Channel occupancy time distribution in a cellular radio system

Guérin, Roch

doi:10.1109/t-vt.1987.24106

Cited by 373 publications

(171 citation statements)

References 4 publications

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“…From (7), (8) and the fact that the rvs {S j,k } j=1,...,N,k=1,2 are mutually independent, we readily find…”

Section: Proposition 1 (Lst Of Message Delay) Under the Two-hop Multmentioning

confidence: 99%

“…In the random direction mobility model [1,8] each node is assigned an initial direction θ, speed S ∈ [v min , v max ] and a finite travel time τ. The node then travels in the direction θ for a duration τ and at speed S. When the node travel time has expired a new direction, speed and travel time are chosen at random, independently of all previous directions, speeds and travel times.…”

Section: Random Direction Mobility Modelmentioning

confidence: 99%

“…is a difficult task due to the inherent complexity of mobile ad hoc networks, particularly the random nature of both the movement of the nodes and of the demand (traffic). The performance of mobile ad hoc networks is in general studied via lengthy and complex simulations, for a limited number of mobility models, including the random waypoint mobility model [3] or the random direction mobility model [1,8].…”

Section: Introductionmentioning

confidence: 99%

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The message delay in mobile ad hoc networks

Groenevelt

Nain

Koole

2005

Performance Evaluation

551

554

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A stochastic model is introduced that accurately models the message delay in mobile ad hoc networks where nodes relay messages and the networks are sparsely populated. The model has only two input parameters: the number of nodes and the parameter of an exponential distribution which describes the time until two random mobiles come within communication range of one another. Closed-form expressions are obtained for the Laplace-Stieltjes transform of the message delay, defined as the time needed to transfer a message between a source and a destination. From this we derive both a closed-form expression and an asymptotic approximation (as a function of the number of nodes) of the expected message delay. As an additional result, the probability distribution function is obtained for the number of copies of the message at the time the message is delivered. These calculations are carried out for two protocols: the two-hop multicopy and the unrestricted multicopy protocols. It is shown that despite its simplicity, the model accurately predicts the message delay for both relay strategies for a number of mobility models (the random waypoint, random direction and the random walker mobility models).

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“…From (7), (8) and the fact that the rvs {S j,k } j=1,...,N,k=1,2 are mutually independent, we readily find…”

Section: Proposition 1 (Lst Of Message Delay) Under the Two-hop Multmentioning

confidence: 99%

Section: Random Direction Mobility Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The message delay in mobile ad hoc networks

Groenevelt

Nain

Koole

2005

Performance Evaluation

551

554

View full text Add to dashboard Cite

show abstract

“…Therefore, exponential distribution has been intensively used to model cellular channel occupancy, see [4] as an example. Nevertheless, many research findings concluded poor similarity between exponential distribution and empirical data [6]. One of the main disagreements between exponential distribution and empirical data is the heavy tail behaviour for the empirical channel occupancy which is not properly characterized by exponential distributions.…”

Section: Introductionmentioning

confidence: 99%

Empirical Statistical Model for LTE Downlink Channel Occupancy

Hamid

Björsell

Slimane

2017

Wireless Pers Commun

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This paper develops an empirical statistical channel occupancy model for downlink long-term evolution (LTE) cellular systems. The model is based on statistical distributions mixtures for the holding times of the channels. Moreover, statistical distribution of the time when the channels are free is also considered. The data is obtained through an extensive measurement campaign performed in Stockholm, Sweden. Two types of mixtures are considered, namely, exponential and log-normal distributions to fit the measurement findings. The log-likelihood of both mixtures is used as a quantitative measure of the goodness of fit. Moreover, finding the optimal number of linearly combined distributions using the Akaike information criterion is investigated. The results show that good fitting can be obtained by using either exponential or log-normal distributions mixture. Even though, the fitting is done for a representative case with a tempo-spatial consideration, the model is yet applicable in general for LTE and other cellular systems in a wider sense.

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“…Guerin's mobility model [15] has become the foundation for a number of mobility models. In this model, each node selects a direction in which to travel from the range .…”

Section: Introductionmentioning

confidence: 99%

Real-world environment models for mobile network evaluation

Jardosh

Belding-Royer

Almeroth

et al. 2005

IEEE J. Select. Areas Commun.

142

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Abstract-Simulation environments are an important tool for the evaluation of new concepts in networking. The study of mobile ad hoc networks depends on understanding protocols from simulations, before these protocols are implemented in a real-world setting. To produce a real-world environment within which an ad hoc network can be formed among a set of nodes, there is a need for the development of realistic, generic and comprehensive mobility, and signal propagation models. In this paper, we propose the design of a mobility and signal propagation model that can be used in simulations to produce realistic network scenarios. Our model allows the placement of obstacles that restrict movement and signal propagation. Movement paths are constructed as Voronoi tessellations with the corner points of these obstacles as Voronoi sites. Our mobility model also introduces a signal propagation model that emulates properties of fading in the presence of obstacles. As a result, we have developed a complete environment in which network protocols can be studied on the basis of numerous performance metrics. Through simulation, we show that the proposed mobility model has a significant impact on network performance, especially when compared with other mobility models. In addition, we also observe that the performance of ad hoc network protocols is effected when different mobility scenarios are utilized.

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Channel occupancy time distribution in a cellular radio system

Cited by 373 publications

References 4 publications

The message delay in mobile ad hoc networks

The message delay in mobile ad hoc networks

Empirical Statistical Model for LTE Downlink Channel Occupancy

Real-world environment models for mobile network evaluation

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