Soft Log Likelihood Ratio Replacement for Low-Complexity Maximum-Likelihood Detection

Abstract

For multiple-input multiple-output systems, spatial multiplexing techniques can provide significant throughput gain. However, this promised gain can be attained by using maximum-likelihood detection (MLD) which requires huge computational complexity, and thus several low-complexity schemes are proposed to reduce the search space of the MLD. In this letter, we consider the log likelihood ratio (LLR) computation in low complexity MLD for soft channel decoding. We design a weighted combining method for a reliable LLR computation, compensating for the performance loss incurred by insufficient candidates of low-complexity MLD. The proposed LLR generation algorithm effectively reduces the computational complexity while maintaining the system performance of spatial multiplexing systems.