• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.460-468
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• 2009

Multiple-input multiple-output (MIMO) technology applied with orthogonal frequency division multiplexing (OFDM) is considered as the ultimate solution to increase channel capacity without any additional spectral resources. At the receiver side, the challenge resides in designing low complexity detection algorithms capable of separating independent streams sent simultaneously from different antennas. In this paper, we introduce an upper-lower bounded-complexity QRD-M algorithm (ULBC QRD-M). In the proposed algorithm we solve the problem of high extreme complexity of the conventional sphere decoding by fixing the upper bound complexity to that of the conventional QRD-M. On the other hand, ULBC QRD-M intelligently cancels all unnecessary hypotheses to achieve very low computational requirements. Analyses and simulation results show that the proposed algorithm achieves the performance of conventional QRD-M with only 26% of the required computations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.628-638
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• 2005

The analysis of maximum diversity order and coding gain for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems over time-and frequency-selective (or doubly-selective) channels is addressed in this paper. A novel channel time-space correlation function is developed given the spatially correlated doubly-selective Rayleigh fading channel model. Based on this channel-model assumption, the upper-bound of pairwise error probability (PEP) for MIMO-OFDM systems is derived under the maximum likelihood (ML) detection. For a certain space-frequency code, we quantify the maximum diversity order and deduce the expression of coding gain. In this wort the impact of channel time selectivity is especially studied and a new definition of time diversity is illustrated correspondingly

• ETRI Journal
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• v.34 no.4
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• pp.503-510
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• 2012

We analyze the relationship between channel coherence bandwidth and two complexity-reduced lattice reduction aided detection (LRAD) algorithms for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems in correlated fading channels. In both the adaptive LR algorithm and the fixed interval LR algorithm, we exploit the inherent feature of unimodular transformation matrix P that remains the same for the adjacent highly correlated subcarriers. Complexity simulations demonstrate that the adaptive LR algorithm could eliminate up to approximately 90 percent of the multiplications and 95 percent of the divisions of the brute-force LR algorithm with large coherence bandwidth. The results also show that the adaptive algorithm with both optimum and globally suboptimum initial interval settings could significantly reduce the LR complexity, compared with the brute-force LR and fixed interval LR algorithms, while maintaining the system performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.4
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• pp.194-208
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• 2008

In this paper, a multiple-input-multiple-output (MIMO) hybrid-automatic repeat request (HARQ) algorithm with antenna scheduling is proposed. It retransmits the packet using scheduled transmit antennas according to the state of the communication link, instead of retransmitting the packet via the same antennas. As a result, a combination of conventional HARQ systems, viz. chase combining (CC) and incremental redundancy (IR) are used to achieve better performance and lower redundancy. The proposed MIMO-OFDM HARQ system with antenna scheduling is shown to be superior to conventional MIMO HARQ systems, due to its spatial diversity gain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4240-4258
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• 2016

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.1
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• pp.27-32
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• 2016

In this paper, we proposed a soft decision-directed channel estimation based on MMSE estimation for MIMO-OFDM system. While the conventional method employs only pilot signals for channel estimation, the proposed algorithm performs channel estimation using pilot and reliable data signals. We also proposed selection criterion among reliable data signal for channel estimation. From numerical simulations, we show that the proposed channel estimator achieves 1 dB performance gain over conventional channel estimators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.296-303
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• 2005

In this paper, we evaluate system performance and propose signal separation and detection when a user with one antenna shares the co-channel together with a user with two space-time coded antennas. The proposed technique can identify co-channel users by an interference cancellation method and detect the signals by maximum likelihood method. Simulation results show that the shortcoming of the Minimum Mean-Squared Error technique which can be applied two users with the same number of antenna but can not applied for heterogeneous MIMO users with the different number of antennas. Also, we apply the proposed scheme to OFDM system and evaluate the system performance. By simulations, we identify that the performance of the proposed system is the same as that of the existing single antenna users and improves the performance of the two-antenna MIMO users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2908-2924
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• 2019

Multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is widely applied in wireless communication by virtue of its excellent properties in data transmission rate and transmission accuracy. However, as a major drawback of MIMO-OFDM systems, the high peak-to-average power ratio (PAPR) complicates the design of the power amplifier at the receiver end. Some available PAPR reduction methods such as selective mapping (SLM) suffer from high computational complexity. In this paper, a low-complexity SLM method based on active constellation extension (ACE) and joint space-time selective mapping (AST-SLM) for reducing PAPR in Alamouti STBC MIMO-OFDM systems is proposed. In SLM scheme, two IFFT operations are required for obtaining each transmission sequence pair, and the selected phase vector is transmitted as side information(SI). However, in the proposed AST-SLM method, only a few IFFT operations are required for generating all the transmission sequence pairs. The complexity of AST-SLM is at least 86% less than SLM. In addition, the SI needed in AST-SLM is at least 92.1% less than SLM by using the presented blind detection scheme to estimate SI. We show, analytically and with simulations, that AST-SLM can achieve significant performance of PAPR reduction and close performance of bit error rate (BER) compared to SLM scheme.

• 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 $10^{-3}$.