• 대한의용생체공학회:의공학회지
• /
• 제9권2호
• /
• pp.159-164
• /
• 1988

This thesis investigates the Quantitative aspect of epidemic phenomena utilizing the analytical method of discrete time systeMs based on the theory of Markov processes. In particular, the pattern on the epidemic character of turberculosis controlled by prophylaxis and BCG vaccinatioll was analyzed by the markovian model of tuberculosis system which is derived according to the ecologic relationship between nine epidemiologic states of individuals. The quantitative aspects of the model were characterized by digital computer simulations.

• 산업경영시스템학회지
• /
• 제26권2호
• /
• pp.62-67
• /
• 2003

This paper deals with a First-Come, First-Served queueing model to analyze the behavior of heterogeneous finite source system with a single server Each sources and the processor are assumed to operate in independently Markovian environments, respectively. Each request is characterized by its own exponentially distributed source and service time with parameter depending on the state of the corresponding environment, that is, the arrival and service rates are subject to random fluctuations. Our aim is to get the usual stationary performance measures of the system, such as, utilizations, mean number of requests staying at the server, mean queue lengths, average waiting and sojourn times. In the case of fast arrivals or fast service asymptotic methods can be applied. In the intermediate situations stochastic simulation Is used. As applications of this model some problems in the field of telecommunications are treated.

• 품질경영학회지
• /
• 제24권3호
• /
• pp.31-36
• /
• 1996

A Markovian stochastic model for a system subject to random shocks is considered. Each shock arriving according to a Poisson process decreases the state of the system by a random amount. A repairman arrives at the system periodically for inspection and repairs the system only if the state is below a threshold. Costs are assigned to each inspection of the repairman, to each repair, and to the system being in bad states below the threshold. The expected long run average cost is obtained and compared with that of the random inspection introduced by Lee and Lee(1994).

• Journal of Communications and Networks
• /
• 제15권2호
• /
• pp.222-227
• /
• 2013

This paper presents an analytical framework for dynamic spectrum allocation in cognitive radio networks. We propose a distributed queuing based Markovian model each for single channel and multiple channels access for a contending user. Knowledge about spectrum mobility is one of the most challenging problems in both these setups. To solve this, we consider probabilistic channel availability in case of licensed channel detection for single channel allocation, while variable data rates are considered using channel aggregation technique in the multiple channel access model. These models are designed for a centralized architecture to enable dynamic spectrum allocation and are compared on the basis of access latency and service duration.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제12권7호
• /
• pp.3095-3111
• /
• 2018

Spectrum sensing (SS) is one of the fundamental tasks for cognitive radio. In SS, decisions can be made via comparing the test statistics with a threshold. Conventional adaptive algorithms for SS usually adjust their thresholds according to the radio environment. This paper concentrates on the issue of adaptive SS whose threshold is adjusted based on the Markovian behavior of primary user (PU). Moreover, Bayesian cost is adopted as the performance metric to achieve a trade-off between false alarm and missed detection probabilities. Two novel adaptive algorithms, including Markov Bayesian energy detection (MBED) algorithm and IMBED (improved MBED) algorithm, are proposed. Both algorithms model the behavior of PU as a two-state Markov process, with which their thresholds are adaptively adjusted according to the detection results at previous slots. Compared with the existing Bayesian energy detection (BED) algorithm, MBED algorithm can achieve lower Bayesian cost, especially in high signal-to-noise ratio (SNR) regime. Furthermore, it has the advantage of low computational complexity. IMBED algorithm is proposed to alleviate the side effects of detection errors at previous slots. It can reduce Bayesian cost more significantly and in a wider SNR region. Simulation results are provided to illustrate the effectiveness and efficiencies of both algorithms.

• 한국통신학회논문지
• /
• 제18권12호
• /
• pp.1855-1869
• /
• 1993

기존의 알로하 시스템은 불안정한 시스템으로 알려져있다. 또한 포획현상을 가지는 알로하 시스템도 불안정하다는 것이 증명되었다. 본 논문에서는 신호, 포획현상을 가지는 알로하 시스템에 전송 제어 알고리즘을 적용하고, 새로운 Lyapunov 함수를 도입하여 다차원 바르코프 연쇄 모델의 안정성을 증명하였다. 부가적으로 시스템의 전송효율을 구하고, 또한 시뮬레이션을 통하여 패킷 전송지연을 분석하였다.

• Journal of applied mathematics & informatics
• /
• 제32권1_2호
• /
• pp.129-136
• /
• 2014

One of the fundamental issues in the design of dynamic spectrum access policy is the modeling of the dynamic behavior of channel occupancy by primary users. Under a Markovian modeling of channel occupancy, a periodic sensing and greedy access policy is known as one of the simple and practical dynamic spectrum access policies in cognitive radio networks. In this paper, the primary occupancy of each channel is modeled as a discrete-time alternating renewal process with generally distributed on- and off-periods. A periodic sensing and greedy access policy is constructed based on the general channel occupancy model. Simulation results show that the proposed policy has better throughput than the policies using channel models with exponentially distributed on- or off-periods.

• 한국통계학회:학술대회논문집
• /
• 한국통계학회 2000년도 추계학술발표회 논문집
• /
• pp.105-108
• /
• 2000

We consider a Markovian retrial queue with waiting space in which the service rates and retrial rates depend on the number of customers in the service facility and in the orbit, respectively. Each arriving customer from outside or orbit decide either to enter the facility or to join the orbit in Bernoulli manner whose entering probability depend on the number of customers in the service facility. In this paper, a stochastic order relation between two bivariate processes (C(t), N(t)) representing the number of customers C(t) in the service facility and N(t) one in the orbit is deduced in terms of corresponding parameters by constructing the equivalent processes on a common probability space. Some applications of the results to the stochastic bounds of the multi-server retrial model are presented.

• Journal of applied mathematics & informatics
• /
• 제35권5_6호
• /
• pp.623-649
• /
• 2017

Retrial queues have been widely used to model the many practical situations arising from telephone systems, telecommunication networks and call centers. An approximation method for a simple Markovian retrial queue by reducing the two dimensional problem to one dimensional problem was presented by Fredericks and Reisner in 1979. The method seems to be a promising approach to approximate the retrial queues with complex structure, but the method has not been attracted a lot of attention for about thirty years. In this paper, we exposit the method in detail and show the usefulness of the method by presenting the recent results for approximating the retrial queues with complex structure such as multi-server retrial queues with phase type distribution of retrial time, impatient customers with general persistent function and/or multiclass customers, etc.

• 한국음향학회:학술대회논문집
• /
• 한국음향학회 1998년도 제15회 음성통신 및 신호처리 워크샵(KSCSP 98 15권1호)
• /
• pp.225-230
• /
• 1998

In this paper, a Kalman filter approach for enhancing speech signals degraded by statistically independent additive nonstationary noise is developed. The autoregressive hidden markov model is used for modeling the statistical characteristics of both the clean speech signal and the nonstationary noise process. In this case, the speech enhancement comprises a weighted sum of conditional mean estimators for the composite states of the models for the speech and noise, where the weights equal to the posterior probabilities of the composite states, given the noisy speech. The conditional mean estimators use a smoothing spproach based on two Kalmean filters with Markovian switching coefficients, where one of the filters propagates in the forward-time direction with one frame. The proposed method is tested against the noisy speech signals degraded by Gaussian colored noise or nonstationary noise at various input signal-to-noise ratios. An app개ximate improvement of 4.7-5.2 dB is SNR is achieved at input SNR 10 and 15 dB. Also, in a comparison of conventional and the proposed methods, an improvement of the about 0.3 dB in SNR is obtained with our proposed method.