• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1082-1086
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• 2008

Multiple-input multiple-output (MIMO) is an efficient technology to increase data rate in wireless networks due to bandwidth and power limitations. Data transmission rate between transmitter and receiver is determined by channel capacity. MIMO has an advantage of reliable communication over wireless channel because of utilizing the channel capacity properly. In this letter, we drive a new formula, closed form capacity formula, using confluent hypergeometric function.

• 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.

• Journal of Korean Association for Spatial Structures
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• v.13 no.3
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• pp.91-98
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• 2013

A multi-input single-output (MISO) semi-active control systems were studied by many researchers. For more improved vibration control performance, a structure requires more than one control device. In this paper, multi-input multi-output (MIMO) semi-active fuzzy controller has been proposed for vibration control of seismically excited small-scale buildings. The MIMO fuzzy controller was optimized by multi-objective genetic algorithm. For numerical simulation, five-story example building structure is used and two MR dampers are employed. For comparison purpose, a clipped-optimal control strategy based on acceleration feedback is employed for controlling MR dampers to reduce structural responses due to seismic loads. Numerical simulation results show that the MIMO fuzzy control algorithm can provide superior control performance to the clipped-optimal control algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37C no.12
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• pp.1289-1295
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• 2012

An adaptive digital predistortion (PD) technique is proposed for linearization of power amplifiers (PAs) in multiple-input multiple-output (MIMO) transmitters. We consider a PD structure equipped with only one combined feedback path while conventional systems have multiple feedback paths. Hence, the proposed structure is much simpler than that of multiple feedback paths. Based on the structure, a new PD algorithm is derived. The simulation results show that linearization performance of the proposed method is almost the same as the conventional multiple feedback technique while the former is much simpler to implement than the latter.

• Journal of Communications and Networks
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• v.18 no.2
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• pp.210-217
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• 2016

In this paper, we propose a low complexity multiple-input multiple-output (MIMO) detection algorithm with adaptive interference mitigation in downlink multiuser MIMO (DL MU-MIMO) systems with quantization error of the channel state information (CSI) feedback. In DL MU-MIMO systems using the imperfect precoding matrix caused by quantization error of the CSI feedback, the station receives the desired signal as well as the residual interference signal. Therefore, a complexMIMO detection algorithm with interference mitigation is required for mitigating the residual interference. To reduce the computational complexity, we propose a MIMO detection algorithm with adaptive interference mitigation. The proposed algorithm adaptively mitigates the residual interference by using the maximum likelihood detection (MLD) error criterion (MEC). We derive a theoretical MEC by using the MLD error condition and a practical MEC by approximating the theoretical MEC. In conclusion, the proposed algorithm adaptively performs interference mitigation when satisfying the practical MEC. Simulation results show that the proposed algorithm reduces the computational complexity and has the same performance, compared to the generalized sphere decoder, which always performs interference mitigation.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.26-33
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• 2014

For wireless communication systems of (and beyond) LTE-Advanced, multiple-input multiple-output (MIMO) with an increased number of antennas will be utilized for system throughput improvement. When using such an increased number of antenna, an excessive amount of overhead in channel state information (CSI) feedback can be a serious problem. In this paper, we propose methods which reduce the CSI feedback overhead, particularly including application strategies for multi-rank transmission targeted for two or more reception antennas. To reduce the information which is instantaneously transmitted from the reception node to the transmission node, we present a beamforming method utilizing singular value decomposition (SVD) based on channel estimation of partitioned antenna arrays. Since the SVDs for partial matrices of the channel may lose the characteristics of the original unpartitioned matrix, we explain an appropriate scheme to cope with this problem.

• Journal of Internet Computing and Services
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• v.4 no.5
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• pp.1-9
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• 2003

In this paper, we combine AMC (Adaptive Modulation and Coding) with MIMO (Multiple Input Multiple Output) multiplexing to improve the throughput performance of AMC in Next Generation Communication Mobile Systems. In addition, we propose a system that adopts STD (Selection Transmit Diversity) in the combined system. The received SNR (Signal to Noise Ratio) is improved by adopting STD techniques and an improved SNR increases a probability of selecting MCS (Modulation and Coding Scheme) level that supports higher data rate. The computer simulation is performed in flat Rayleigh fading channel. The results show that higher throughput is achieved by AMC-TD schemes. AMC-STTD scheme shows about 250kbps increase in throughput. And AMC-STD with 2 transmit antennas achieves about 420 kbps throughput improvement over the conventional AMC at 9dB SNR.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.17-22
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• 2018

In massive multiple-input multiple-output (MIMO) systems, linear channel estimation algorithms are widely applied owing to their simple structures. However, they may cause pilot contamination, which affects the subsequent data detection performance. Therefore, herein, for an uplink multicell massive multiuser MIMO system, we consider using an alternating projection (AP) for channel estimation to eliminate the effect of pilot contamination and improve the performance of data detection in terms of the bit error rates as well. Even though the AP is nonlinear, it iteratively searches the best solution in only one dimension, and the computational complexity is thus modest. We have analyzed the mean square error with respect to the signal-to-interference ratios for both the cooperative and non-cooperative multicell scenarios. From the simulation results, we observed that the channel estimation results via the AP benefit the following signal detection more than that via the least squares for both the cooperative and non-cooperative multicell scenarios.

• 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