• Journal of Communications and Networks
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• v.4 no.2
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• pp.136-147
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• 2002

In this paper, the maximal capacity of the data network link has attempted to be exploited by using the dynamic allocation strategy. We propose a new methodology based on the economic models for competing traffic classes (classes of sessions) in packet networks. As the demand for network services accelerates, users' satisfaction to the service level might decrease due to the congestion at the network nodes. To prevent this, efficient allocation of a networks resources, such as available bandwidth and switch capacity, is needed. By using the so-called user profile as well as the utility (e.g., data rate) functions, it is possible to allocate data rates and other utilities using the arbitrary number of QoS classes, say $0.01,...,$10.

• ETRI Journal
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• v.36 no.6
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• pp.953-959
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• 2014

This paper studies the uplink resource allocation for multiple radio access (MRA) in reconfigurable radio systems, where multiple-input and multiple-output (MIMO) multicarrier-code division multiple access (MC-CDMA) and MIMO orthogonal frequency-division multiple access (OFDMA) networks coexist. By assuming multi-radio user equipment with network-guided operation, the optimal resource allocation for MRA is analyzed as a cross-layer optimization framework with and without fairness consideration to maximize the uplink sum-rate capacity. Numerical results reveal that parallel MRA, which uses MC-CDMA and OFDMA networks concurrently, outperforms the performance of each MC-CDMA and OFDMA network by exploiting the multiuser selection diversity.

• ETRI Journal
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• v.40 no.6
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• pp.714-725
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• 2018

Destination-assisted jamming (DAJ) is usually used to protect confidential information against untrusted relays and eavesdroppers in wireless networks. In this paper, a DAJ-based untrusted relay network with multiple antennas installed is presented. To increase the secrecy, a joint optimization of beamforming and power allocation at the source and destination is studied. A matched-filter precoder is introduced to maximize the cooperative jamming signal by directing cooperative jamming signals toward untrusted relays. Then, based on generalized singular-value decomposition (GSVD), a novel transmitted precoder for confidential signals is devised to align the signal into the subspace corresponding to the confidential transmission channel. To decouple the precoder design and optimal power allocation, an iterative algorithm is proposed to jointly optimize the above parameters. Numerical results validate the effectiveness of the proposed scheme. Compared with other schemes, the proposed scheme shows significant improvement in terms of security performance.

• ETRI Journal
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• v.40 no.6
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• pp.726-735
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• 2018

Femtocells are good examples of the ultimate networking technology, offering enhanced indoor coverage and higher data rate. However, the dense deployment of femto base stations (FBSs) and the exploitation of subcarrier reuse between macrocell base stations and FBSs result in significant co-tier and cross-tier interference, thus degrading system performance. Therefore, appropriate resource allocations are required to mitigate the interference. This paper proposes a discrete bacterial foraging optimization (DBFO) algorithm to find the optimal resource allocation in two-tier networks. The simulation results showed that DBFO outperforms the random-resource allocation and discrete particle swarm optimization (DPSO) considering the small number of steps taken by particles and bacteria.

• ETRI Journal
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• v.42 no.6
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• pp.846-858
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• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.239-248
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• 2007

In the highly competitive construction industry, a slight inaccuracy of estimation can easily cause the loss of a project. Erroneous experience-based cost estimates or allocations of on-site supervisory manpower often offset the profit gained from the project and may jeopardize the management processes. To counter these types of problems, we develop a model using mathematical analysis and case-based reasoning to automate the allocation of on-site supervisory manpower and estimate construction site costs. The method is founded upon laborious data collection processes and analysis by matching statistical assumptions, and is applicable to construction projects. In the modeling the costs and allocation of on-site supervisory manpower are quantified for both owners and contractors before initiating or bidding on the projects. The findings confirm that the degree of variation of the model predictions has an accuracy rate at 88.47%. Single-site construction projects can be accurately predicted and the assignment of supervisory manpower feasibly automated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.202-215
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• 2023

This paper proposes a non-orthogonal multiple access (NOMA) based low-complexity relaying approach for multiuser cellular two-way relay channels (CTWRCs). In the proposed scheme, the relay detects the signal using successive interference cancellation (SIC) and re-generates the transmit signal with zero-forcing (ZF) transmit precoding. The achievable data rates of the NOMA-based multiuser two-way relaying (TWR) approach is analyzed. We further study the power allocation among different data streams to maximize the weighted sum-rate (WSR). We re-form the resultant non-convex problem into a standard monotonic program. Then, we design a polyblock outer approximation algorithm to sovle the WSR problem.The proposed optimal power allocation algorithm converges fast and it is shown that the NOMA-TWR-OPA scheme outperforms a NOMA benchmark scheme and conventional TWR schemes.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.9
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• pp.9-16
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• 2007

In the multiuser OFDM systems, an efficient resource allocation is necessary in order to provide the service to more users. This paper proposes u improved subcarrier allocation algorithm, satisfying each user's QoS under the limited resources, to maximize total transmission data rate and spectral efficiency. The proposed algorithm is divided into two steps. In the first step, users who are eligible for services are determined by using BER, user's minimum data rate requirement, and channel information. In the second step, first, subcarriers are allocated to users on the basis of channel state. And then, reallocation is fulfilled so that the total transmission data rate is maximized and the least reduction in the overall throughput is caused.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.430-435
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• 2022

In this paper, we consider the non-orthogonal multiple access (NOMA) technique in the heterogeneous network (HetNET) consisting of a single macro base station (BS) and multiple small BSs, where the perfect successive interference cancellation is assumed for the NOMA signals. In this paper, we propose a deep learning-based user association and power allocation scheme to maximize the data rate in the NOMA-based HetNET. In particular, the proposed scheme includes the deep neural network (DNN)-based user association process for load balancing and the DNN-based power allocation process for data-rate maximization. Through the simulation assuming path loss and Rayleigh fading channels between BSs and users, the performance of the proposed scheme is evaluated, and it is compared with the conventional maximum signal-to-interference-plus-noise ratio (Max-SINR) scheme. Through the performance comparison, we show that the proposed scheme provides better sum rate performance than the conventional Max-SINR scheme.

• Journal of the Korea Society for Simulation
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• v.33 no.1
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• pp.27-34
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• 2024

This study aims to propose an optimal asset allocation that minimizes the risk of insufficient realized replacement rates compared to the OECD average replacement rate. To do this, we set the shortfall risk of replacement rates and calculates an asset allocation plan to minimize this risk based on the period of enrollment, the income level and additional contribution. We consider stocks and deposits as investment assets, using Monte Carlo simulation with a GBM model to generate return distributions for stocks. Our result show that, for individuals with a enrollment period of less than 30 years, participants should invest a minimum of 70-80% of their funds in risky assets to minimize the shortfall risk. However, the proportion of funds that need to be invested in risky assets declines significantly when participants contribute an additional premiums. This effect is particularly pronounced among low-income individuals. Therefore, to achieve OECD average replacement rates, the government needs to incentivize participants to invest more in risky assets, while also providing policies to encourage additional contributions, especially for the low-income population.