• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.8
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• pp.1485-1491
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• 2015

This paper introduces a new pilot assignment algorithm for uplink Massive multiple-input multiple-output (MIMO) systems. Since the conventional pilot assignment algorithm has the performance degradation compared to the optimal algorithm which performs the exhaustive search, we propose a new pilot assignment algorithm using Pre-determined Interference and Pre-determined Desired-term techniques. The proposed algorithm has the low complexity and guarantees negligible performance loss compared to the optimal algorithm. Simulation result verifies that the proposed algorithm achieves a large performance gain over the conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4214-4230
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• 2020

This paper introduces a pilot allocation scheme for massive MIMO systems based on deep convolutional neural network (CNN) learning. This work is an extension of a prior work on the basic deep learning framework of the pilot assignment problem, the application of which to a high-user density nature is difficult owing to the factorial increase in both input features and output layers. To solve this problem, by adopting the advantages of CNN in learning image data, we design input features that represent users' locations in all the cells as image data with a two-dimensional fixed-size matrix. Furthermore, using a sorting mechanism for applying proper rule, we construct output layers with a linear space complexity according to the number of users. We also develop a theoretical framework for the network capacity model of the massive MIMO systems and apply it to the training process. Finally, we implement the proposed deep CNN-based pilot assignment scheme using a commercial vanilla CNN, which takes into account shift invariant characteristics. Through extensive simulation, we demonstrate that the proposed work realizes about a 98% theoretical upper-bound performance and an elapsed time of 0.842 ms with low complexity in the case of a high-user-density condition.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.9
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• pp.965-970
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• 2010

Because of a large number of subcarriers, the high PAPR(Peak-to-Average Power Ratio) is the major drawback of NC-OFDM system used for wireless communication system. Comb type pilot assignment is more efficient and lower computational complexity for the channel estimation than the block type pilot. However, even if the CAZAC(Constant Amplitude Zero Autocorrelation) matrix transform is used for the PAPR reduction of the data symbols, PAPR increases when the pilot is inserted in comb type with the data symbols. Therefore, in this paper, we additionally use a new SLM technique in order to lower the PAPR again even in the comb type pilot. Also, a new SLM technique suggested in this paper does not need any additional bandwidth for sending selection information for SLM. This combined method has good PAPR reduction performance and efficient data transmission.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.8
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• pp.2797-2820
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• 2015

In order to accommodate huge number of antennas in a limited antenna size, a large scale antenna array is expected to have a three dimensional (3D) array structure. By using the Active Antenna Systems (AAS), the weights of the antenna elements arranged vertically could be configured adaptively. Then, a degree of freedom (DOF) in the vertical plane is provided for system design. So the three-dimension MIMO (3D MIMO) could be realized to solve the actual implementation problem of the massive MIMO. However, in 3D massive MIMO systems, the pilot contamination problem studied in 2D massive MIMO systems and the inter-cell interference as well as inter-vertical sector interference in 3D MIMO systems with vertical sectorization exist simultaneously, when the number of antenna is not large enough. This paper investigates the interference management towards the above challenges in 3D massive MIMO systems. Here, vertical sectorization based on vertical beamforming is included in the concerned systems. Firstly, a cooperative joint vertical beams adjustment and pilot assignment scheme is developed to improve the channel estimation precision of the uplink with pilots being reused across the vertical sectors. Secondly, a downlink interference coordination scheme by jointly controlling weight vectors and power of vertical beams is proposed, where the estimated channel state information is used in the optimization modelling, and the performance loss induced by pilot contamination could be compensated in some degree. Simulation results show that the proposed joint optimization algorithm with controllable vertical beams' weight vectors outperforms the method combining downtilts adjustment and power allocation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.1-7
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• 2010

PAPR of the pilot symbols can be reduced down by the CAZAC sequence in the SC-FDMA communication system. However, it is very complicated and takes quite a long time to compute the interpolation between the OFDM information symbols for the channel estimation because the pilot data are trasmitted in the block type. Furthermore, situation will be much more serious in the severe fading channel. Actually the pilot insertion of the comb type is much efficient and convenient for the channel estimation since the calculation of the interpolation can be made in the frequency domain symbol by symbol. But, the PAPR will be regrown when the pilot data are inserted with the information data in the comb type. So, in this paper, we like to study the PAPR reduction and comb type pilot assignment for the efficient channel estimation. Unlike the conventional SLM(selected mapping) method requiring the side information, our improved SLM method is to use the phase rotation sequence into information data without rotating phase of pilot. We use different pilot data according to the different phase rotation sequence. From the simulation result, it can be confirmed that when SLM method of 4 phase rotation sequence is used, PAPR is almost same to the block type method without pilot.

• Journal of IKEEE
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• v.16 no.3
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• pp.258-264
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• 2012

Although linear channel estimation for the frequency selective fading channel has been widely deployed, its accuracy depends on the number of pilots to probe the channel. Thus, it is unavoidable to employ large number of pilots to enhance the channel estimation performance, which essentially leads to the degradation of the transmission efficiency. It even does not utilize the sparseness of the multipath channel. In this paper a sparse channel estimation scheme based on the matching pursuit algorithm and a pilot assignment method, which minimizes the coherence, are proposed. The simulation results reveal that the proposed algorithm shows superior channel estimation performance with fewer pilots to the LS based ones.

• Journal of the Korean Magnetic Resonance Society
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• v.11 no.2
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• pp.73-84
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• 2007

MTH1821 (UniProtKB/TrEMBL ID O27849) is a 96-residue hypothetical protein from the open reading frame of Methanobacterium thermoautotrophicum H one of the target organisms of structural genomics pilot project. Proteins which contain conserved sequence compared with MTH1821 have not been discovered yet and the functional and structural information for MTH1821 is not available. Here, we present the sequence-specific backbone resonance using multidimensional heteronuc1ear NMR spectroscopy and propose the secondary structure using GetSBY software. The backbone resonances of N, HN, $C_{\alpha}$, $C_{\beta}$, CO and $H_{\alpha}$ which are necessary for a prediction of secondary structure by GetSBY were assigned about 98% (557/568). The secondary structure of MTH1821 confirmed that it is comprised of four strand regions and two helical regions. This report will provide a valuable resource for the calculation solution structure of MTH1821 and for the other hypothetical protein that is targeted for structural-based functional discovery.

• Journal of Korea Multimedia Society
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• v.13 no.11
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• pp.1667-1676
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• 2010

In this paper, we propose a packet scheduling algorithm that assigns different number of HS-PDSCH(High Speed Primary Downlink Shared Channel) to the service user according to the received signal to interference ratio of CPICH(Common Pilot Channel) and to the traffic characteristics. Assigned channel number is determined by the signal to interference ratio level from CPICH. The highest signal to interference ratio user gets the number of channels based on the signal to interference ratio table and the remained channels are assigned to the other level users. Therefore the proposed scheme can provide the similar maximum service throughput and higher fairness than existing scheduling algorithm. Simulation results show that our algorithm can provide the similar maximum service throughput and higher fairness than MAX C/I algorithm and can also support the higher service throughput than proportional fairness scheme.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.1
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• pp.143-148
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• 2023

Currently, pilots and tugs perform the function of minimizing or eliminating property damage by preventing accidents on ships, ports, and human life by supporting docking/unloading and access and departure of ships. The piloting/tuging system is an essential function for the smooth functioning of the port, and it is the system that has the greatest influence on the cargo volume of the port. In this study, we developed an pilot and tugs information system analysis and operating system that can improve port operation efficiency, reduce the waiting time of ships, optimize the operation of ships, and allocate optimal pilots and tugs by utilizing the operation information of the tugbosts.