Low-complexity MIMO detector with 1024-QAM

In this paper, dual-layer multiple-input multiple-output (2 × 2 MIMO) systems that use 1024-QAM constellations are studied. Using the layered orthogonal lattice detector (LORD) algorithm, which achieves optimal maximum-likelihood (ML) performance at the expense of high complexity, we argue that the low-complexity version of LORD (LC-LORD) introduces a significant performance degradation, especially with high channel correlation. We propose several approaches that outperform LC-LORD at a lower complexity. These approaches are based on improving the location of a reduced region of search within a 1024-QAM constellation, as well as optimizing the bit log likelihood ratio (LLR) approximation. The proposed approaches were studied in the context of non-iterative and iterative detection and decoding, and significant gains were achieved in both cases.

[1]  Sandro Bellini,et al.  Turbo-LORD: A MAP-Approaching Soft-Input Soft-Output Detector for Iterative MIMO Receivers , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[2]  Louay M. A. Jalloul,et al.  Reduced Complexity Soft-Output MIMO Sphere Detectors—Part I: Algorithmic Optimizations , 2014, IEEE Transactions on Signal Processing.

[3]  Louay M. A. Jalloul,et al.  Efficient Soft-Input Soft-Output Detection of Dual-Layer MIMO Systems , 2014, IEEE Wireless Communications Letters.

[4]  Michael P. Fitz,et al.  Layered Orthogonal Lattice Detector for Two Transmit Antenna Communications , 2005, ArXiv.

[5]  Sandro Bellini,et al.  Low Complexity, Quasi-Optimal MIMO Detectors for Iterative Receivers , 2010, IEEE Transactions on Wireless Communications.

[6]  Louay M. A. Jalloul,et al.  Optimized Configurable Architectures for Scalable Soft-Input Soft-Output MIMO Detectors With 256-QAM , 2015, IEEE Transactions on Signal Processing.

[7]  Emanuele Viterbo,et al.  A universal lattice code decoder for fading channels , 1999, IEEE Trans. Inf. Theory.

[8]  Sandro Bellini,et al.  Hardware oriented, quasi-optimal detectors for iterative and non-iterative MIMO receivers , 2012, EURASIP J. Wirel. Commun. Netw..

[9]  Louay M. A. Jalloul,et al.  Reduced Complexity Soft-Output MIMO Sphere Detectors—Part II: Architectural Optimizations , 2014, IEEE Transactions on Signal Processing.

[10]  Mohammad M. Mansour A Near-ML MIMO Subspace Detection Algorithm , 2015, IEEE Signal Processing Letters.

[11]  Babak Hassibi,et al.  On the sphere-decoding algorithm I. Expected complexity , 2005, IEEE Transactions on Signal Processing.

[12]  Michael P. Fitz,et al.  On Layer Ordering Techniques for Near-optimal MIMO Detectors , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[13]  David Tse,et al.  Fundamentals of Wireless Communication , 2005 .

[14]  Mohammad M. Mansour A low-complexity MIMO subspace detection algorithm , 2015, EURASIP J. Wirel. Commun. Netw..

[15]  Babak Hassibi,et al.  On the sphere-decoding algorithm II. Generalizations, second-order statistics, and applications to communications , 2005, IEEE Transactions on Signal Processing.

[16]  Sandro Bellini,et al.  A Hardware Oriented, Low-Complexity LORD MIMO Detector , 2010, 2010 IEEE International Conference on Communications.

[17]  Rohit U. Nabar,et al.  Introduction to Space-Time Wireless Communications , 2003 .