• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.7
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• pp.1249-1254
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• 2016

Recently, there have been many researches which can achieve high data rate in multi-user massive MIMO networks while reducing the complexity in terms of both hardware and algorithm. In addition, many researches have been conduced to reduce the energy consumption in next generation mobile communication networks. In this paper, we thus investigated new transmit antenna selection scheme to achieve low computational complexity and enhance energy efficiency in multi-user massive MIMO networks. First, we introduced the optimal scheme based on Brute-Force searching to maximize the energy efficiency and then proposed new antenna selection scheme to dramatically reduce the computational complexity compared to the optimal scheme. As the number of transmit antennas increases, the complexity of the optimal scheme exponentially increases while the complexity of the proposed scheme linearly increases. Nevertheless, the energy efficiency performance gap between proposed and optimal schemes is not huge.

• Journal of Communications and Networks
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• v.15 no.4
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• pp.338-351
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• 2013

Multiple-input multiple-output (MIMO) communication may provide high spectral efficiency through the deployment of a very large number of antenna elements at the base stations. The gains from massive MIMO communication come from the use of multi-user MIMO on the uplink and downlink, but with a large excess of antennas at the base station compared to the number of served users. Initial work on massive MIMO did not fully address several practical issues associated with its deployment. This paper considers the impact of channel aging on the performance of massive MIMO systems. The effects of channel variation are characterized as a function of different system parameters assuming a simple model for the channel time variations at the transmitter. Channel prediction is proposed to overcome channel aging effects. The analytical results on aging show how capacity is lost due to time variation in the channel. Numerical results in a multicell network show that massive MIMO works even with some channel variation and that channel prediction could partially overcome channel aging effects.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1055-1062
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• 2022

In order to use the Massive MIMO (Multi Input Multi Output) technology using the massive array antenna, it is essential to know the angle of arrival (AOA) of the signal. When using a massive array antenna, the existing AOA estimation algorithm has excellent estimation performance, but also has a disadvantage in that computational complexity increases in proportion to the number of antenna elements. To solve this problem, a cascade AOA estimation algorithm has been proposed and the performance of a single-shaped (non)massive array antenna has been proven through a number of papers. However, the computational complexity of the cascade AOA estimation algorithm to which single and double rim array antennas are applied has not been compared. In this paper, we compare and analyze the computational complexity for AOA estimation when single and double rim array antennas are applied to the cascade AOA estimation algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.5
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• pp.57-62
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• 2020

The millimeter wave that uses the spectrum in the 30GHz~300GHz band has a shorter wavelength due to its high carrier frequency, so it is suitable for Massive MIMO systems because more antennas can be equipped in the base station. However, since an RF chain is required per antenna, hardware cost and power consumption increase as the number of antennas increases. Therefore, in this paper, we investigate antenna selection schemes to solve this problem. In order to solve the problem of high computational complexity in the exhaustive search based antenna selection scheme, we propose a approach of applying deep learning technology. An best antenna combination is predicted using a DNN model capable of classifying multi-classes. By simulation tests, we compare and evaluate the existing antenna selection schemes and the proposed deep learning-based antenna selection scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1354-1362
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• 2015

Heterogeneous network technology is expected to be a core technology for 5G mobile communications. 5G mobile network would be composed of many base stations even have mobility, then the operator should connect base stations through the wireless backhaul technology. This paper presents Ultra Wide Area Wireless Backhaul Network System with massive array antenna. We conducted link budget analysis for Ultra Wide Area Wireless Backhaul Network and performance analysis of massive array antenna system through the transmission simulator based on beamforming technology. In wide area ($10km^2$) wireless backhaul system composed of massive antenna, we achieved 5 bps/Hz average spectral efficiency with 1 W transmission power per beam.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1559-1565
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• 2021

In this paper, an antenna selection scheme is proposed in massive multi-user multiple input multiple output (MU-MIMO) systems. The proposed antenna selection scheme can achieve almost the same performance as a conventional scheme while significantly reducing the overhead of feedback by using deep reinforcement learning (DRL). Each user compares the channel gains of massive antennas in base station (BS) to the L-largest channel gain, converts them to one-bit binary numbers, and feed them back to BS. Thus, the feedback overhead can be significantly reduced. In the proposed scheme, DRL is adopted to prevent the performance loss that might be caused by the reduced feedback information. We carried out extensive Monte-Carlo simulations to analyze the performance of the proposed scheme and it was shown that the proposed scheme can achieve almost the same average sum-rates as a conventional scheme that is almost optimal.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.3
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• pp.216-221
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• 2013

In this paper, wireless channel characteristics of massive MIMO system is analyzed by comparing angular spread, cross polarization discrimination(XPD) and delay spread of dual polarized 4 and 128 transmit array antenna systems, by using 3D rat-tracing simulator, Wireless Insite in microcell environments. The analysis shows that increasing the number of transmit antennas results in the smaller angular spread and delay spread, and the higher value of XPD.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.261-279
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• 2023

In this article, the uplink achievable rate is investigated for massive multiple-input multiple-output (MIMO) under correlated Ricean fading channel, where each base station (BS) and user are both deployed multiple antennas. Considering the availability of prior knowledge at BS, two different channel estimation approaches are adopted with and without prior knowledge. Based on these channel estimations, a two-layer decoding scheme is adopted with maximum ratio precoding as the first layer decoder and optimal second layer precoding in the second layer. Based on two aforementioned channel estimations and two-layer decoding scheme, the exact closed form expressions for uplink achievable rates are computed with and without prior knowledge, respectively. These derived expressions enable us to analyze the impacts of line-of-sight (LoS) component, two-layer decoding, data transmit power, pilot contamination, and spatially correlated Ricean fading. Then, numerical results illustrate that the system with spatially correlated Ricean fading channel is superior in terms of uplink achievable rate. Besides, it reveals that compared with the single-layer decoding, the two-layer decoding scheme can significantly improve the uplink achievable rate performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.286-287
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• 2019

In this paper, we consider an amplify-and-forward (AF) full duplex (FD) massive-antenna relay (or base station) aiding communication between K single-antenna source and destination pairs whose transmissions are overheard by one single-antenna eavesdropper. Maximum ratio combining (MRC) and maximum ratio transmission (MRT) processing is employed at the relay. The secrecy performance of the system is then derived with both relay and destination being equipped with low resolution analog-to-digital converters (ADCs). The results show the detrimental effect of the eavesdropper's presence on the sum rate of the system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.3068-3078
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• 2015

Although the massive MIMO system supports a high throughput, it requires a lot of channel information for channel compensation. For the reduction of overhead, the massive MIMO system generally uses TDD as duplexing scheme. Therefore, the massive MIMO system is sensitive to rapidly changing fast fading in according to time. For the improvement of reduced SINR by fast fading, the adaptive power control is proposed. Unlike the conventional scheme, the proposed scheme considers mobility of device for adaptive power control. The simulation of the proposed scheme is performed with consideration for mobility of device. The result of the simulation shows that the proposed scheme improves SINR. Since SINR is decreased in according to the number of device in the network by unit of cell, each base station can accommodate more devices by the proposed scheme. Also, because the massive MIMO system with high SINR can use high order modulation scheme, it can support higher throughput.