Abstract
The faster decoding algorithm is still required in multiple-input multiple-output (MIMO) wireless communication technology. Lattice reduction (LR) technique can improve the performance of linear MIMO detection methods. LLL (Lenstra-Lenstra-Lovasz) algorithm is one of the LR techniques and it has being extensively used for better basis of channel matrix by removing noise. LR-aided detection algorithms involve two problems. The first problem is that the reduced basis is still non-orthogonal and most algorithms are devoted for finding a near orthogonal matrix. The second problem is that the feasible set of the detected symbol cannot be found without huge operation. In this paper, we propose a new algorithm which considers unknown transformed symbol to search the neighboring points on transformed basis of the channel matrix. This paper mainly focuses on the second problem to resolve the poor accuracy particularly in high signal-to-noise ratio (SNR). Our proposed algorithm can achieve better BER performance with low complexity and it is proven by simulations.
Highlights
Multiple-input multiple-output technology for wireless communication system has been extensively investigated in recent research with many antennas increasing from tens to hundreds due to its potential support for greater efficiency in data rate and higher reliability than a conventional technology like singleinput single-output (SISO)[1,2]
Our algorithm is more complex than previous Lattice reduction (LR)-linear detection (LD) algorithm because the number of calculation for returning to original basis increases depending on the number of points
The decoding algorithm of multiple-input multiple-output (MIMO) system with its low complexity and great performance is developed from the LR based algorithm
Summary
Multiple-input multiple-output technology for wireless communication system has been extensively investigated in recent research with many antennas increasing from tens to hundreds due to its potential support for greater efficiency in data rate and higher reliability than a conventional technology like singleinput single-output (SISO)[1,2]. ZF and MMSE are linear detection techniques which provide low complexity with inferior performance in comparison with ML detection. Lattice reduction (LR) aided MIMO detection techniques are recently adopted in MIMO systems. Lattice reduction (LR) aided linear detection (LD) techniques can give the same BER performance as ML detection with low complexity. The LR-aided detectors are based on the LLL algorithm which is originally used for reducing real lattice bases[4]. LR can improve the performance by reducing interference on high SNR. We propose a new algorithm focusing on the lattice reduction (LR) to improve the bit error rate (BER) performance. LR can significantly improve the BER performance in MIMO linear decoding using LLL (Lenstra-Lenstra-lovasz) algorithm. The matrices are stated by uppercase letters like A and vectors are stated by lowercase letters like a
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