• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.11
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• pp.1311-1317
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• 2010

In this paper, for a uplink space division multiple access system named cooperative spatial multiplexing(CSM), radio resource management(RRM) algorithms are proposed based on sharing uplink channel information among a serving base station(BS) and interfering BSs in a uplink coordinated wireless communication system. A constrained maximum transmit power algorithm is proposed for mobile station(MS) to limit uplink inter-cell interference(ICI). And joint scheduling algorithm among coordinated BSs is proposed to enhance uplink capacity through ICI mitigation by using channel information from interfering BSs. It is shown that the proposed RRM algorithm provides a considerable uplink capacity enhancement by effective ICI mitigation only with moderate complexity.

• Journal of information and communication convergence engineering
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• v.10 no.2
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• pp.117-122
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• 2012

We propose a hybrid multiple access (HMA) for uplink orthogonal frequency division multiple access (OFDMA) systems, which combines two resource sharing schemes: a scheduling-based resource allocation (SBRA) scheme and a contentionbased resource allocation (CBRA) scheme. The SBRA scheme is appropriate for non-real time high data rate traffic, and, CBRA is appropriate for near-real time low/medium data rate traffic. Thus, the proposed HMA scheme supports various types of traffic. As a CBRA scheme, our proposed random frequency hopping (RFH)-OFDMA scheme was presented. Simulation results show that the proposed HMA yields the best performance among various resource allocation schemes for uplink OFDMA systems.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.449-458
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• 2010

In this paper, we present a distributed resource allocation algorithm for multi-cell uplink systems that increases the weighted sum of the average data rates over the entire network under the average transmit power constraint of each mobile station. For the distributed operation, we arrange each base station (BS) to allocate the resource such that its own utility gets maximized in a noncooperative way. We define the utility such that it incorporates both the weighted sum of the average rates in each cell and the induced interference to other cells, which helps to instigate implicit cooperation among the cells. Since the data rates of different cells are coupled through inter-cell interferences, the resource allocation taken by each BS evolves over iterations. We establish that the resource allocation converges to a unique fixed point under reasonable assumptions. We demonstrate through computer simulations that the proposed algorithm can improve the weighted sum of the average rates substantially without requiring any coordination among the base stations.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.57-66
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• 2010

In this paper, we propose the reliability constrained resource allocation scheduling algorithm in cellular network for uplink transmission, where uplink transmission is supported via packet switching schemes without the dedicated uplink circuit links. We evaluate the performance of the proposed algorithm, and compared with the conventional works to identify the pros and cons. The proposed uplink scheduling algorithm is to satisfy the constraints requirements of the MTC services which is considered as the core technology for future mobile wireless networks. It is different to conventional works which target to maximize the link capacity. The proposed algorithm provides reliable uplink transmission independent to the location and the quality of the wireless link of the mobile terminal. Based on the performance evaluation results, we conclude that the proposed method provides enhanced reliability performance than conventional works.

• ETRI Journal
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• v.29 no.1
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• pp.120-123
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• 2007

In this letter, we address the problem of resource allocation with efficiency and quality of service (QoS) support in uplink for a wireless CDMA network supporting real-time (RT) and non-realtime (NRT) communication services. For RT and NRT users, there are different QoS requirements. We introduce and describe a new scheme, namely, traffic aided uplink opportunistic scheduling (TAUOS). While guaranteeing the different QoS requirements, TAUOS exploits the channel condition to improve system throughput. In TAUOS, the cross-layer information, file size information, is used to improve fairness for NRT users. Extensive simulation results show that our scheme can achieve high system throughput in uplink wireless CDMA systems, while guaranteeing QoS requirements.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.1996-2013
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• 2015

This paper considers a scenario that more D2D users exist in the cell, they compete for cellular resources to increase their own data rates, which may cause transmission interference to cellular users (CU) and the unfairness of resource allocation. We design a resource allocation scheme for selfish D2D users assisted by cooperative relay technique which is used to further enhance the users' transmission rates, meanwhile guarantee the QoS requirement of the CUs. Two transmission modes are considered for D2D users: direct transmission mode and cooperative relay transmission mode, both of which reuses the cellular uplink frequency resources. To ensure the fairness of resource distribution, Nash bargaining theory is used to determine the transmission mode and solve the bandwidth allocation problem for D2D users choosing cooperative relay transmission mode, and coalition formation game theory is used to solve the uplink frequency sharing problem between D2D users and CUs through a new defined "Selfish order". Through theoretical analysis, we obtain the closed Nash bargaining solution under CUs' rate constraints, and prove the stability of the formatted coalition. Simulation results show that the proposed resource allocation approach achieves better performance on resource allocation fairness, with only little sacrifice on the system sum rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• ETRI Journal
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• v.34 no.5
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• pp.759-762
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• 2012

Carrier aggregation is an essential feature in the Long Term Evolution-Advanced (LTE-A) system, which allows the scalable expansion of the effective bandwidth to be delivered to user equipment (UE) through the concurrent use of radio resources across multiple component carriers (CCs). This system's optimal radio-resource use has received much attention under simultaneous access (SA) scenarios for multiple CCs (m-CCs). This letter establishes how many CCs a UE should simultaneously connect to maintain maximum uplink capacity. Under the m-CC LTE-A system, the spectral efficiency of the m-CC SA scheme ($m{\geq}2$) is compared with that of CC selection (CCS). Numerical results reveal that the 2-CC SA scheme outperforms CCS and performs almost equally to the m-CC SA scheme ($m{\geq}3$).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.319-333
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• 2022

In order to enhance system energy efficiency, bidirectional link resource allocation strategy in GFDM-based multiuser SWIPT systems is proposed. In the downlink channel, each SWIPT user applies power splitting (PS) receiver structure in information decoding (ID) and non-linear energy harvesting (EH). In the uplink channel, information transmission power is originated from the harvested energy. An optimization problem is constructed to maximize weighted sum ID achievable rates in the downlink and uplink channels via bidirectional link power allocation as well as subcarriers and subsymbols scheduling. To solve this non-convex optimization problem, Lagrange duality method, sub-gradient-based method and greedy algorithm are adopted respectively. Simulation results show that the proposed strategy is superior to the fixed subcarrier scheme regardless of the weighting coefficients. It is superior to the heuristic algorithm in larger weighting coefficients scenario.