An Adaptive K-Best Algorithm Without SNR Estimation for MIMO Systems

This paper proposes a new adaptive K-best algorithm for MIMO systems. The proposed scheme controls the number of survivor paths, K based on the degree of the reliability of Zero-Forcing (ZF) estimates at each K-best step. The critical drawback of the fixed K-best detection is that the correct path's metric may be temporarily larger than K minimum paths metrics due to imperfect interference cancellation by the incorrect ZF estimates. So, the conventional variable K-best schemes control K according to measured SNR value. However, these schemes still have the problem that needs to accurately and dynamically measure SNR for optimal setting of K.