Using Reinforcement Learning for Call Admission Control in Cellular Environments featuring Self-Similar Traffic

Lilith, Nimrod; Doğançay, Kutluyıl

doi:10.1109/tencon.2005.300835

Cited by 8 publications

(4 citation statements)

References 14 publications

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“…No exact fractal phenomenon exists in the real world. Most of the fractal phenomena observed in the real world only have the statistical fractal characteristic [6][7]. Statistical fractal random processes present the spectral density power-law behavior and the slowly decaying variance characteristic in the frequency and time domains, respectively.…”

Section: Fractal Evaluation Of the Measured Wireless Cellular Covmentioning

confidence: 99%

“…Moreover, the traffic load of cellular networks has been demonstrated to manifest the self-similar characteristic which also conduces to the heavy-tailed distribution of traffic load [7]. Essentially, several effects such as the wireless signal attenuation, the network traffic and the interference caused by adjacent BSs may affect the shape of wireless cellular coverage boundary.…”

Section: Introductionmentioning

confidence: 99%

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Wireless fractal cellular networks

Qiu

Chen

et al. 2016

IEEE Wireless Commun.

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With the seamless coverage of wireless cellular networks in modern society, it is interesting to consider the shape of wireless cellular coverage. Is the shape a regular hexagon, an irregular polygon, or another complex geometrical shape? Based on fractal theory, the statistical characteristic of the wireless cellular coverage boundary is determined by the measured wireless cellular data collected from Shanghai, China. The measured results indicate that the wireless cellular coverage boundary presents an extremely irregular geometrical shape, which is also called a statistical fractal shape. Moreover, the statistical fractal characteristics of the wireless cellular coverage boundary have been validated by values of the Hurst parameter estimated in angular scales. The statistical fractal characteristics of the wireless cellular coverage boundary can be used to evaluate and design the handoff scheme of mobile user terminals in wireless cellular networks.Accepted by IEEE Wireless Communications.

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Section: Fractal Evaluation Of the Measured Wireless Cellular Covmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wireless fractal cellular networks

Qiu

Chen

et al. 2016

IEEE Wireless Commun.

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“…The elements of the transition matrix 𝐓 are the probabilities of the transitions between note that traffic statistics are necessary to develop the MDP framework but are not required by the RL approachsee for example (Lilith & Dogancay, 2005), whose RLbased admission control succeeded in controlling traffic characterized by a self-similar distribution.…”

Section: Transition Matrixmentioning

confidence: 99%

A lexicographic approach to constrained MDP admission control

Panfili

Pietrabissa

Oddi

et al. 2015

International Journal of Control

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This paper proposes a reinforcement learning-based lexicographic approach to the call admission control problem in communication networks. The admission control problem is modeled as a multi-constrained Markov decision process. To overcome the problems of the standard approaches to the solution of constrained Markov decision processes, based on the linear programming formulation or on a Lagrangian approach, a multi-constraint lexicographic approach is defined, and an on-line implementation based on reinforcement learning techniques is proposed. Simulations validate the proposed approach.

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“…Voice handoff traffic was simulated according to an exponential distribution with a mean call duration 1/μ of a further 1 minute in the new cell. The shape value α for the holding time of data traffic in the case of a handoff was set to 1.4 and the β value was set according to (10) to give a mean of approximately 1 minute.…”

Section: Simulated Systemmentioning

confidence: 99%

Reinforcement Learning-Based Dynamic Guard Channel Scheme with Maximum Packing for Cellular Telecommunications Systems

Lilith

Doğançay

2007

2007 International Conference on Wireless Communications, Networking and Mobile Computing

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This paper presents a distributed reinforcement learning solution to the problem of call admission control for cellular telecommunication networks in the presence of both voice traffic and self-similar data traffic, and user mobility. The developed call admission control architecture is designed to make use of only localised information, and therefore is suitable for implementation in a distributed manner. By way of computer simulations, the call admission control is shown to further improve the revenue raising capability and handoff blocking probability of the optimal maximum packing channel allocation scheme.

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Using Reinforcement Learning for Call Admission Control in Cellular Environments featuring Self-Similar Traffic

Cited by 8 publications

References 14 publications

Wireless fractal cellular networks

Wireless fractal cellular networks

A lexicographic approach to constrained MDP admission control

Reinforcement Learning-Based Dynamic Guard Channel Scheme with Maximum Packing for Cellular Telecommunications Systems

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