The zip file contains several matlab files. These files implement the optimal vlassifier (optimal_classifier.m), a sub-optimal classifier (SOS_STBC_Classifier.m) which is based on Second Order Statistic and a low-complexity sub optimal code-parameter classifier (CP_Classifier.m). See reference [1] for the theoretical background. Example: To create the fig 3,4 and 5 of the paper, call the routine: Blind_recognition_STBC2_simulation_results(512,4, PSK ,4) Reference: [1] V. Choqueuse, M. Marazin, L. Collin, K. Yao and G. Burel "Blind recognition of STBC: A Likelihood-based Approach", IEEE Transactions on Signal Processing (IF: 2.33), vol. 58(3), pp : 1290-1299, March 2010.

Blind_recognition_STBC2_simulation_results.m
Blind_recognition_STBC4_simulation_results.m
CP_Classifier.m
Optimal_Classifier.m
PermsRep.m
Readme.txt
SOS_STBC_Classifier.m
compute_LF.m
compute_LF_CP.m
compute_LF_SOS.m
license.txt
one_shot_STBC2.m
one_shot_STBC4.m
space_time_coding.m

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