• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2893-2907
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• 2019

Wireless mobile communication systems in subway tunnels have been widely researched these years, due to increased demand for the communication applications. As a result, an accurate model is essential to effectively evaluate the communication system performance. Thus, a neoteric three-dimensional (3D) geometry-based stochastic model (GBSM) is proposed for the massive multiple-input multiple-output (MIMO) fading channels in tunnel environment. Furthermore, the statistical properties of the channel such as space-time correlation, amplitude and phase probability density are analyzed and compared with those of the traditional two-dimensional (2D) model by numerical simulations. Finally, the ergodic capacity is investigated based on the proposed model. Numerical results show that the proposed model can describe the channel in tunnels more practically.

• ETRI Journal
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• v.41 no.4
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• pp.426-436
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• 2019

In time division duplex (TDD)-based multiuser massive multiple input multiple output (MIMO) systems, the uplink channel is estimated and the results are used in downlink for signal detection. Owing to noisy uplink channel estimation, the downlink channel should also be estimated for accurate signal detection. Therefore, recently, a blind method was developed, which assumes the use of a linear high-power amplifier (HPA) in the base station (BS). In this study, we extend this method to a scenario with a nonlinear HPA in the BS, where the Bussgang decomposition is used for HPA modeling. In the proposed method, the average power of the received signal for each user is a function of channel gain, large-scale fading, and nonlinear distortion variance. Therefore, the channel gain is estimated, which is required for signal detection. The performance of the proposed method is analyzed theoretically. The simulation results show superior performance of the proposed method compared to that of the other methods in the literature.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.861-869
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• 2014

This paper shows the research of a platform architecture relates to the LTE-based macro basestation; the proposed platform architecture is designed with the interface between the baseband signal and IF (Intermediate Frequency) per codeword. Using this method, we can smoothly transmit/receive a large amounts of data regardless of the number of antenna in a macro base station which is used technology such as massive MIMO. In this paper, We analyzed the evolution of LTE technology and the trend in the development of the LTE-based system. For validation of the proposed architecture, we compare the general architecture of a conventional with the proposed architecture. From the calculation results of transmission quantity data, we see that the proposed architecture can give better performance than the existing architecture. By presenting this architecture, we hope to provide a new foundation for Design and Implementation of a LTE base station platform which is used technology such as massive MIMO, carrier aggregation (CA), coordinated multi point (CoMP).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.2
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• pp.274-279
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• 2021

Since conventional massive antenna systems require too many RF chains, they have disadvantages of high implementation cost and complexity. To overcome this problem, hybrid precoding schemes have been proposed. But, they are still of high implementation cost and complexity because RF chains are connected to all antenna elements. In this paper, we consider massive MIMO systems with overlapped sub-array (OSA) structure and then, propose a hybrid precoding scheme. In the overlapped subarray structure, RF analog precoding matrix has a sparse structure where many elements of RF analog precoding matrix are zeros. Using this sparse property, we propose a GTP-based precoder design method for RF and baseband digital precoding. Through simulation, we show that the proposed scheme has more than 85% of the spectral efficiency of the fully-connected structure while having 20~30% of complexity of it.

• 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.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.704-711
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• 2013

Applying channel state information feedback scheme based on codebook for FDD downlink MIMO system to massive MIMO system directly causes following two problems. First, codebook generation becomes hard because resources needed for codebook generation increases exponentially in the number of antennas. In addition, long time is needed for channel state information feedback because users's codebook search time increases linearly in the number of antennas. This paper proposes a codebook generation scheme and a codebook search scheme which can reduce resource for codebook generation and codebook search time drastically though they have similar performance as conventional approaches.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.58-67
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• 2020

In this paper, we propose a data-driven-based beam selection scheme for massive multiple-input and multiple-output (MIMO) systems in ultra-dense networks (UDN), which is capable of addressing the problem of high computational cost of conventional coordinated beamforming approaches. We consider highly dense small-cell scenarios with more small cells than mobile stations, in the millimetre-wave band. The analog beam selection for hybrid beamforming is a key issue in realizing millimetre-wave UDN MIMO systems. To reduce the computation complexity for the analog beam selection, in this paper, two deep neural network models are used. The channel samples, channel gains, and radio frequency beamforming vectors between the access points and mobile stations are collected at the central/cloud unit that is connected to all the small-cell access points, and are used to train the networks. The proposed machine-learning-based scheme provides an approach for the effective implementation of massive MIMO system in UDN environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.160-162
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• 2014

네트워크 급속발전 때문에 기지국 용량이 부족하다는 문제가 커지고 있다. 일반 기지국은 기지국에서 신호처리를 하지만 클라우드 기지국은 신호를 전부 클라우드 컴퓨팅 플랫폼(Cloud Computing Platform)에 전송해서 집중처리한다. 이러한 기술을 통해 에너지 절약과 원가 절약하고 컴퓨팅의 효율을 최대화한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.469-477
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• 2015

In this paper, joint spatial division and reuse (JSDR) scheme is proposed for maximizing network throughput in densely-deployed wireless local area networks equipped with massive antenna array. The proposed JSDR scheme divides the massive spatial space into two subspaces: one is for suppressing the interference from the neighboring access points and another is for sensing the carrier sensing and transmitting the information-bearing signals to intended stations. By using computer simulation, the proposed JSDR can provide 133% higher network throughput, compared to the carrier sensing technique defined in the IEEE 802.11 standard so that the proposed JSDR is suitable for the next generation WLAN systems.