middle element is unavailable.
S22, the signal modulus value on available subcarrier is fixed as to the same constant ε, ε is that the power normalization of signal is calculated
Son, at this point, the autocorrelation of sequence is best.
S3, according to the subcarrier label vector a of the obtained every cluster of S2l, designed by cycle phase mapping algorithm low
The sequence sets of PAPR, the specific steps are as follows:
S31, initial random phasic serial signal set: P=[p is provided1,p2,…,pU], in which:mu(n) ∈ [0,2 π) be signal phase on u-th of user, n-th of subcarrier, root
According to subcarrier label vector al, generate initial optimal sub-clustering sequence sets: Q0=ε diag (al)P。
S32, fixed QkIt is constant, calculate frequency domain sequence collection QkTime domain sequences collection: qk=FHQk, wherein F is DFT matrix, can
Accelerated with IFFT.Only take qkPhase information can obtain:
A=exp (jangle (qk))
Wherein, angle () is to take phase operation.
S33, fixed A are constant, calculate frequency domain sequence collection corresponding to A: B=FA, and equally available FFT accelerates to calculate, according to B
Update optimal sub-clustering sequence sets Qk+1:
Qk+1=ε diag (a) exp (jangle (B))
S34, S32 and S33 is repeated, until reaching previously given algorithm stop condition:
||Qk+1-Qk||≤10-3or k≥100
Wherein | | | | the Frobenius norm of matrix is represented, k >=100 provide controllable runing time for algorithm.
Technical solution of the present invention, before Waveform Design, sub-carrier carries out sub-clustering first.Specifically: it finds and son
Total number subcarriers N and the relevant circular difference set of sub-clustering number L, it is verified, it can be made with the carrier notation vector that circular difference set generates
The autocorrelation of sub-clustering sequence is optimal.One group of circular difference set is generated by the circular difference set again, is selected from these circular difference sets
The identical least L circular difference set of element is taken to generate the carrier notation vector of L different optimal clustering algorithms.Then for each
One low PAPR of a carrier notation vector design and optimal relevant sequence sets.
In the sequence sets design of optimal clustering algorithm, generated first by random phasic serial signal collection and carrier notation vector
Initiation sequence collection, then sequence sets are transformed into time domain through IFFT, for the PAPR characteristic obtained, only take the phase of the time domain sequences collection
Position information generates the time domain sequences collection of a permanent mould, this time domain sequence sets is obtained a frequency domain sequence through FFT transform to frequency domain
Collection, then the phase information of this frequency domain sequence collection and carrier notation vector is taken to generate the new sequence for meeting optimal clustering algorithm
Collection, iteration finally obtains the optimal clustering algorithm of optimization PAPR until meeting previously given algorithm stop condition repeatedly
Sequence sets.
Beneficial effects of the present invention:
Sequence sets design method proposed by the present invention is the low PAPR sequence sets design based on optimal clustering algorithm, can
The correlation properties and PAPR characteristic of effective optimization collection, are suitable for sub-clustering TDCS and MIMO radar, effectively promotion sub-clustering
The multiple access capability of TDCS system and the detection accuracy of radar.
Detailed description of the invention
Fig. 1 is the clustering algorithm figure of random sub-clustering；
Fig. 2 is the autocorrelation function graph of random sub-clustering；
Fig. 3 is the clustering algorithm figure based on the optimal sub-clustering of (31,15,7) circular difference set；
Fig. 4 is the autocorrelation function graph based on the optimal sub-clustering of (31,15,7) circular difference set；
Fig. 5 is the temporal amplitude figure of random sequence；
Fig. 6 is the temporal amplitude figure for the sequence that the method for the present invention obtains.
Specific embodiment
Technical solution of the present invention is described in detail in Summary, details are not described herein.
Claims (1)
1. a kind of sequence sets design method based on optimal clustering algorithm, if sub-carrier number is N, N is prime number, and the number of sub-clustering is
L, the number of users on each group are U, and total number of users is UL, which comprises the following steps:
S1, get parms forCircular difference set, in which:To be rounded downwards, specifically include:
S11, orderKnown sub-carrier number N and sub-clustering number L is substituted into, λ value is calculated, slightly sentences
Disconnected (N, N/L, λ) circular difference set whether there is: if λ value is integer, there may be recycle if λ is not integer circular difference set
Difference set is centainly not present, and adjusts sub-carrier number N and sub-clustering number L by above formula and λ is made to be integer；
S12, it is by existing circular difference set generation method searching parameterCircular difference set, and followed by this
Ring difference set constructs N number ofCircular difference set chooses L from this N number of circular difference set, and selection principle is this L
The identical element of circular difference set is minimum；
S2, the L circular difference set according to selection, divide the spectrum into L cluster, and clustering algorithm at this time is defined as optimal sub-clustering plan
Slightly, it specifically includes:
S21, circular difference set is mapped as to the subcarrier status label vector a that length is Nl=[al(1),al(2),...,al(N)],
Wherein:Indicate circular difference set in subcarrierPosition corresponding to middle element
The subcarrier set is available,It represents and is not belonging to circular difference set in subcarrierSubcarrier on position corresponding to middle element is unavailable；
S22, the signal modulus value on available subcarrier is fixed as to the same constant ε, ε is the power normalization operator of signal；
S3, according to the subcarrier label vector a of the obtained every cluster of S2l, pass through cycle phase mapping algorithm implementation sequence collection, tool
Body includes:
S31, an initial random phasic serial signal set is provided:
P=[p1,p2,...,pU]
Wherein:mu(n) ∈ [0,2 π) be letter on u-th of user, n-th of subcarrier
Number phase, according to subcarrier label vector al, generate initial optimal sub-clustering sequence sets: Q0=ε diag (al)P；
S32, fixed QkIt is constant, calculate frequency domain sequence collection QkTime domain sequences collection: qk=FHQk, wherein F is DFT matrix, only takes qk
Phase information obtain:
A=exp (jangle (qk))
Wherein, angle () is to take phase operation；
S33, fixed A are constant, calculate frequency domain sequence collection corresponding to A: B=FA, update optimal sub-clustering sequence sets Q according to Bk+1:
Qk+1=ε diag (a) exp (jangle (B))
S34, S32 and S33 is repeated, until reaching previously given stop condition:
||Qk+1-Qk||≤10-3or k≥100
Wherein | | | | the Frobenius norm of matrix is represented, k >=100 are the runing time of setting.
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