• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.6
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• pp.86-93
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• 2009

We investigate lattice-reduction-aided precoding techniques for multi-user multiple-input multiple-output (MIMO) channels. When assuming full knowledge of the channel state information only at the transmitter, a vector perturbation (VP) is a promising precoding scheme that approaches sum capacity and has simple receiver. However, its encoding is nondeterministic polynomial time (NP)-hard problem. Vector perturbation using lattice reduction algorithms can remarkably reduce its encoding complexity. In this paper, we propose a vector perturbation scheme using Seysen's lattice reduction (VP-SLR) with simultaneously reducing primal basis and dual one. Simulation results show that the proposed VP-SLR has better bit error rate (BER) and larger capacity than vector perturbation with Lenstra-Lenstra-Lovasz lattice reduction (VP-LLL) in addition to less encoding complexity.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.826-835
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• 2014

Recently, spatial modulation (SM) schemes are considered to improve the reception performance in spatially correlated channel environments. SM schemes utilize a switching method between multiple transmitters to reduce the correlation among multiple transmitters to reduce the correlation of each received signals and can support transmission additional bits using antenna combinations without extra bandwidth. Therefore, SM schemes can overcome correlation interference of conventional MIMO in urban wireless channels. However, the performance comparisons between SM schemes are not yet performed in correlated urban wireless channels. In this paper, some representative SM schemes are compared and a suitable SM-MIMO system in correlated urban wireless channels is proposed.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.24 no.2
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• pp.95-101
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• 2011

In wireless X networks where all transmitters send the independent messages to all receivers, the theoretical bound on the degrees of freedom (DOF) and interference alignment (IA) scheme for its achievability are given by Cadambe and Jafar [1]. However, IA scheme for wireless X network may be infeasible in practice unless the transmitters have the perfect channel information. In addition, if the transmitter with single antenna uses time-varying channel coefficients as a beamforming vector, the infinite channel extension is required to achieve the theoretical bound on the DOF of wireless X networks with perfect IA scheme. In this paper, we consider K-user MIMO X network where K transmitters and K receivers have M antennas each. While the beamforming vectors have been constructed with multiple channel uses over multiple time slot in the earlier work, we consider the beamforming vectors constructed only by a spatial signature over unit time. Accordingly the channel information at the transmitters can be available instantaneously. Then we propose the perfect IA scheme with no channel extension. Based on our sum-rate analysis and the simulation results, we confirm that our proposed scheme can achieve MK/2 DOF which is quite close to the theoretical bound on the DOF region of wireless X networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.746-755
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• 2014

In this paper, we propose the structure of a dual polarized system for a wireless communication. The proposed dual polarized antenna is formed by one vertical antenna and two horizontal antennas that are orthogonal to each other. Vertical and horizontal polarized antennas transmit different signals, but two orthogonal horizontal polarized antennas transmit the same data signals. So, the signals of the proposed dual polarized system construct two dual-polarization planes. And, only one dual-polarization plane with a large signal power is selected at the side of a receiver. The simulation results show that the proposed dual polarized system could obtain a higher capacity compared to an ordinary $2{\times}2$ MIMO (Multi-input Multi-output) system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.40-48
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• 2015

This paper presents a processor that performs QR decomposition (QRD) as well as Lattice Reduction (LR) for multiple-input multiple-output (MIMO) systems. By sharing the operations commonly required in QRD and LR, the hardware complexity of the proposed processor is reduced significantly. In addition, the proposed processor is designed based on a multi-cycle architecture so as to reduce the hardware complexity. The proposed processor is implemented with 139k logic gates in a $0.18-{\mu}m$ CMOS process, and its latency is $5{\mu}s$ for $8{\times}8$ MIMO preprocessing both QRD and LR where the operating frequency is 117MHz.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.11
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• pp.33-39
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• 2014

We propose an optimal number of transmit antennas which maximizes energy-efficiency (EE) in multi-user massive multiple-input multiple-output (MIMO) downlink system with the maximal ratio transmission (MRT) precoding. With full channel state information at the transmitter (CSIT), we find a closed form solution by partial differential function with proper approximations using average channel gain, independence of individual channels, and average path loss. With limited feedback, we get a solution numerically by the bisection with approximations in the same manner, and analyze an effect of feedback bits on the optimal number of transmit antennas. Simulation results show that the optimal numbers of transmit antenna getting from proposed closed form solution and exhaustive search are nearly same.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.12
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• pp.579-587
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• 2014

This paper deals with precise analytical state equation modeling of a variable speed refrigeration system (VSRS) for optimum control in state space. The VSRS is described as multi-input and multi-output (MIMO) system, which has two controlled variables and two control inputs. First, the Navier-Stokes equation and mass flow rate were applied to each component of the basic refrigeration cycle to build a dynamic model. The dynamic model, represented by a differential equation, was transformed into the state equation formula. Next, a full-order state observer was built to estimate all of the state variables to compose an optimum control system. Then, an optimum controller was designed to minimize an evaluation function that has input energy and control error. Finally, simulations and experiments were conducted to verify the validity of the proposed modeling and designed optimum controller to regulate target temperature and superheat in a 1RT oil cooler system. The results show that the proposed method, state equation modeling and optimum control, is efficient to ensure optimal control performance of the VSRS.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.11 s.114
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• pp.1058-1064
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• 2006

In this paper, the channel capacity of a specified wireless indoor multiple-input multiple-output(MIMO) channel is estimated by analyzing spatial characteristics of this channel using the three-dimensional ray tracing method, and a technique for deriving an optimized separation of multi-antenna elements is proposed. At first, the ray paths, the path losses, and the time-delay profile are computed using the three-dimensional ray tracing method in an indoor corridor environment, which has the line of sight(LOS) and non-line of sight(NLOS) regions. The ray tracing method is verified by a comparison between the computation results and the measurements which are obtained with dipole antennas, an amplifier and a network analyzer. Then, an MIMO system is positioned in the indoor channel environment and the ray paths and path losses are computed for four antenna-position combinations and various values of the antenna separation to obtain the channel capacity for the MIMO system. An optimum antenna-separation is derived by averaging the channel capacities of 100 receiver positions with four different antenna combinations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.36-44
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• 2010

When multi-user MIMO (Multiple-Input Multiple-Output) systems utilize a sum-rate maximization (SRM) scheduler, the throughput of the systems can be enhanced. However, fairness problems may arise because users located near cell edge or experiencing poor channel conditions are less likely to be selected by the SRM scheduler. In this paper, a weighted sum-rate maximization (WSRM) scheduler is used to enhance the fairness performance of the MIMO systems. Closed-form expressions for the optimal transmit power allocation of WSRM and corresponding weighted sum-rate (WSR) are derived in the 6-sector collaborative transmission system. Using the derived results, we propose an algorithm which searches the optimal power allocation for WSRM in the 3-sector collaborative transmission system. Based on the derived closed-form expressions and the proposed algorithm, we perform computer simulations to compare performance of the WSRM scheduler and the SRM scheduler with respect to the sum-rate and the log-sum-of-average rates. We further verify that the WSRM scheduler efficiently improves fairness performance by showing the enhanced performance of average transmission rates in low percentile region.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.515-527
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• 2009

IEEE 802.11n is an ongoing next-generation WLAN(Wireless Local Area Network) standard that supports a very high-speed connection with more than 100Mb/s data throughput measured at the MAC(Medium Access Control) layer. Study trends of IEEE 802.11n show two aspects, enhanced data throughput using aggregation among packets in MAC layer, and better data rates adapting MIMO(Multiple-Input Multiple-Output) in PHY(Physical) layer. But, the former doesn't consider wireless channel and the latter doesn't consider aggregation among packets for reality. Therefore, this paper analyzes data throughput for IEEE 802.11n considering MAC and PHY connection. A-MPDU(Aggregation-MAC Protocol Data Unit) and A-MSDU(Aggregation-MAC Service Unit) is adapted considering multi-service in MAC layer, WLAN MIMO TGn channel using SVD(Singular Value Decomposition) is adapted considering MIMO and wireless channel in PHY layer. Consequently, Simulation results shows throughput between A-MPDU and A-MSDU. Also, We use Ns-2(Network simulator-2) for reality.