• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.108-122
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• 2014

Massive antenna array is an attractive candidate technique for future broadband wireless communications to acquire high spectrum and energy efficiency. However, such benefits can be realized only when proper channel information is available at the transmitter. Since the amount of the channel information required by the transmitter is large for massive antennas, the feedback is burdensome in practice, especially for frequency division duplex (FDD) systems, and needs normally to be reduced. In this paper a novel channel feedback reduction scheme based on the theory of distributed compressive sensing (DCS) is proposed to apply to massive antenna arrays with spatial correlation, which brings substantially reduced feedback load. Simulation results prove that the novel scheme is better than the channel feedback technique based on traditional compressive sensing (CS) in the aspects of mean square error (MSE), cumulative distributed function (CDF) performance and feedback resources saving.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1397-1404
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• 2015

Recently, high data rate transmission is required in maritime communication. In this paper, we consider multiple input multiple output (MIMO) spatial multiplexing (SM). However, the performance of SM is severly degraded due to spatial channel correlation and line-of-sight (LOS) component. In the maritime communication, the MIMO channel correlation and LOS are critical due to the lack of scatteres around the transmitter and/or the receiver. When the feedback of channel information is available, precoding can enhance the error performance by exploiting the channel information. However, it is difficult to derive closed-form solution considering both the correlation and LOS. In this paper, we present open-loop precoding-based spatial multiplexing transmission method by showing that the effect of performance for the correlation and LOS. It is shown that the open-loop precoding can mitigate the performance degradation due to the LOS as well as the correlation. Consequently, we expect that the proposed open-loop precoding can be adopted to the maritime communication system.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.8
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• pp.759-764
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• 2004

This paper proposes a method that estimates MIMO channel characteristics analytically using a 3D ray tracing propagation model. We calculate the discrete spatial correlation between sub-channels by considering phase differences of paths, and using this, estimate the mean capacity upper bound of MIMO channel by Jensen's inequality. This analysis model is a deterministic model that do not approach stochastically through measurement nor approach statistically through Monte-Carlo simulations, so this model has high efficiency for time and cost. And based on the electromagnetic theory, this model may analyze quantitatively the parameters which can affect the channel capacity - antenna pattern, polarization mutual coupling, antenna structure and etc. This model may be used for the development of an optimal antenna structure for MIMO systems.

• Journal of the Korea Institute of Military Science and Technology
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• v.20 no.3
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• pp.369-375
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• 2017

One of good DF(Direction Finding) methods is based on TDOA(Time Difference of Arrival) estimation when finding underwater moving target. For small DF error, high time resolution A/D(Analog-to-digital) conversion board and long baseline are needed. But the result of sea trial about close-range and high speed moving target, spatial correlation coefficient and appeared poor properties below 0.3 when hydrophone arrangement are separated over 6 ${\lambda}$ because of underwater fading channel. And we also find out that the distance between hydrophone should be under 4 ${\lambda}$ apart to take advantage of spatial correlation coefficient gain and performance of DF in underwater moving channel environments.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.95-104
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• 2016

Massive multiple-input multiple-output (MIMO) is a promising approach for cellular communication due to its energy efficiency and high achievable data rate. These advantages, however, can be realized only when channel state information (CSI) is available at the transmitter. Since there are many antennas, CSI is too large to feed back without compression. To compress CSI, prior work has applied compressive sensing (CS) techniques and the fact that CSI can be sparsified. The adopted sparsifying bases fail, however, to reflect the spatial correlation and channel conditions or to be feasible in practice. In this paper, we propose a new sparsifying basis that reflects the long-term characteristics of the channel, and needs no change as long as the spatial correlation model does not change. We propose a new reconstruction algorithm for CS, and also suggest dimensionality reduction as a compression method. To feed back compressed CSI in practice, we propose a new codebook for the compressed channel quantization assuming no other-cell interference. Numerical results confirm that the proposed channel feedback mechanisms show better performance in point-to-point (single-user) and point-to-multi-point (multi-user) scenarios.

• Journal of information and communication convergence engineering
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• v.16 no.1
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• pp.38-42
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• 2018

In this paper, we consider measurement allocation problem in a spatially correlated sensor field. Our goal is to determine the probability of each sensor's being measured based on its contribution to the estimation reliability; it is desirable that a sensor improving the estimation reliability is measured more frequently. We consider a spatial correlation model of a sensor field reflecting transmission power limit, noise in measurement and transmission channel, and channel attenuation. Then the estimation reliability is defined distortion error between event source and its estimation at sink. Motivated by the correlation nature, we model the measurement allocation problem into a cooperative game, and then quantify each sensor's contribution using Shapley value. Against the intractability in the computation of exact Shapley value, we deploy a randomized method that enables to compute the approximate Shapley value within a reasonable time. Besides, we envisage a measurement scheduling achieving the balance between network lifetime and estimation reliability.

• Korean Journal of Remote Sensing
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• v.17 no.4
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• pp.335-344
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• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9A
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• pp.767-775
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• 2011

In this paper, we propose a new multi-input multi-output (MIMO) channel modeling method for mobile-to-mobile (M2M) communications based on IEEE 802.16n. To reflect the mobilities at the transmitter and the receiver, we propose a new channel model by invoking the geometrical two-ring scattering model and modifying the conventional IEEE 802.16m fixed-to-mobile (F2M) channel model considering M2M communication environments. Through computer simulations, we analyze the statistical properties of proposed channel model in terms of the time correlation and the spatial correlation. Finally, the performance of the system using the proposed M2M channel model is compared with that using the conventional 802.16m F2M channel model by link level simulations.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.8
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• pp.748-757
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• 2015

MIMO systems utilizing multiple antenna transmission and reception is one of the key technologies to enhance the capacity of 5G wireless communications. In order to obtain an appropriate performance evaluation of MIMO techniques, the usage of wireless channel model reflecting spatial channel characteristics is required, such as the 3-dimensional spatial channel model(3D SCM) proposed by 3GPP TR36.873 documentation. In this paper, we implement and verify the channel simulation environment based on 3D SCM, to present and compare the characteristics of UMi and UMa environments. We also apply MIMO transmission to the UMa scenario to investigate the channel correlation among antenna elements with different array distances and to identify the corresponding throughput changes. By evaluating the channel power correlations for randomly distributed users within the sector for different horizontal and vertical antenna distances, we present the statistical characteristics which determine the transmission performance under the SCM environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6A
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• pp.563-574
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• 2006

This paper implements SCM(Spatial Channel Model), a kind of ray-tracing method which has characteristics similar to realistic wave propagation environments, for link-level performance analysis of OFDM(Orthogonal Frequency Division Multiplexing) based multiple antenna systems. The SCM is proposed by 3GPP & 3GPP2 Spatial Channel AHG(Ad-hoc Group) for system-level performance validation. In this paper, we modify the system level parameters and channel coefficient of SCM to compare the link-level performances of OFDM based multiple antenna systems. Through computer simulations, we manifest the implemented SCM channel characteristics. We analyze a realistic link-level performance of OFDM based conventional MIMO(Multiple Input Multiple Output) system and smart antenna system in the implemented channel. We also include the link-level performance of OFDM based multiple antenna systems in I-METRA(Intelligent Multi Element Transmit and Receive Antenna) and independent channel environments with the same system parameters. We suggest appropriate multiple antenna system in the given environment by comparing the link-level performance in the spatial channels that have different channel correlation values.