On an improved K-best algorithm with high performance and low complexity for MIMO systems

Abstract

Multiple-input multiple-output (MIMO) techniques are significantly advanced in contemporary high-rate wireless communications. The computational complexity and bit-error-rate (BER) performance are main issues in MIMO systems. An algorithm is proposed based on a traditional K-Best algorithm, coupling with the fast QR decomposition algorithm with an optimal detection order for the channel decomposition, the Schnorr–Euchner strategy for solving the zero floating-point and sorting all the branches’ partial Euclidean distance, the sphere decoding algorithm for reducing the search space. The improved K-Best algorithm proposed in this paper has the following characteristics: (i) The searching space for the closest point to a region is smaller compared to that of the traditional K-Best algorithm in each dimension; (ii) it can eliminate the survival candidates at early stages, and (iii) it obtains better performance in the BER and the computational complexity.