• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.712-723
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• 2013

Recent exploration of smart-phone user is fueling the deployment of long term evolution (LTE) service that offers higher data rates service over 3G HSPA networks. In particular, Korea, mobile powerhouse, recently launched the service of LTE-Advanced (LTE-A) which is the latest release in LTE standard. Multiple-input-multiple-output (MIMO) technology is the one of key enablers for LTE and LTE-A for achieving high data rate. MIMO technology has received much attention since it is possible to achieve channel capacity in proportion to the number of antennas without increasing frequency and power. In this paper, we overview of the theoretical background of MIMO technology regarding from single-user MIMO, multiuser MIMO, and massive MIMO and design considerations to implement the communication system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.2998-3017
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• 2018

Massive (large-scale) MIMO (multiple-input multiple-output) is one of the key technologies in next-generation wireless communication systems. This paper proposes a high-performance low-complexity turbo receiver for SC-FDMA (single-carrier frequency-division multiple access) based MMIMO (massive MIMO) systems. Because SC-FDMA technology has the desirable characteristics of OFDMA (orthogonal frequency division multiple access) and the low PAPR (peak-to-average power ratio) of SC transmission schemes, the 3GPP LTE (long-term evolution) has adopted it as the uplink transmission to meet the demand high data rate and low error rate performance. The complexity of computing will be increased greatly in base station with massive MIMO (MMIMO) system. In this paper, a low-complexity adaptive turbo equalization receiver based on normalized minimal symbol-error-rate for MMIMO SC-FDMA system is proposed. The proposed receiver is with low complexity than that of the conventional turbo MMSE (minimum mean square error) equalizer and is also with better bit error rate (BER) performance than that of the conventional adaptive turbo MMSE equalizer. Simulation results confirm the effectiveness of the proposed scheme.

• ETRI Journal
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• v.42 no.1
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• pp.26-35
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• 2020

Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.7
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• pp.431-436
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• 2014

In this paper, we propose a compressive sensing-based channel quantization feedback mechanism that is appropriate for practical massvie multiple-input multiple-output (MIMO) systems. We assume that the base station (BS) has a compact uniform square array that has a highly correlated channel. To serve multiple users, the BS uses a zero-forcing precoder. Our proposed channel feedback algorithm can reduce the feedback overhead as well as a codebook search complexity. Numerical simulations confirm our analytical results.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.735-743
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• 2016

This paper proposes a direction-of-arrival (DOA)-based beamforming approach for multi-cell massive multiple-input multiple-output systems with uniform rectangular arrays (URAs). The proposed approach utilizes the steering vectors of the URA to form a basis of the spatial space and selects the partial space for beamforming according to the DOA information. As a result, the proposed approach is of lower computational complexity than the existing methods which utilize the channel covariance matrices. Moreover, the analysis demonstrates that the proposed approach can eliminate the interference in the limit of infinite number of the URA antennas. Since the proposed approach utilizes the multipaths to enhance the signal rather than discarding them, the proposed approach is of better performance than the existing low-complexity method, which is verified by the simulation results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.4006-4020
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• 2018

In recent years, one of the most remarkable 5G technologies is massive multiple-input and multiple-output (MIMO) system which increases spectral efficiency by deploying a large number of transmit-antennas (eg. tens or hundreds transmit-antennas) at base station (BS). However, conventional massive MIMO system using single-polarized (SP) transmit-antennas increases the size of the transmit-array proportionally as the number of transmit-antennas increases. Hence, size reduction of large-scale transmit-array is one of the major concerns of massive MIMO system. To reduce the size of the transmit-array at BS, dual-polarized (DP) transmit-antenna can be the solution to halve the size of the transmit-array since one collocated DP transmit-antenna deploys vertical and horizontal transmit-antennas compared to SP transmit-antennas. Moreover, proposed DP massive MIMO system increases the spectral efficiency by not only in the space domain but also in the polarization domain whereas the conventional SP massive MIMO system increases the spectral efficiency by space domain only. In this paper, the comparative performance of DP and SP massive MIMO systems is analyzed by space division multiple access (SDMA) and space-polarization division multiple access (SPDMA) respectively. To analyze the performance of DP and SP massive MIMO systems, DP and SP spatial channel models (SCMs) are proposed which consider depolarized propagation channels between transmitter and receiver. The simulation results show that the performance of proposed 32 transmitter (Tx) DP massive MIMO system improves the spectral efficiency by about 91% for a large number of user equipments (UEs) compare to 32Tx SP massive MIMO system for identical size of the transmit-array.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1630-1638
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• 2016

In this paper, we consider multiuser massive multiple-input and multiple-output (MIMO) system where multiusers simultaneously utilize massive antennas of base station (BS). With a downlink frame structure considering pilot signals, we derive the ergodic cell capacity based on zero-forcing beamforming (ZFBF) technique. This paper proves that the ergodic cell capacity is concave function with respect to the numbers of BS antennas and users, and derives the optimum numbers of BS antennas and users maximizing ergodic cell capacity. From the simulation results, it is shown that the derived numbers of BS antennas and users has the optimum value for the maximum ergodic cell capacity, and the ergodic cell capacity with the derived optimum values increases with respect to the transmit SNR(Signal to Noise Ratio).

• Journal of Advanced Information Technology and Convergence
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• v.8 no.2
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• pp.13-25
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• 2018

The paper analyzes the sum spectral efficiency (SE) for a heterogeneous cellular network (HetNet) which has the backhaul, provided with wireless full-duplex massive multiple-input multiple-out (MIMO) with hardware distortions. We derive approximate expressions to obtain the uplink/downlink sum SE of the backhaul. The analytic results have been shown to be exact when compared to Monte Carlo simulations. From the analysis, it is shown that the desired signal and the hardware distortion noise have the same order. The sum SE generally improves when the number of receive antennas increases but degrades when the hardware quality reduces. A sum SE performance ceiling is introduced by the hardware quality level.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.237-253
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• 2019

For massive multiple-input multiple-output (MIMO) circumstances with time division duplex (TDD) protocol, pilot contamination becomes one of main system performance bottlenecks. This paper proposes an uplink pilot sequence assignment to alleviate this problem for spatially correlated massive MIMO circumstances. Firstly, a single-cell TDD massive MIMO model with multiple terminals in the cell is established. Then a spatial correlation between two channel response vectors is established by the large-scale fading variables and the angle of arrival (AOA) span with an infinite number of base station (BS) antennas. With this spatially correlated channel model, the expression for the achievable system capacity is derived. To optimize the achievable system capacity, a problem regarding uplink pilot assignment is proposed. In view of the exponential complexity of the exhaustive search approach, a pilot assignment algorithm corresponding to the distinct channel AOA intervals is proposed to approach the optimization solution. In addition, simulation results prove that the main pilot assignment algorithm in this paper can obtain a noticeable performance gain with limited BS antennas.