• ETRI Journal
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• v.44 no.6
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• pp.955-965
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• 2022

A low Earth orbit (LEO) satellite constellation could be used to provide network coverage for the entire globe. This study considers multi-beam frequency reuse in LEO satellite systems. In such a system, the channel is time-varying due to the fast movement of the satellite. This study proposes an efficient power and bandwidth allocation method that employs two linear machine learning algorithms and take channel conditions and traffic demand (TD) as input. With the aid of a simple linear system, the proposed scheme allows for the optimum allocation of resources under dynamic channel and TD conditions. Additionally, efficient projection schemes are added to the proposed method so that the provided capacity is best approximated to TD when TD exceeds the maximum allowable system capacity. The simulation results show that the proposed method outperforms existing methods.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.240-242
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• 2004

A channel allocation algorithm of multi-user OFDM(orthogonal frequency division multiplexing) system is presented. The proposed algorithm is to reduce the complexity of the system, using the GNN(gradual neural network) with gradual expansion scheme and the algorithm attempts to allocate channel with good channel gain to each user. The method has lower computational complexity and less iteration than other algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.10
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• pp.2395-2410
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• 2013

Many telecommunication operators around the world have multiple networks. The networks run by each operator are always of different generations, such as 2G and 3G or even 4G systems. Each system has unique characters and specified requirements for optimal operation. It brings about resource allocation problem among these networks for the operator, because the budget of each operator is limited. However, the evaluation of resource allocation among various networks under each operator is missing for long, not to mention resource allocation optimization. The operators are dying for an algorithm to end their blind resource allocation, and the Resource Allocation Optimization Algorithm for Multi-network Operator (RAOAMO) proposed in this paper is what the operators want. RAOAMO evaluates and optimizes resource allocation in the view of overall cost for each operator. It outputs a resource distribution target and corresponding optimization suggestion. Evaluation results show that RAOAMO helps operator save overall cost in various cases.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.2
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• pp.288-307
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• 2013

This paper formulates resource allocation for decode-and-forward (DF) relay assisted multi-cell orthogonal frequency division multiple (OFDM) networks as an optimization problem taking into account of inter-cell interference and users fairness. To maximize the transmit rate of system we propose a joint interference coordination, subcarrier and power allocation algorithm. To reduce the complexity, this semi-distributed algorithm divides the primal optimization into three sub-optimization problems, which transforms the mixed binary nonlinear programming problem (BNLP) into standard convex optimization problems. The first layer optimization problem is used to get the optimal subcarrier distribution index. The second is to solve the problem that how to allocate power optimally in a certain subcarrier distribution order. Based on the concept of equivalent channel gain (ECG) we transform the max-min function into standard closed expression. Subsequently, with the aid of dual decomposition, water-filling theorem and iterative power allocation algorithm the optimal solution of the original problem can be got with acceptable complexity. The third sub-problem considers dynamic co-channel interference caused by adjacent cells and redistributes resources to achieve the goal of maximizing system throughput. Finally, simulation results are provided to corroborate the proposed algorithm.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.26-35
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• 2009

In this paper, we investigate how to do resource allocation to guarantee a minimum user data rate at low signaling overhead in multi-cell orthogonal frequency division multiple access (OFDMA) wireless systems. We devise dynamic resource allocation (DRA) algorithms that can minimize the QoS violation ratio (i.e., the ratio of the number of users who fail to get the requested data rate to the total number of users in the overall network). We assume an OFDMA system that allows dynamic control of frequency reuse factor (FRF) of each sub-carrier. The proposed DRA algorithms determine the FRFs of the sub-carriers and allocate them to the users adaptively based on inter-cell interference and load distribution. In order to reduce the signaling overhead, we adopt a hierarchical resource allocation architecture which divides the resource allocation decision into the inter-cell coordinator (ICC) and the base station (BS) levels. We limit the information available at the ICC only to the load of each cell, that is, the total number of sub-carriers required for supporting the data rate requirement of all the users. We then present the DRA with limited coordination (DRA-LC) algorithm where the ICC performs load-adaptive inter-cell resource allocation with the limited information while the BS performs intra-cell resource allocation with full information about its own cell. For performance comparison, we design a centralized algorithm called DRA with full coordination (DRA-FC). Simulation results reveal that the DRA-LC algorithm can perform close to the DRA-FC algorithm at very low signaling overhead. In addition, it turns out to improve the QoS performance of the cell-boundary users, and achieve a better fairness among neighboring cells under non-uniform load distribution.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.11
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• pp.19-24
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• 2007

This paper presents a performance analysis of dynamic channel allocation (DCA) based on the greedy approach (GA) for orthogonal frequency division multiple access (OFDMA) systems over Rayleigh fading channels. The GA-based DCA achieves its performance improvement using multi-user diversity. We analyze the statistics of the number of allocable users (NAU), which represents the multi-user diversity order at each allocation process. The derived statistics are then used to analyze the performance of GA-based DCA. The analysis results show that the number of subcarriers allocated to each user must be equal to achieve the maximum system performance (i.e., based on outage probability and data throughput).

• 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.

• Journal of Korea Water Resources Association
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• v.42 no.3
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• pp.259-270
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• 2009

The applicability of the developed distributed rainfall runoff model using a multi-directional flow allocation algorithm and a real-time updating algorithm was evaluated. The rainfall runoff processes were simulated for the events of the Andong dam basin and the Namgang dam basin using raingauge network data and weather radar rainfall data, respectively. Model parameters of the basins were estimated using previous storm event then those parameters were applied to a current storm event. The physical propriety of the multi-directional flow allocation algorithm for flow routing was validated by presenting the result of flow grouping for the Andong dam basin. Results demonstrated that the developed model has efficiency of simulation time with maintaining accuracy by applying the multi-directional flow allocation algorithm and it can obtain more accurate results by applying the real-time updating algorithm. In this study, we demonstrated the applicability of a distributed rainfall runoff model for the advanced basin-wide flood management.

• ETRI Journal
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• v.27 no.6
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• pp.768-776
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• 2005

We compare the achievable throughput of time division multiple access (TDMA) multiple-input multiple-output (MIMO) schemes illustrated in the 3rd Generation Partnership Project (3GPP) MIMO technical report, versus the sum-rate capacity of space-time multiple access (STMA). These schemes have been proposed to improve the 3GPP high speed downlink packet access (HSDPA) channel by employing multiple antennas at both the base station and mobile stations. Our comparisons are performed in multi-user environments and are conducted using TDMA such as Qualcomm's High Data Rate and HSDPA, which is a simpler technique than STMA. Furthermore, we present the unified optimal power allocation strategy for HSDPA MIMO schemes by exploiting the similarity of multiple antenna systems and multi-user channel problems.