• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3458-3478
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• 2022

Automatic modulation recognition is the core algorithm in the field of modulation classification in communication systems. Our investigations show that deep learning (DL) based modulation recognition techniques have achieved effective progress for multiple-input multiple-output (MIMO) systems. However, network complexity is always an additional burden for high-accuracy classifications, which makes it impractical. Therefore, in this paper, we propose a low-complexity dimensional interactive lightweight network (DilNet) for MIMO systems. Specifically, the signals received by different antennas are cooperatively input into the network, and the network calculation amount is reduced through the depth-wise separable convolution. A two-dimensional interactive attention (TDIA) module is designed to extract interactive information of different dimensions, and improve the effectiveness of the cooperation features. In addition, the TDIA module ensures low complexity through compressing the convolution dimension, and the computational burden after inserting TDIA is also acceptable. Finally, the network is trained with a penalized statistical entropy loss function. Simulation results show that compared to existing modulation recognition methods, the proposed DilNet dramatically reduces the model complexity. The dimensional interactive lightweight network trained by penalized statistical entropy also performs better for recognition accuracy in MIMO systems.

• 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 Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.9-17
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• 2004

In this paper, we examine the MIMO(Multiple Input Multiple Output) system in the point of mobile communication that is used for railway environment. First, under the radio environment, wireless channel characteristics are analyzed between moving train and base station, both assuming track side base stations and non-track side base stations. Next, the paper introduces the MIMO system which can be used to solve the problem of performance degradation in railway environment, and analyzes its performance in terms of channel capacity and diversity. We especially compares open-loop scheme with closed loop scheme at the diversity and analyses their performance according to antenna correlation. Finally, the we presents experimental result from the ESCORT project that was studied in railway environment with the MIMO system.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.19-24
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• 2015

We introduce an optimization of the number of base station antennas in massive multiple-input multiple-output (MIMO) wireless powered communication network (WPCN). We use channel hardening property of massive MIMO system to approximate channel gain in terms of the number of base station antennas. Then, we find an optimal solution by partial differential and obtain a closed form solution by using Lambert-W function. The simulation results show that the approximation and the method of solving the optimization problem are reasonable, and the optimal solution of proposed scheme is almost identical to the optimal number of base station antennas by the exhaustive search method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2275-2284
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• 2015

In this paper, the Walsh coded orthogonal training signals for 4 × 4 multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems are designed and the channel estimation equations are derived as a closed form, taking account of the inter training signal interference problems caused by the multi-path delayed signals. The performances of the proposed channel estimation method are analyzed and compared with the conventional methods[9,14] by using computer simulation. The simulation results show that the proposed methods has better performances, compared with the conventional methods[9,14]. As a result, the proposed method can be used for MIMO-OFDM systems with null sub-carriers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11C
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• pp.932-939
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• 2008

Recently lattice-reduction (LR) has been used in signal detection for multiple-input multiple-output (MIMO) systems. The conventional LR aided detection schemes are combinations of LR and signal detection methods such as zero-forcing (ZF) and minimum mean square error (MMSE) detection. In this paper, we propose the Lattice-Reduction-aided scheme based on extended noise variance matrix to search good candidate symbol set in quantization step. Then this scheme estimates transmitted symbol with Semidefinite Relaxation by candidate symbol set. Simulation results in a random MIMO system show that the proposed scheme exhibits improved performance and a slight increase in complexity.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.639-648
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• 2016

Next-generation (4G) systems are designed to support universal frequency reuse (UFR) to achieve best use of valuable spectra. However, it leads to undesirable interference level near cell borders. To control this, 4G systems adopt techniques, such as network multiple-input multiple-output (MIMO) and inter-cell interference coordination (ICIC), to improve cell-edge throughput. Network MIMO aims at mitigating inter-cell interference towards cell-edge users (CEUs) through multi-cell cooperation, where each collaborative base station serves both cell-center users (CCUs) and CEUs, including other cells' CEUs, under a power constraint. The present ICIC strategies cannot be directly applied to network MIMO because they were designed in absence of multi-cell coordination. In the presence of network MIMO, this paper investigates antenna orientations in ICIC and the method of power management. Results show that a proper antenna orientation can improve the cell-edge capacity and meantime lower the interference to CCUs. Capacity inconsistency between CCUs and CEUs is detrimental to mobile communications. Simulation results show that the proposed power management for ICIC in network MIMO systems can achieve a uniform data rate regardless users' position.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4A
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• pp.337-344
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• 2011

In this paper, a multiple-input and multiple-output (MIMO) spatial multiplexing (SM) relay system is studied in a bit error rate (BER) sense, where every node is deployed with multiple antennas. In order to efficiently use the limited power resource, it is essential to optimally allocate the power to nodes and antennas. In this context, the power allocation (PA) algorithm based on minimum BER (MBER) for a MIMO SM relay system is proposed, which is derived by direct minimization of the average BER, and divided into inter-node and inter-antenna PA algorithm. The proposed scheme outperforms the conventional equal power allocation (EPA) algorithm without extra power consumption.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.878-883
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• 2018

A jamming design scheme to disturb target position estimation of a bistatic multiple-input multiple-output(MIMO) radar system is presented. The proposed method exploits the received signals from distributed multiple electronic sensors and combines them to produce a jamming signal. The proposed algorithm can eliminate the target by transmitting the delayed sum or the weighted sum of the received senor signals. Simulation results confirm the performance of the proposed method.