• Journal of Industrial Convergence
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• v.1 no.2
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• pp.69-79
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• 2003

In order to solve scheduling, many techniques including optimization and heuristics methods have been proposed. However, these conventional approaches are usually inadequate to obtain a satisfactory solution because of a NP-Complete which requires extensive computation effort. The aim of this paper is to develop an expert system for job shop scheduling using an AI technique. Through this system, the user can choose one of several performances. If one performance is chosen, then the system solves a scheduling in order to satisfy that performance. Then, this system decides urgent job. This system can utilize production resources efficiently and minimize work-in-process inventories and tardy jobs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.6
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• pp.1101-1112
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• 2011

The Multiuser Eigenmode Transmission (MET) has generated significant interests in literature due to its optimal performance in linear precoding systems. The MET can simultaneously transmit several spatial multiplexing eigenmodes to multiple users which significantly enhance the system performance. The maximum number of users that can be served simultaneously is limited due to the constraints on the number antennas, and thus an appropriate user selection is critical to the MET system. Various algorithms have been developed in previous works such as the enumerative search algorithm. However, the high complexities of these algorithms impede their applications in practice. In this paper, motivated by the necessity of an efficient and effective user selection algorithm, a low complexity recursive user selection algorithm is proposed for the MET system. In addition, the fairness of the MET system is improved by using the combination of the proposed user selection algorithm and the adaptive Proportional Fair Scheduling (PFS) algorithm. Extensive simulations are implemented to verify the efficiency and effectiveness of the proposed algorithm.

• Journal of Multimedia Information System
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• v.2 no.1
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• pp.143-152
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• 2015

Multimedia services in the cloud have become a popular trend in the big data environment. However, how to efficiently schedule a large number of multimedia services in the cloud is still an open and challengeable problem. Current cloud-based scheduling algorithms exist the following problems: 1) the content of the multimedia is ignored, and 2) the cloud platform is a known parameter, which makes current solutions are difficult to utilize practically. To resolve the above issues completely, in this work, we propose a novel distributed multimedia scheduling to satisfy the objectives: 1) Develop a general cloud-based multimedia scheduling model which is able to apply to different multimedia applications and service platforms; 2) Design a distributed scheduling algorithm in which each user makes a decision based on its local information without knowing the others' information; 3) The computational complexity of the proposed scheduling algorithm is low and it is asymptotically optimal in any case. Numerous simulations have demonstrated that the proposed scheduling can work well in all the cloud service environments.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.201-204
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• 2006

In this paper, we propose efficient scheduling strategy for Multi-user MIMO systems that find advantageous trade off solution between multiuser diversity and spatial diversity, spatial multiplexing technique. Specifically, we suggest P-SFS(Pseudo-SNR Fair scheduling) algorithm that consider throughput and fairness problem. also we propose channel aware Antenna deployment that decide how to use assigned multiple antennas by the information of each user's channel condition.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.6
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• pp.3-9
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• 2015

We investigate rate scheduling and power allocation problem for a delay constrained CDMA systems. Specifically, we determine an energy efficient scheduling policy, while each user maintains the short term (n time slots) average throughput. We consider a multirate CDMA system where multirate is achieved by multiple codes. Each code can be interpreted as a virtual user. The aim is to schedule the virtual users into each time slot, such that the sum of transmit energy in n time slots is minimized. We then show that the total energy minimization problem can be solved by a shortest path algorithm. We compare the performance of the optimum scheduling with that of TDMA-type scheduling.

• 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.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.651-657
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• 1998

In this study, an intelligent scheduling with hybrid architecture, which integrates expert system and neural network, is proposed. Neural network is trained with the data acquired from simulation model of FMC to obtain the knowledge about the relationship between the state of the FMC and its best dispatching rule. Expert system controls the scheduling of FMC by integrating the output of neural network, the states of FMS, and user input. By applying the hybrid system to a scheduling problem, the human knowledge on scheduling and the generation of non-logical knowledge by machine teaming, can be processed in one scheduler. The computer simulation shows that comparing with MST(Minimum Slack Time), there is a little increment in tardness, 5% growth in flow time. And at breakdown, tardness is not increased by expert system comparing with EDD(Earliest Due Date).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.6
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• pp.1848-1868
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• 2014

Multiple-in multiple-out (MIMO) in long-term evolution (LTE) is an essential factor in achieving high speed data rates and spectral efficiency. The unexpected growth in data rate demand has pushed researchers to extend the benefits of multi-user MIMO. The multi-user MIMO system can take full advantage of channel conditions by employing efficient adjustment techniques for scheduling, and by assigning different modulation and coding rates. However, one of the critical issues affecting this feature is the appropriate estimation of channel quality indicator (CQI) to manage the allocated resources to users. Therefore, an accurate CQI estimation scheme is required for the multi-user MIMO transmission to obtain significant improvements on spectral efficiency. This paper presents overviews of multi-user MIMO in LTE/LTE-advanced systems. The link adaptation, scheduling process, and different factors that affect the reliability of CQI measurements are discussed. State-of-the-art schemes for the post-processing CQI estimation, and the comparisons of various CQI estimation schemes to support multi-user MIMO are also addressed.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.63-68
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• 2015

We consider a cell edge environment. In cell edge, a user interfered by signal which is generated by a base stations not including the user. In cell edge environment, that is, there are inter cell interference (ICI) as well as multi user interference (MUI). Coordinated multi-point transmission (CoMP) is a technique which mitigates ICI between base stations. In CoMP, therefore, base stations can coordinate with each other by sharing user state information (CSI) in order to mitigate ICI. To improve sum rate performance in CoMP, each base station should generate optimal user group and transmit data to users selected in the optimal user group. In this paper, we propose a user selection algorithm in CoMP. The proposed method use signal to interference plus noise ratio (SINR) as criterion of selecting users. Because base station can't measure accurate SINR of users, in this paper, we estimate SINR equation considering ICI as well as MUI. Also, we propose a user selection algorithm based on the estimated SINR. Through MATAL simulation, we verify that the proposed method improves the system sum rate by an average of 1.5 ~ 3 bps/Hz compared to the conventional method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.2
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• pp.9-16
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• 2012

In this paper, the beamforming and user scheduling scheme for device-to-device (D2D) underlaying celullar networks with partial channel state information is investigated. In the proposed scheme, cellular users whose channels are nearly orthogonal to the channel between base station and D2D receiver are selected for unitary beamforming so as to minimize the interference to the D2D receiver. The interference caused by underlaying D2D communication can be minimized by reducing the D2D transmitter's transmission power. To enhance the cellular users' throughput further, we also investigate codebook generation method in which each code vector belongs to multiple unitary code matrices. From simulation results, we show that the proposed beamforming and user scheduling scheme mitigates D2D interference to the cellular networks and the codebook generation method improves cellular users' throughput.