CN107070602B - A kind of spatial modulation system blind checking method based on K mean cluster algorithm - Google Patents

A kind of spatial modulation system blind checking method based on K mean cluster algorithm Download PDF

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CN107070602B
CN107070602B CN201710258060.7A CN201710258060A CN107070602B CN 107070602 B CN107070602 B CN 107070602B CN 201710258060 A CN201710258060 A CN 201710258060A CN 107070602 B CN107070602 B CN 107070602B
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CN107070602A (en
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游龙飞
杨平
肖悦
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University of Electronic Science and Technology of China
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0047—Decoding adapted to other signal detection operation
    • H04L1/0048—Decoding adapted to other signal detection operation in conjunction with detection of multiuser or interfering signals, e.g. iteration between CDMA or MIMO detector and FEC decoder
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/23—Clustering techniques
    • G06F18/232—Non-hierarchical techniques
    • G06F18/2321—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions
    • G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0036—Systems modifying transmission characteristics according to link quality, e.g. power backoff arrangements specific to the receiver
    • H04L1/0038—Blind format detection
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
    • H04L1/0045—Arrangements at the receiver end
    • H04L1/0052—Realisations of complexity reduction techniques, e.g. pipelining or use of look-up tables
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
    • H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
    • H04L1/0618—Space-time coding
    • H04L1/0631—Receiver arrangements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
    • H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks
    • H04L25/03891—Spatial equalizers

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Abstract

The invention belongs to Communication Anti-Jamming Techniques fields, particularly relate to a kind of improved Blind Detect Algorithm based on K mean cluster.The present invention mainly for avoid incorrect platform problem and reduce algorithm complexity, the specific method is as follows: the reception signal of L time slot is considered as L observation, the Euclidean distance matrix between each observation is acquired first, and K observation is selected as initial cluster center according to the thought for maximizing minimum euclidean distance；Then remaining observation is sequentially placed into that corresponding class away from its nearest cluster centre；Then the mean value of the observation of each class is used to classify as new cluster centre, and by previous step, until classification results no longer change；It is finally bit information by cluster result demapping.Beneficial effects of the present invention are that traditional K mean cluster detection algorithm has incorrect platform, and to mitigate this problem, algorithm complexity is higher, and the present invention can avoid incorrect platform problem completely, and can effectively reduce algorithm complexity.

Description

A kind of spatial modulation system blind checking method based on K mean cluster algorithm
Technical field
The invention belongs to Communication Anti-Jamming Techniques fields, are related to spatial modulation (Spatial Modulation, SM) technology, Spatial displacement keying (Space Shift Keying, SSK) technology, blind examination survey technology (Blind Detection), multi input is more (Multiple Input Multiple Output, the MIMO) technology of output and K mean cluster (K-means Clustering, KMC) algorithm.
Background technique
Spatial modulation system has recently received great interest as a kind of new MIMO technology.In spatial modulation system, often A time slot only activates a transmission antenna transmission data, so as to avoid the interference of interchannel, between the synchronism requirement antenna Also it decreases, and in receiving end, can also be detected when receiving antenna number is less than transmission antenna number.
Detection for spatial modulation system is also a popular problem, and in the work of early stage, there are three types of typical empty Between modulation detection algorithm: Maximum Likelihood Detection, matched filtering detection and globular decoding detection.And these detections hypothesis is known complete U.S. channel state information, and perfect channel state information is difficult to obtain in practice.Therefore, in recent years successively it has been proposed that Blind Detect Algorithm without knowing channel state information, and most Blind Detect Algorithm is required to send some training symbols Sequence, so as to cause the waste of resource.Then recently again it is proposed that a kind of blind examination measuring and calculating based on K mean cluster algorithm Method, without knowing channel state information, without using training symbol, but its application is there are still biggish limitation, such as wrong Accidentally platform problem and high complexity issue, and only considered SSK system.
Summary of the invention
The purpose of the present invention proposes a kind of spatial modulation based on K mean cluster algorithm aiming at spatial modulation system System detecting method.
Technical scheme is as follows:
Assuming that there is NtRoot transmission antenna, NrRoot receiving antenna, order of modulation M, X=[x1,...,xL] be length be L Signal sequence is sent, that is, takes the transmission signal of L time slot.XSMIt is to send signal set,It is to receive Symbol sebolic addressing.The reception signal of L time slot is regarded into L observation, then sends letter received by the identical time slot of signal Number it can be divided into a classI.e.Therefore, the blind Detecting problem of spatial modulation system can be with It is converted into clustering problem, the number K of cluster is all possible numbers for sending signal, i.e. K=Nt*M。
Traditional K mean cluster algorithm random selection initial cluster center reruns so as to cause incorrect platform problem Incorrect platform problem can be mitigated K mean algorithm P times, but the algorithm complexity that has also been multiplied simultaneously.In this regard, the present invention proposes A kind of method based on the selection initial cluster center for maximizing minimum Eustachian distance thought, includes the following steps:
A. set l is inputted, h is enabled*={ yi| i ∈ l } it is initial cluster center set, it is expressed as It is WithFor the class of cluster centre, K is the number of cluster, i.e. all possible number K=N of transmission signalt*M；Obtain the tool of set l Body method is as follows:
A1. assume l=i | yiIt is chosen as cluster centre } it is the set for being chosen as the index of observation of cluster centre, it enablesAs initial value；
A2. the Euclidean distance matrix between each observation is calculated, a matrix is obtainedIts element is
A3. it enablesWherein
A4. willIt is added in set l, and updates setForWherein
A5. step a4 is repeated until the radix of set l is K；
B. for each observation yi, i=1,2 ..., L are calculatedAnd by yiIt is added In；
C. the cluster centre for recalculating each class, using the mean value of the observation in each class as new cluster centre；
D. step b and step c is repeated, until cluster resultIt is no longer changed；
It e. is bit information by cluster result demapping.
The beneficial effects of the present invention are first by maximizing the thought of minimum euclidean distance, acquisition one is more smart True initial cluster center, thus incorrect platform problem caused by avoiding because of bad initial cluster center；In addition, tradition K Mean cluster detector needs to run P K mean cluster algorithm to mitigate the influence of incorrect platform, when transmission antenna number mostly with And order of modulation it is higher when, P value is also bigger, so that complexity is very high, and improved K mean value proposed by the present invention Cluster detector need to only run a K mean cluster algorithm, to considerably reduce algorithm complexity.
Detailed description of the invention
Fig. 1 is spatial modulation blind-detection system block diagram；
Fig. 2 is the improved Blind Detect Algorithm flow chart based on K mean cluster algorithm；
Fig. 3 be different detection algorithm performances compare (4 hair 4 receive, (a) be SSK system, L=40；It (b) is SM system, L= 80, BPSK)；Wherein KMC (P) indicates to be run P times with different initial cluster centers, and improvement KMC is detection proposed by the present invention Method.
Specific embodiment
Below in conjunction with attached drawing, specific embodiments of the present invention are provided.It should be understood that the parameter in embodiment is not Influence generality of the invention.
The improved Blind Detect Algorithm based on K mean cluster algorithm of one kind that the invention proposes is illustrated below.It examines Consider a Nt×NrSpatial modulation system, wherein NtIt is transmitting antenna number, NrIt is receiving antenna number, X=[x1,...,xL] it is long Degree is the transmission signal sequence of L, that is, takes the transmission signal of L time slot.XSMIt is to send signal set,It is to receive symbol sebolic addressing.The reception signal of L time slot is regarded into L observation, is enabledThe number K of cluster is K=Nt*M.As shown in Fig. 2, improved K mean cluster detector Specific detecting step is as follows:
Step 1: input set l enables h*={ yi| i ∈ l } it is initial cluster center set, it is represented by It is
WithFor the class of cluster centre.Obtaining set l, the specific method is as follows:
A) assume l=i | yiIt is chosen as cluster centre } it is the set for being chosen as the index of observation of cluster centre, it enablesAs initial value.
B) the Euclidean distance matrix between each observation is calculated, to obtain a matrixIts element is
C) it enablesWherein
D) willIt is added in set l, and updates setForWherein
E) step d) is repeated until the radix of set l is K.
Step 2: for each observation yi, i=1,2 ..., L are calculatedAnd by yiAdd EnterIn；
Step 3: recalculate the cluster centre of each class, using the mean value of the observation in each class as new cluster in The heart；
Step 4: step 2 and step 3 are repeated, until cluster resultIt is no longer changed.
Step 5: being bit information by cluster result demapping.
The complexity of above-mentioned improvement K mean cluster detector is ο (LNtMniter+L2), traditional K mean cluster detector Complexity is ο (PLNtMniter), niterFor the number of iterations.It is compared with traditional K cell average detector, improved base proposed by the present invention It can completely avoid the influence of incorrect platform problem in the Blind Detect Algorithm of K mean cluster, and there is very low algorithm complexity.

Claims (1)

1. a kind of spatial modulation system blind checking method based on K mean cluster algorithm, setting spatial modulation system has NtRoot is sent Antenna, NrRoot receiving antenna, order of modulation M, X=[x1,...,xL] it is the transmission signal sequence that length is L, XSMIt is to send letter Number set,It is to receive symbol sebolic addressing, the reception signal of L time slot is regarded into L observation, i.e., It sends signal received by the identical time slot of signal and is divided into a classI.e.Its feature It is, comprising the following steps:
A. set l is inputted, h is enabled*={ yi| i ∈ l } it is initial cluster center set, it is expressed as Be with For the class of cluster centre, K is the number of cluster, i.e. all possible number K=N of transmission signalt*M；Obtain the specific side of set l Method is as follows:
A1. assume l=i | yiIt is chosen as cluster centre } it is the set for being chosen as the index of observation of cluster centre, enable l= φ,As initial value；
A2. the Euclidean distance matrix between each observation is calculated, a matrix is obtainedIts element isA3. it enablesWherein
A4. willIt is added in set l, and updates setForWherein
A5. step a4 is repeated until the radix of set l is K；
B. for each observation yi, i=1,2 ..., L are calculatedAnd by yiIt is addedIn；
C. the cluster centre for recalculating each class, using the mean value of the observation in each class as new cluster centre；
D. step b and step c is repeated, until cluster resultIt is no longer changed；
It e. is bit information by cluster result demapping.
CN201710258060.7A 2017-04-19 2017-04-19 A kind of spatial modulation system blind checking method based on K mean cluster algorithm Expired - Fee Related CN107070602B (en)

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CN105743617A (en) * 2014-12-09 2016-07-06 山东大学 Hybrid spatial modulation method based on Euclidean distance and antenna selection
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