• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.5-9
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• 2006

In this paper, a low-complexity ML decoder based on QR decomposition, called LCMLDec decoder, is proposed for the V-BLAST with 2 transmit antennas. Then, it is combined with other suboptimal interference nulling and cancelling decoders originated form QR decomposition such as sorted QR or MMSE-SQRD decoder to generate efficient decoders that significantly improve the performance of the V-BLAST with more than 2 transmit antennas, at the expense of a small increase in complexity. Simulation results are provided to demonstrate the performances and complexities of the proposed decoders.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.110-116
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• 2005

In this paper, a low-complexity ML decoder based on QR decomposition, called LCMLDec decoder, is proposed for the V-BLAST with 2 transmit antennas. Then, it is combined with other suboptimal interference nulling and cancelling decoders originated form QR decomposition such as sorted QR or MMSE-SQRD decoder to generate efficient decoders that significantly improve the performance of the V_BLAST with more than 2 transmit antennas, at the expense of a small increase in complexity. Simulation results are provided to demonstrate the performances and complexities of the proposed decoders.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.8C
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• pp.782-787
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• 2007

This paper presents the D(Diagonal)-QR-RLS algorithm which normalizes the fast algorithm minimizes the MSE by using Givens rotated inputs and analyzes its characteristic. This proposed one has computational complexity of O(N) and the merit that it obtains the coefficients of TDL filter directly. Although this proposed normalized algorithm has the similar form to NLMS algorithm, we can see that D-QR-RLS has superior convergence characteristic to NLMS by computer simulation.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.20-25
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• 2009

The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been presented as a suboptimum multiple-input multiple-output (MIMO) detection scheme which can provide almost the same performance as the optimum maximum likelihood (ML) MIMO detection scheme but with the reduced complexity. However, due to the lack of parallelism and the regularity in the decoding structure, the conventional QRM-MLD which uses the tree-structure still has very high complexity for the very large scale integration (VLSI) implementation. In this paper, we modify the tree-structure of conventional QRM-MLD into trellis-structure in order to obtain high operational parallelism and regularity and then apply the Viterbi algorithm to the QRM-MLD to ease the burden of the VLSI implementation.We show from our selected numerical examples that, by using the QRM-MLD with our proposed trellis-structure, we can reduce the complexity significantly compared to the tree-structure based QRM-MLD while the performance degradation of our proposed scheme is negligible.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.11
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• pp.1371-1377
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• 2013

In this analysis, a method is presented to calculate the critical speed of a railway vehicle by using a multibody dynamic model. The contact conditions and contact forces between the wheel and the rail are formularized for the wheelset model. This is combined with the bogie model to obtain a multibody dynamic model of a railway vehicle with constraint conditions. First-order linear dynamic equations with independent coordinates are derived from the constraint equations and dynamic equations of railway vehicles using the QR decomposition method. Critical speeds are calculated for the wheelset and bogie dynamic models through an eigenvalue analysis. The influences of the design parameters on the critical speed are presented.

• ETRI Journal
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• v.35 no.3
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• pp.371-377
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• 2013

An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11A
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• pp.1244-1252
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• 2004

In this paper, we derive some properties of linear detectors (zero forcing or minimum mean square error) at spatial multiplexing systems with alamouti's space-time block code. Based on the derived properies, this paper proposes low-complexity receivers. Implementing MMSE detector adaptively, the number of weight vectors to be calculated and updated is greatly reduced with the derived properties compared to the conventional methods. In the case of recursive least square algorithm, with the proposed approach computational complexity is reduced to less than the half. We also identify that sorted QR decomposition detector, which reduces the complexity of V-Blast detector, has the same properties for unitary matrix Q and upper triangular matrix R. A complexity reduction of about 50%, for sorted QR decomposition detector, can be achieved by using those properties without the loss of performance.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.10
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• pp.75-82
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• 2008

In this paper, we propose an efficient symbol detection algorithm for multiple-input multiple-output spatial multiplexing (MIMO-SM) systems and present its design and implementation results. By enhancing the performance of the first detected symbol which causes error propagation, the proposed algorithm achieves a considerable performance gain as compared to the conventional sorted QR decomposition (SQRD) based detection and the ordered successive detection (OSD) algorithms. The bit error rate (BER) performance of the proposed detection algorithm is evaluated by the simulation. In case of 16QAM MIMO-SM system with 4 transmit and 4 receive ($4{\times}4$) antennas, at $BER=10^{-3}$ the proposed algorithm obtains the gai improvement of about 2.5-13.5 dB over the conventional algorithms. The proposed detection algorithm was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.18um 1.8V CMOS standard cell library. The results show that the proposed algorithm can be implemented without increasing the hardware costs significantly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.535-544
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• 2012

Multi-Input Multi-Output (MIMO) transmission is now considered as one of essential techniques enabling high rate data transmissions in wireless communication systems. In addition, severe channel impairments in wireless systems should be compensated by using highly efficient forward error correction (FEC) codes. Turbo codes or low density parity check (LDPC) codes, using iterative decoding with soft decision detection information (SDDI), are the most common examples. The excellent performance of these codes should be conditioned on accurate estimation of SDDI from the MIMO detection process. In this paper, we propose a soft MIMO detection scheme using QR decomposition of channel matrices as an efficient means to provide accurate SDDI to the iterative decoder. The proposed method employed a two sequential soft MIMO detection process in order to reduce computational complexity. Compared to the soft ZF method calculating the direct inverse of the channel matrix, the complexity of the proposed method can be further reduced as the number of antennas is increased, without any performance degradation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1127-1133
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• 2007

This paper proposes one of normalized QR-typed LMS (Least Mean Square) algorithms with computational complexity of O(N). This proposed algorithm shows the normalized property in terms of theoretical characteristics. This proposed algorithm is one of algorithms which normalize variance of input signal in terms of mean because QR-typed LMS is proportional to variance of input signal. In this paper, convergence characteristic analysis of normalized algorithm was made. Computer simulation was made by the algorithms used for echo canceller. Proposed algorithm has similar performance to theoretical value. And, we can see that proposed method shows similar one to performance of NLMS.by comparison among different algorithms.