Low-complexity Techniques of K-Best Sphere Decoding for MIMO systems

In the thesis, two low-complexity techniques of K-best SD algorithm are proposed while remain similar performance to conventional K-best SD algorithm and ML detection. Adaptive K-Best SD algorithm provides a means to determine the value K according to the received signals. Clustered K-Best SD algorithm uses the statistics knowledge of the received signal, and the clustering technique replaces the high complexity of the sorter with a few comparators. As compared with conventional 64-Best SD algorithm for 4x4 64-QAM system, the adaptive K-Best SD algorithm can reduce complexity ranges from 23.65 % to 52.22 % within 0.13dB and 1.18dB performance degradation, whereas the clustered K-Best SD algorithm can reduce ove