Loss formulas and their application to optimization for cellular networks

Harine, G.; Marie, Raymond; Puigjaner, Ramon; Trivedi, Kishor S.

doi:10.1109/25.933303

Cited by 108 publications

(84 citation statements)

References 4 publications

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“…The objective is to minimize the blocking probability of new calls subject to the constraint that the dropping probability of handoff calls is less than 0.01. The optimal number of guard channels for guard channel policy is obtained by algorithm given in [4] and the optimal parameters of limited fractional guard channel policy is obtained by algorithm given in [3]. By inspecting table 1, it is evident that the performance of dynamic guard channel policy is close to the performance of guard channel policy.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…The value of p h specifies by the quality of service of the network. In order to find the optimal value of T * , in [3] a binary search and in [4] a linear search algorithms are given. These algorithms assumes that the all parameters of input traffic are known in advance.…”

Section: Fig 1 Markov Chain Model Of Cellmentioning

confidence: 99%

“…It has been shown that there is an optimal threshold T * in which B n is minimized subject to the hard constraint on B h [3]. Algorithms for finding the optimal number of guard channels are given in [3,4]. These algorithms assume that the input traffic is a stationary process with known parameters.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Learning automata based dynamic guard channel algorithms

Beigy

Meybodi

2011

Computers & Electrical Engineering

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Abstract. Dropping probability of handoff calls and blocking probability of new calls are two important QoS measures for cellular networks. Call admission policies, such as fractional guard channel and uniform fractional guard channel policies are used to maintain the pre-specified level of QoS. Since the parameters of network traffics are unknown and time varying, the optimal number of guard channels is not known and varies with time. In this paper, we introduce a new dynamic guard channel policy, which adapts the number of guard channels in a cell based on the current estimate of dropping probability of handoff calls. The proposed algorithm minimizes blocking probability of new calls subject to the constraint on the dropping probability of handoff calls. In the proposed policy, a learning automaton is used to find the optimal number of guard channels. The proposed algorithm doesn't need any a priori information about input traffic. The simulation results show that performance of this algorithm is close to the performance of guard channel policy for which we need to know all traffic parameters in advance. Two advantages of the proposed policy are that it is fully autonomous and adaptive. The first advantage implies that, the proposed policy does not require any exchange of information between the neighboring cells and hence the network overheads due to the information exchange will be zero. The second one implies that, the proposed policy does not need any priori information about input traffic and the traffic may vary.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Fig 1 Markov Chain Model Of Cellmentioning

confidence: 99%

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Learning automata based dynamic guard channel algorithms

Beigy

Meybodi

2011

Computers & Electrical Engineering

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“…These schemes accept handover calls as long as the cell has idle channels. When the number of calls is compared with the given threshold, this scheme is called call bounding (Ramjee et al, 1997); (Hong & Rappaport, 1986); (Oh & Tcha, 1992); (Haring et al, 2001); (Beigy & Meybodi, 2005). When the current number of new calls is compared with the given threshold, the scheme is called new call bounding scheme (Fang & Zhang, 2002).…”

Section: Reservation Based Schemesmentioning

confidence: 99%

Call Admission Control in Cellular Networks

Sneps-Sneppe¹,

Iversen²

2012

Mobile Networks

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“…This priority is usually implemented through allocation of more resources to calls with higher level of QoS [1]. Several call admission control policies have been proposed to reduce the dropping of voice calls in wireless networks [2,3,4,5,6].…”

Section: Introductionmentioning

confidence: 99%

A general call admission policy for next generation wireless networks

Beigy

Meybodi

2005

Computer Communications

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In this paper, we consider the call admission problem in ne}.."t generation wireless networks, which must handles multi-media traffics. We first introduce a multi-threshold guard channel policy. The limiting behavior of this policy. is analyzed under the stationary traffic. Then we give an algorithm, which finds the optimal number of guard channels, which minimi?:esthe blocking probability calls with lowest level of QoS subject to the hard constraint on the blocking probabilities of other calls.

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Loss formulas and their application to optimization for cellular networks

Cited by 108 publications

References 4 publications

Learning automata based dynamic guard channel algorithms

Learning automata based dynamic guard channel algorithms

Call Admission Control in Cellular Networks

A general call admission policy for next generation wireless networks

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