Research On Blind Estimation Based On K-means Clustering Algorithms In Space Shift Keying System

SSK(Space Shift Keying,SSK)as a new type of MIMO(Multiple-Input Multiple-Output,MIMO)technology,has attracted widespread attention in recent years.Compared with the traditional MIMO that needs to transfer APM(Amplitude/Phase Modulation,APM)constellation,SSK system just activates index of a single antenna as the carrier of information transaction,and its main advantage is that a transmitter has simple structure and high efficiency.At the same time,activating only a single antenna can avoid the problem of the IAI(Inter-Antenna Interference,IAI)and IAS(Inter-Antenna Synchronization,IAS)that traditional MIMO multiplexing technology usually has.For detection technology of receiver in the SSK system,compared with the ideal CSI(Channel State Information,CSI)detection algorithm,in the case of unknown CSI,KMC(K-Means Clustering,KMC)blind detection algorithm can effectively reduce the detection complexity.Under the block fading channel model,the KMC algorithm and exhaustive de-mapping based on the clustering results are proportional to sending sequence length.Therefore,the thesis mainly aims at how to reduce the KMC blind detection algorithm computational complexity,and discusses the blind estimation CSI of the KMC algorithm and exhaustive de-mapping based on clustering results.Firstly,the thesis analyzes the SSK system model and the signal model.For the SSK blind detection system,combining with the clustering algorithm in the field of data mining,the thesis analyzes the connection and transformation between KMC algorithm and detection technology of receiver,and gives mathematical derivation.Using the clustering results of the KMC algorithm de-mapping as a bit of information,with the aid of channel coding rectifying error detection ability,it carries on the exhaustive de-mapping.Secondly,in regard to the system BER performance improvement,the selection of the initial center of mass of the KMC algorithm was improved,the random initialization of centroid to optimized initialization of centroid.From the angle of the lowering computational complexity of the KMC blind detection algorithm,the truncated sequence replaces the original sequence,using the KMC algorithm to blindly estimate the system CSI which later clusters the received signal.Algorithm complexity analysis shows that the computational complexity of detection algorithm based on the KMC algorithm blindly estimate CSI is reduced from proportion to independence with the sending sequence length.Simulation experiment compares the system BER performance of the random initialization of centroid and the optimize initialization of centroid,and validates the system BER performance of the KMC blind detection algorithm and detection algorithm based on the KMC algorithm blindly estimate CSI.Finally,the thesis analyzes the exhaustive de-mapping algorithm based on the clustering results of the KMC algorithm,improves the exhaustive de-mapping algorithm with the aid of channel coding,from checking the whole received sequence to making selective check of the received sequence according to the error interval.The algorithm complexity analysis shows that the computational complexity of the original global de-mapping algorithm is directly proportional to the sending sequence length,and the computational complexity of the improved local de-mapping algorithm,independent of the sending sequence length,is reduced.The simulation experiment have validated the system BER performance of the local de-mapping algorithm and the global de-mapping algorithm.