• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.559-573
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• 2016

In this paper, we investigate the problem of achieving proportional fairness in hierarchical wireless sensor networks. Combining clustering formulation and scheduling, we maximize total bandwidth utility for proportional fairness while controlling the power consumption to a minimum value. This problem is decomposed into two sub-problems and solved in two stages, which are Clustering Formulation Stage and Scheduling Stage, respectively. The above algorithm, called CSPF_PC, runs in a network formulation sequence. In the Clustering Formulation Stage, we let the sensor nodes join to the cluster head nodes by adjusting transmit power in a greedy strategy; in the Scheduling Stage, the proportional fairness is achieved by scheduling the time-slot resource. Simulation results verify the superior performance of our algorithm over the compared algorithms on fairness index.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1291-1297
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• 2004

In this paper, the new scheduling algorithm that supports the maximization of system throughput and the proportional fairness among non-real time traffic users is proposed in OFDMA wireless mobile communication systems. The concept of the proposed algorithm is based on the proportional fairness algorithm, which is deployed in 3GPP2, and sorting method. The proportional fairness algorithm is adapted to allocate the number of subcarrier per user. A sorting method is contributed to the maximization of system throughput in the practical allocation of subcarrier per user. Simulation results show that new algorithm had better performance than the max rate rule in case of fairness, higher throughput than the scheduling algorithm without sorting method. Even though the system throughput of the proposed algorithm is almost same with the iteration scheme using subcarrier swapping method between users, the computational time of the former is reduced up to 3 times than the latter.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.4
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• pp.291-303
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• 2009

Round robin based proportional share scheduling(RRPS) defines weight which determines share for each task and allocates CPU resource to each task in proportional to its respective weight. RRPS uses fairness as the measure of performance and aims at high fairness of scheduling. However, researches for scheduling fairness problem due to synchronization among tasks have been rarely investigated. In this paper, we discuss that scheduling delay due to synchronization may result high unfairness in RRPS. We explain such a situation as weight inversion. We then propose weight inheritance protocol(WIP), a synchronization mechanism, that prevents weight inversion. We also show that WIP can reduce unfairness using fairness analysis and simulation.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.346-357
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• 2010

Opportunistic scheduling provides the capability of resource management in wireless networks by taking advantage of multiuser diversity and by allowing delay variation in delivering data packets. It generally aims to maximize system throughput or guarantee fairness and quality of service (QoS) requirements. In this paper, we develop an extended proportional fair (PF) scheduling policy that can statistically guarantee three kinds of QoS. The scheduling policy is derived by solving the optimization problems in an ideal system according to QoS constraints. We prove that the practical version of the scheduling policy is optimal in opportunistic scheduling systems. As each scheduling policy has some parameters, we also consider practical parameter adaptation algorithms that require low implementation complexity and show their convergences mathematically. Through simulations, we confirm that our proposed schedulers show good fairness performance in addition to guaranteeing each user's QoS requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5328-5346
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• 2016

An optimal power control algorithm based on convex optimization is proposed for base stations in long term evolution networks. An objective function was formulated to maximize the proportional fairness of the networks. The optimal value of the objective function was obtained using convex optimization and distributed methods based on the path loss model between the base station and users. Field tests on live networks were conducted to evaluate the performance of the proposed algorithm. The experimental results verified that, in a multi-cell multi-user scenario, the proposed algorithm increases system throughputs, proportional fairness, and energy efficiency by 9, 1.31 and 20.2 %, respectively, compared to the conventional fixed power allocation method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.6B
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• pp.586-592
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• 2002

In this paper, new channel scheduling algorithms which reduce transmission delay caused by wireless network are proposed in AMC/TDM wireless data communication. The concept of the Proposed algorithms is based on the proportional fairness, M-LWDF, and performance-guaranteeing algorithm proposed by Xin Liu. The proposed algorithm can be applied to QoS guaranteeing services as well as best-effort services. Simulation results show that new algorithm reduced transmission delay upto 11.5% in case of proportional fairness algorithm and also decreased transmission delay unto 9% in case of M-LWBF algorithm.

• Journal of Communications and Networks
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• v.13 no.6
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• pp.633-638
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• 2011

In this paper, we consider resource allocation with proportional fairness in the downlink orthogonal frequency division multiple access relay networks, in which relay nodes operate in decode-and-forward mode. A joint optimization problem is formulated for relay selection, subcarrier assignment and power allocation. Since the formulated primal problem is nondeterministic polynomial time-complete, we make continuous relaxation and solve the dual problem by Lagrangian dual decomposition method. A near-optimal solution is obtained using Karush-Kuhn-Tucker conditions. Simulation results show that the proposed algorithm provides superior system throughput and much better fairness among users comparing with a heuristic algorithm.

• ETRI Journal
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• v.38 no.6
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• pp.1153-1162
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• 2016

This paper addresses the resource allocation (RA) problem in multi-cell cognitive radio networks. Besides the interference power threshold to limit the interference on primary users PUs caused by cognitive users CUs, a proportional fairness constraint is used to guarantee fairness among multiple cognitive cells and the impact of imperfect spectrum sensing is taken into account. Additional constraints in typical real communication scenarios are also considered-such as a transmission power constraint of the cognitive base stations, unique subcarrier allocation to at most one CU, and others. The resulting RA problem belongs to the class of NP-hard problems. A computationally efficient optimal algorithm cannot therefore be found. Consequently, we propose a suboptimal RA algorithm composed of two modules: a subcarrier allocation module implemented by the immune algorithm, and a power control module using an improved sub-gradient method. To further enhance algorithm performance, these two modules are executed successively, and the sequence is repeated twice. We conduct extensive simulation experiments, which demonstrate that our proposed algorithm outperforms existing algorithms.

• ETRI Journal
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• v.30 no.5
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• pp.741-743
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• 2008

In this letter, a heuristic channel allocation and scheduling scheme is proposed. By comparing the size of the alternative-factor assessment, which is obtained by simple calculation, we can easily find the most appropriate channel for each user for overall throughput enhancement. Numerical results show that the downlink throughput of the proposed scheme is higher than that of proportional fairness and is almost the same as that of the maximum C/I scheme, while user fairness remains better than that of the maximum C/I scheme.