• Nonlinear Functional Analysis and Applications
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• v.28 no.2
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• pp.497-520
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• 2023

Numerous problems in science and engineering defined by nonlinear functional equations can be solved by reducing them to an equivalent fixed point problem. Fixed point theory provides essential tools for solving problems arising in various branches of mathematical analysis, such as split feasibility problems, variational inequality problems, nonlinear optimization problems, equilibrium problems, complementarity problems, selection and matching problems, and problems of proving the existence of solution of integral and differential equations.The theory of fixed is known to find its applications in many fields of science and technology. For instance, the whole world has been profoundly impacted by the novel Coronavirus since 2019 and it is imperative to depict the spread of the coronavirus. Panda et al. [24] applied fractional derivatives to improve the 2019-nCoV/SARS-CoV-2 models, and by means of fixed point theory, existence and uniqueness of solutions of the models were proved. For more information on applications of fixed point theory to real life problems, authors should (see [6, 13, 24] and the references contained in).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.205-207
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• 2020

This paper proposes a novel deep learning-based method to upsample a depth map. Most conventional methods estimate high-resolution depth map by modifying pixel value of given depth map using high-resolution color image and low-resolution depth map. However, these methods cause under- or over-shooting problems that restrict performance improvement. To overcome these problems, the proposed method iteratively performs grid warping scheme which shifts pixel values to restore blurred image for estimating high-resolution depth map. Experimental results show that the proposed method improves both quantitative and visual quality compared to the existing method.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.361-366
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• 2015

The objective of this paper was to establish the attributes that determines neighbourhood satisfaction in South Africa lowincome housing subsidy scheme ultilising the Delphi approach. This is because the perception and housing satisfaction of lowincome housing beneficiaries toward their housing condition can be studied by examining their satisfaction toward s the neighbourhood factors. The Delphi method was used where the views of housing experts were solicited on 26 potential attributes as identified from li terature. Consensus was achieved after three iterative rounds. The expert"s scored each attributes on a 10-point ordinal scale of impact significance, where 1-2=No impact and 9-10= very high impact. The scales adapted for consensus were: strong consensus, median 9-10, inter quartile deviation (IQD) ≤1; good consensus, median 7 ≤ 6.99and IQD≥2.1≤3. The key findings indicate that there was a good to strong consensus of 19 attributes which were key attributes that the experts perceived as determinants of neighbourhood satisfaction; while 6 other attributes had weak consensus, as they were considered to have a le sser impact in determining residents" neighbourhood satisfaction. However, attributes with weak consensus were the attributes that are highly regarded as core neighbourhood factors in other housing settings. The study contributes to the body of knowledge on th e subject where no consensus has been reached pertaining to indicators for measuring neighbourhood satisfaction in subsidised low-income housing in South Africa.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.2047-2066
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• 2024

In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.207-215
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• 2011

A signal passed through multi-path channel suffers ISI(Inter-Symbol Interference) and severe distortions caused by channel delay spread and noise components at the SC-FDE(Single Carrier with Frequency Domain Equalizer) transmission. Conventional UW(Unique-Word) based SC-FDE iterative channel estimation improves channel estimation performance by smoothing estimated CIR(Channel Impulse Response) of the noise components outside the channel length at time domain and restoring the broken cyclic property through UW reconstruction. In this paper, we propose channel estimation scheme through noise suppression within channel length. To suppress the noise, we estimate noise standard deviation as estimated CIR of the noise components outside the channel length and make criteria of the noise standard deviation gain that doesn't affect the original signal samples. When estimated CIR samples within channel length are less than the criteria value using the noise standard deviation and gain, the noise components are removed. Simulation results show that the proposed channel estimation scheme brings good channel MSE(Mean Square Error) and good BER(Bit Error Rate) performance.

• Journal of Internet Computing and Services
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• v.8 no.4
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• pp.61-70
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• 2007

In this paper, we propose and observe the Adaptive Modulation system with optimal Turbo Coded V-BLAST(Vertical-Bell-lab Layered Space-Time) technique that is applied the extrinsic information from MAP Decoder in decoding Algorithm of V-BLAST: ordering and slicing. And comparing the proposed system with the Adaptive Modulation system using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme, we observe how much throughput performance and SNR has been improved. In addition, we show that the proposed system using STD(Selection Transmit Diversity) scheme results in on improved result, By using simulation and comparing to conventional Turbo Coded V-BLAST technique with the Adaptive Modulation systems, the optimal Turbo Coded V-BLAST technique with the Adaptive Modulation systems has SNR gain over all SNR range and better throughput gain that is about 350Kbps in 11dB SNR range. Also, comparing with the conventional Turbo Coded V-BLAST technique using 2 transmit and 2 receive antennas, the proposed system with STD scheme show that the improvement of maximum throughput is about 1.77Mbps in the same SNR range and the SNR gain is about 5.88dB to satisfy 4Mbps throughput performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.1
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• pp.1-10
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• 2002

A space-time concatenated convolutional and differential coding scheme is employed in a multiuser direct-sequence code-division multiple-access(DS-CDMA) system. The system consists of single-user detectors (SUD), which are used to suppress multiple-access interference(MAI) with no requirement of other users' spreading codes, timing, or phase information. The space-time differential code, treated as a convolutional code of code rate 1 and memory 1, does not sacrifice the coding efficiency and has the least number of states. In addition, it brings a diversity gain through the space-time processing with a simple decoding process. The iterative process exchanges information between the differential decoder and the convolutional decoder. Numerical results show that this space-time concatenated coding scheme provides better performance and more flexibility than conventional convolutional codes in DS-CDMA systems, even in the sense of similar complexity Further study shows that the performance of this coding scheme applying to DS-CDMA systems with SUDs improves by increasing the processing gain or the number of taps of the interference suppression filter, and degrades for higher near-far interfering power or additional near-far interfering users.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.6 s.360
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• pp.40-47
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• 2007

In this paper, we propose and analyze the Adaptive Modulation System with optimal Turbo Coded V-BLAST(Vertical-Bell-lab Layered Space-Time) technique that adopts the extrinsic information from MAP (Maximum A Posteriori) Decoder with Iterative Decoding as a priori probability in two decoding procedures of V-BLAST; the ordering and the slicing. Also, we consider and compare the Adaptive Modulation System using conventional Turbo Coded V-BLAST technique that is simply combined V-BLAST with Turbo Coding scheme and the Adaptive Modulation System using conventional Turbo Coded V-BLAST technique that is decoded by the ML (Maximum Likelihood) decoding algorithm. We observe a throughput performance and a complexity. As a result of a performance comparison of each system, it has been proved that the complexity of the proposed decoding algorithm is lower than that of the ML decoding algorithm but is higher than that of the conventional V-BLAST decoding algorithm. however, we can see that the proposed system achieves a better throughput performance than the conventional system in the whole SNR (Signal to Noise Ratio) range. And the result shows that the proposed system achieves a throughput performance close to the ML decoded system. Specifically, a simulation shows that the maximum throughput improvement in each MIMO scheme is respectively about 350 kbps, 460 kbps, and 740 kbps compared to the conventional system. It is suggested that the effect of the proposed decoding algorithm accordingly gets higher as the number of system antenna increases.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.6
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• pp.66-74
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• 2010

Recently distributed video coding (DVC) is spotlighted for the environment which has restriction in computing resource at encoder. Wyner-Ziv (WZ) coding is a representative scheme of DVC. The WZ encoder independently encodes key frame and WZ frame respectively by conventional intra coding and channel code. WZ decoder generates side information from reconstructed two key frames (t-1, t+1) based on temporal correlation. The side information is regarded as a noisy version of original WZ frame. Virtual channel noise can be removed by channel decoding process. So the performance of WZ coding greatly depends on the performance of channel code. Among existing channel codes, Turbo code and LDPC code have the most powerful error correction capability. These channel codes use stochastically iterative decoding process. However the iterative decoding process is quite time-consuming, so complexity of WZ decoder is considerably increased. Analysis of the complexity of LPDCA with real video data shows that the portion of complexity of LDPCA decoding is higher than 60% in total WZ decoding complexity. Using the HDA (Hard Decision Aided) method proposed in channel code area, channel decoding complexity can be much reduced. But considerable RD performance loss is possible according to different thresholds and its proper value is different for each sequence. In this paper, we propose an adaptive HDA method which sets up a proper threshold according to sequence. The proposed method shows about 62% and 32% of time saving, respectively in LDPCA and WZ decoding process, while RD performance is not that decreased.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.12
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• pp.1250-1260
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• 2014

In this paper, a novel resource scheduling, which is used for hub network based long distance airborne tactical communication, is proposed. Recently, some countries of the world has concentrated on developing data rate and networking performance of CDL, striving to keep pace with modern warfare, which is changed into NCW. And our government has also developed the next generation high capacity CDL. In hub network, a typical communication structure of CDL, hybrid FDMA/TDMA can be considered to exchange high rate data among multiple UAVs simultaneously, within limited bandwidth. However, due to different RTT and traffic size of UAV, idle time resource and unnecessary packet transmission delay can occur. And these losses can reduce entire efficiency of hub network in long distance communication. Therefore, in this paper, we propose RTT and data traffic size based UAV scheduling, which selects time/frequency resource of UAVs by using iterative sorting algorithm. The simulation results verified that the proposed scheme improves data rate and packet delay performance in low complexity.