Enhanced QRD-M algorithm for soft-output MIMO detection

QR-decomposition with M algorithm is a promising technique for multi-input multi-output (MIMO) systems. When the number of candidates is insufficient, its performance is, however, degraded due to an inaccurate log likelihood ratio (LLR). To address this problem, an enhanced soft LLR calculation scheme is proposed for soft-output MIMO detection. Based on QR-decomposition, the proposed algorithm can efficiently obtain a soft information of minimum mean-squared error (MMSE) equalization. With this information, an optimal weighted combining method is derived in an MSE sense. In addition, we compute a more reliable clipping value from the soft information of MMSE equalization. Simulation results show that the proposed algorithm provides a considerable performance gain over conventional algorithms and its performance is close to optimal performance with insufficient candidates.

I. Introduction

Multiple-input multiple-output (MIMO) system is considered one of the most promising technologies for high speed wireless communications. Current standards such as 3GPP Long Term Evolution Advanced (LTE-A) and IEEE 802.16m support MIMO systems to meet the requirements of the International Telecommunication Union [1]–[4]. The use of multiple antennas provides considerable throughput gain proportional to the number of antennas, which is called spatial multiplexing gain. In practice, the benefit of spatial multiplexing gain is not fully exploited unless maximum likelihood detection (MLD) is employed. While the MLD algorithm gives optimal performance, its complexity grows exponentially with the number of transmit antennas and modulation order.