• Journal of Communications and Networks
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• v.10 no.2
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• pp.163-174
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• 2008

Performance of downlink transmission strategies exploiting cooperative transmit diversity is investigated for distributed multiple-input single-output (MISO) systems, for which geographically distributed remote antennas (RA) in a cell can either communicate with distinct mobile stations (MS) or cooperate for a common MS. Statistical characteristics in terms of the signal-to-interference-plus-noise ratio (SINR) and the achievable capacity are analyzed for both cooperative and non-cooperative transmission schemes, and the preferred mode of operation for given channel conditions is presented using the analysis result. In particular, we determine an exact amount of the maximum achievable gain in capacity when RAs for signal transmission are selected based on the instantaneous channel condition, by deriving a general expression for the SINR of such antenna selection based transmission. For important special cases of selecting a single RA for non-cooperative transmission and selecting two RAs for cooperative transmission among three RAs surrounding the MS, closed-form formulas are presented for the SINR and capacity distributions.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.299-304
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• 1996

This paper studies the rational approximation of multiple input delay systems using the Hankel singular values and vectors, which are the soultion of a transcendental equation. Rational approximatants are obtained from output normal realizations which are constructed by the Hankel singular values and vectors. Consequently, it is shown that rational approximants by output normal realization preserve intrinsic properties of time delay systems than Pade approximants.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.2
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• pp.18-26
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• 2009

When channel state information (CSI) is available at the transmitter, the system throughput can be enhanced by adaptive transmissions and opportunistic multiuser scheduling. In this paper, we consider multiple-input multiple-output (MIMO) systems employing bit-interleaved coded orthogonal frequency division multiplexing (BIC-OFDM). We first propose a bit-loading algorithm based on the Levin-Campello algorithm for the BIC-OFDM. Then we will apply this algorithm to the MIMO system with a finite set of constellations, by reassigning residual power on each stream Simulation results show that proposed bit-loading scheme which takes the residual power into account improves the system performance especially at high signal-to-noise ratio (SNR) range.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5A
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• pp.402-406
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• 2005

A multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) system using low-density parity-check (LDPC) code and iterative decoding is presented. The iterative decoding is performed by combining the zero-forcing technique and LDPC decoding through the use of the 'turbo principle.' The proposed system is shown to be effective with high order modulation and outperforms the space frequency block code (SFBC) method with iterative decoding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.49-52
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• 2008

In this letter, we derive a tight closed form formula for an ergodic rapacity of a multiple-input multiple-output (MIMO) for the application of wireless communications. The derived expression is a simple close-form formula to determine the ergodic capacity of MIMO systems. Assuming the channels are independent and identically distributed (i.i.d.) Rayleigh flat-fading between antenna pairs, the ergodic capacity can be expressed in a closed form as the finite sum of exponential integrals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2166-2180
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• 2016

We investigate the opposite of artificial noise (AN)-assisted communication in multiple-input-multiple-output (MIMO) wiretap channels for the multiuser case by taking the side of the eavesdropper. We first define a framework for an AN-assisted multiuser multiple-input-multiple-output (MU-MIMO) system, for which eavesdropping methods are proposed with and without knowledge of legitimate users' channel state information (CSI). The proposed method without CSI is based on a modified joint approximate diagonalization of eigen-matrices algorithm, which eliminates permutation indetermination and phase ambiguity, as well as the minimum description length algorithm, which blindly estimates the number of secret data sources. Simulation results show that both proposed methods can intercept information effectively. In addition, the proposed method without legitimate users' CSI performs well in terms of robustness and computational complexity.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.398-406
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• 2013

In this paper, we investigate two types of in-phase and quadrature-phase (IQ) data transfer methods for cloud multiple-input multiple-output (MIMO) network operation. They are termed "after-precoding" and "before-precoding". We formulate a cloud massive MIMO operation problem that aims at selecting the best IQ data transfer method and transmission strategy (beamforming technique, the number of concurrently receiving users, the number of used antennas for transmission) to maximize the ergodic sum-rate under a limited capacity of the digital unit-radio unit link. Based on our proposed solution, the optimal numbers of users and antennas are simultaneously chosen. Numerical results confirm that the sum-rate gain is greater when adaptive "after/before-precoding" method is available than when only conventional "after-precoding" IQ-data transfer is available.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.1029-1042
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• 2017

A joint channel estimation and data detection technique for a multiple input multiple output (MIMO) wireless communication system is proposed. It combines the least square (LS) training based channel estimation (TBCE) scheme with sphere decoding. In this new approach, channel estimation is enhanced with the help of blind symbols, which are selected based on their correctness. The correctness is determined via sphere decoding. The performance of the new scheme is studied through simulation in terms of the bit error rate (BER). The results show that the proposed channel estimation has comparable performance and better computational complexity over the existing semi-blind channel estimation (SBCE) method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5304-5322
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• 2018

Since designing a feedback topology is a practical way to implement interference alignment at reduced cost of channel state information (CSI) feedback, six feedback topologies have been presented in prior works for a K-user multiple-input multiple-output interference channel. To fully reveal the potential benefits of the feedback topology in terms of the saving of CSI overhead, we propose a new feedback topology in this paper. By efficiently performing dimensionality-decreasing at the transmitter side and aligning interference signals at a subset of receivers, we show that the proposed feedback topology obtains substantial reduction of feedback cost over the existing six feedback designs under the same antenna configuration.

• ETRI Journal
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• v.43 no.1
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• pp.17-30
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• 2021

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies-generalized Nash game and cooperative and noncooperative game theory.