Research On Uplink SC-FDMA Multi-antenna Detection And Blind Recognition Of Space-time Block Code

This paper includes two parts: the first part studies SU-MIMO & MU-MIMO detection algorithm that can promote BER performance of the system,against multi-atenna SC-FDMA system, the second part is about STBC blind recognition at the receiver.MIMO and SC-FDMA has become core technology of LTE uplink system, which can enhance uplink transmission reliability and improve spectral efficiency. For detector is an integral part of receiver, the first part is against LTE/LTE-A uplink detection algorithm.To complete the detetion and recovery of MIMO signal, the receiver need the information of MIMO mode and STBC type in advance. In LTE system, those information is sent to the reception through signaling. But in some special scenarios like military affairs, to investigate signal or ensure the safety and efficiency of own communication, the recognition may be taken with MIMO information unknown. Most attention of the studies has been payed to the identification of the parameters like modulation and bandwith, not to the multi-atenna communiacation. So the second part is against the blind recongnition of STBC when several types are used at the transmitter.The study and the structure of this paper is as following.Chapter 1st inroduce LTE/LTE-A uplink key technique, MIMO, SC-FDMA and Co MP and the background and development of blind recognition, then give the content and strecture of this paper;Chapter 2nd studies the the detection algorithms of the detector in single-cell SU-MIMO system. First, discribe the classic frequency domain linear equlization,decision feedback equalization, Turbo equalization and successive interference cancellation, then the quasi-maximum-likelihood algorithm including K-Best, QRD-M,ML-Post Detection Processing and an algorithm which based on ISI cacellation. Using Matlab Simulink link simulation platform built by myself, compare the BER performance of different algorithms under various attenna configuration.The simulation gives the conclusion that Quasi-ML algorithm is better than the others in the system without coding.In Chapter 3rd,simulation towards ZF, MMSE and SIC under 3GPP SCM or three-cell Co MP channel has been taken in single-cell MU-MIMO model and multi-cell Co MP MU-MIMO model. In the scenario of single-cell MU-MIMO, two cases has been considered as to compare BER performance of detection algorithm with SU-MIMO. Case 1st is thar the configuration of every UE and BS is the same as that in SU-MIMO; Case 2nd is that the configuration of total antenna configuration at receiver and transmitter is the same in both system.As the simulation result shows, in Case 1st BER performance in SU-MIMO exceeds that in MU-MIMO, however, in Case 2nd,BER performance in MU-MIMO exceeds that in SU-MIMO, for MU-MIMO can get multi-user diversity gain much easier. In multi-cell, the simulation shows that without Co MP, SNR has little impact at the performance of algorithms, for the interference from neighbour cell is in domination. At the end, from the simulation we can tell that the BER performance in Co MP-MU-MIMO and single-cell SU-MIMO is nearly the same.Chapter 4th study the blind recognition of STBC, which aims at making decision of the STBC type chosen by the transmition end with the knowledge of the set of STBC being uesd. Two type of STBC has been taken into consideration, algorithms based either on matrix norm or maximum liklihood ratio. The one based on matrix norm can be divided into two categories, classifier based on decision tree and classifier based on minimum distance of matrix norm. On the other hand, the one based on maximum liklihood ratio contains three algorithms, which are optimal classifier,second order statistics classifier and code parameter classifier. This paper take correct detection ratio as asessment criteria for the performance of different algorithms.Conclusion as follows have been drawn: 1) more receiving atennas, more samples,higher the correct recogition ratio is; 2) the performance of the algorithm based on maximum liklihood ratio is better than that of the algorithm based on matrix norm; 3)as for optimal classifier, second order statistics classifier and decision tree basing classifier, there is no performance difference between them SM and AL, but for code parameter classifier and minimum distance of matrix basing classifier, the performance of SM is better than SL.The last chapter makes a summary, point out the future research direction and work.