• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11A
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• pp.852-861
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• 2009

We propose a complexity reduced Lattice Reduction(LR) scheme for MIMO detection under time varying fading environments. It is found that for successive MIMO transmission instances, the integer matrix P after LR decomposition remains the same or only a few elements of the matrix P are slightly changed. Based on this feature, we perform LR reduction by setting the initial values for P matrix for the decomposition to be the one obtained in the previous instance not starting from the identity matrix. Simulation results reveal that the proposed scheme drastically reduces overall complexity of LR reduction compared to the conventional scheme for various system parameters under time varying channels. We also show that the proposed scheme can be applied to Seysen LR as well as LLL(Lenstra, Lenstra, and Lavasaz)-LR.

• International journal of advanced smart convergence
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• v.7 no.3
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• pp.37-43
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• 2018

Lattice-reduction (LR) techniques have been developed for signal detection in spatial multiplexing multiple input multiple output (MIMO) systems to obtain the largest diversity gain. Thus, an LR-assisted zero-forcing (ZF) receiver can achieve the maximum diversity gain in spatial multiplexing MIMO systems. In this paper, a simplified analysis of the achievable diversity gain is presented by fitting the channel coefficients lattice-reduced by a complex Lenstra-Lenstra-$Lov{\acute{a}}z$ (LLL) algorithm into approximated Gaussian random variables. It will be shown that the maximum diversity gain corresponding to two times the number of receive antennas can be achieved by the LR-based ZF detector. In addition, the approximated bit error rate (BER) expression is also derived. Finally, the analytical BER performance is comparatively studied with the simulated results.

• Journal of Communications and Networks
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• v.13 no.5
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• pp.481-493
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• 2011

Multiple-input multiple-output (MIMO) technology provides high data rate and enhanced quality of service for wireless communications. Since the benefits from MIMO result in a heavy computational load in detectors, the design of low-complexity suboptimum receivers is currently an active area of research. Lattice-reduction-aided detection (LRAD) has been shown to be an effective low-complexity method with near-maximum-likelihood performance. In this paper, we advocate the use of systolic array architectures for MIMO receivers, and in particular we exhibit one of them based on LRAD. The "Lenstra-Lenstra-Lov$\acute{a}$sz (LLL) lattice reduction algorithm" and the ensuing linear detections or successive spatial-interference cancellations can be located in the same array, which is considerably hardware-efficient. Since the conventional form of the LLL algorithm is not immediately suitable for parallel processing, two modified LLL algorithms are considered here for the systolic array. LLL algorithm with full-size reduction-LLL is one of the versions more suitable for parallel processing. Another variant is the all-swap lattice-reduction (ASLR) algorithm for complex-valued lattices, which processes all lattice basis vectors simultaneously within one iteration. Our novel systolic array can operate both algorithms with different external logic controls. In order to simplify the systolic array design, we replace the Lov$\acute{a}$sz condition in the definition of LLL-reduced lattice with the looser Siegel condition. Simulation results show that for LR-aided linear detections, the bit-error-rate performance is still maintained with this relaxation. Comparisons between the two algorithms in terms of bit-error-rate performance, and average field-programmable gate array processing time in the systolic array are made, which shows that ASLR is a better choice for a systolic architecture, especially for systems with a large number of antennas.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3010-3025
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• 2016

Lattice reduction (LR) has been used widely in conventional multiple-input multiple-output (MIMO) systems to enhance the performance. However, LR is hard to be applied to the relay systems which are important but more complicated in the wireless communication theory. This paper introduces a new viewpoint for utilizing LR in multiuser MIMO relay systems. The vector precoding (VP) is designed along with zero force (ZF) criterion and minimum mean square error (MMSE) criterion and enhanced by LR algorithm. This implementable precoder design combines nonlinear processing at the base station (BS) and linear processing at the relay. This precoder is capable of avoiding multiuser interference (MUI) at the mobile stations (MSs) and achieving excellent performance. Moreover, it is shown that the amount of feedback information is much less than that of the singular value decomposition (SVD) design. Simulation results show that the proposed scheme using the complex version of the Lenstra--Lenstra--Lovász (LLL) algorithm significantly improves system performance.