Modelling opportunistic spectrum renting in mobile cellular networks

Do, Tien Van; H., Nam; Horváth, Ádám; Wang, Jinting

doi:10.1016/j.jnca.2015.02.007

Cited by 7 publications

(5 citation statements)

References 15 publications

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“…The first type is termed as (underlay network) in which unlicensed users might use the primary channels simultaneously with the licensed users, based on some predetermined conditions. The second type is called (overlay networks) where the unlicensed users are allowed at any given time to use the Primary Service Unit whilst it is unoccupied by licensed customers, more information was introduced by the authors of [18,22,26,29] . However, the current paper deals with overlay CRN, by modelling a system that contains two finite-source subsystems(Primary and Secondary).…”

Section: Introductionmentioning

confidence: 99%

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Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

Zaghouani¹,

Sztrik²

2020

AMI

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The current paper takes into consideration a cognitive radio network with impatient customers, by the help of finite-source retrial queueing system. We consider two different types of customers (Primary and Secondary) assigned to two interconnected frequency bands. A first frequency band with a priority queue and a second one with an orbit, both are respectively dedicated for the Primary Users (PUs) and Secondary Users (SUs). In case the servers are busy, both customers (Licensed and Unlicensed) join either the queue or the orbit. Before joining the orbit, secondary customers receive a random retrial time according to Exponential distribution, which is the holding time before the next retry. Unlicensed users (impatient) are obliged to leave the system once their total waiting time exceeds a given maximum waiting time.The novelty of this work is the investigation of the abandonment and its impact on several performance measures of the system such as the mean response time and waiting time of users, probability of abandonment of SU, etc. Several figures illustrate the problem in question by the help of simulation.

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Section: Introductionmentioning

confidence: 99%

“…If not, they will join automatically the orbit. From the orbit, the postponed requests retry to get the service after an exponentially distributed random interval, more details can be found in [6,8,18,22,24,29].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

Zaghouani¹,

Sztrik²

2020

AMI

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“…There are two types of CRN, the first is known as (underlay network) in which unlicensed users are entitled at the same time to use the primary channels with the PUs, depending on some predefined conditions. The second type is called (overlay networks) where the secondary customers are allowed to use the Primary Service Unit if this unit does not contain licensed customers, more explanation was introduced by the authors of [10,13,16]. Theoretically, the current paper treats the second mentioned type of CRN (overlay), by modeling a CRN that uses two finite-source subsystems with non-reliable servers (Primary and Secondary) exposed to breakdowns and repairs.…”

Section: Introductionmentioning

confidence: 99%

“…If not, they must join the orbit automatically. Canceled requests in the orbit retry to be served after an exponentially distributed random interval, more details can be found in [2,3,10,13,14,16]. The servers used in our network are subject to some random breakdowns the interrupted requests are sent to the queue or to the orbit, respectively.…”

Section: Introductionmentioning

confidence: 99%

Simulation of the performance of CognitiveRadio Networks with unreliable servers

Zaghouani¹,

Sztrik²,

Uka³

2020

AMI

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This paper deals with a Cognitive Radio Network (CRN) which is modeled using a retrial queuing system with two finite-sources. This network includes two non-independent service units treating two types of users: Primary Users (PU) and Secondary Users (SU). The primary unit has priority queue (FIFO) and a second service unit contains an orbit both units are dedicated for the Primary Users and Secondary Users, respectively.The current work highlights the unreliability of the servers as we are assuming that both servers of this network are subject to random breakdowns and repairs. All the inter-event times in this CRN are either exponentially or non-exponentially distributed. The novelty of our investigation is to analyze the effect of several distributions (Gamma, Pareto, Log-normal, Hypo-Exponential and Hyper-Exponential) of the failure and repair times on the main performance measure of the system. By the help of simulation we show some interesting results concerning to sensitivity problems.

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“…By means of CRs cooperation, the network is able to sense its environment, learn from the history, and accordingly decide the best spectrum settings. Many researches have dealt with the opportunistic use of this latter, see for example [5,11].…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of finite-source cognitive radio networks with non-reliable services using simulation

Nemouchi¹,

Sztrik²

2018

AMI

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The cognitive radio (CR) is a dynamic spectrum access technique which provides the capability to share a wireless channel between licensed and unlicensed users opportunistically (also called Primary Users-PU and Secondary Users-SU). In this paper, stochastic simulation is used for performance evaluation of cognitive radio network. A finite-source retrial queuing model with two service units is proposed. A priority queue and an orbit are assigned to the PUs and SUs respectively. The proposed queueing system contains two interconnected, not independent subsystems. The Primary Channel Service (PCS) and the Secondary Channel Service (SCS) are not reliable and the services are assumed to be subject to a random failure with probability p1 and p2 for the PCS and SCS, respectively. The failure can be detected after the service and the request retransmission process starts immediately. The novelty of this work is to analyze the effect of the failure probability on the mean and the variance of the response time of the PUs and SUs, and on the Utilization of the PCS and SCS. The inter-event times are supposed to be exponentially, hypo-exponentially and hyper-exponentially distributed random variables, depending on different cases during simulation. By the help of simulation we compare the effect of the non-reliability of the servers in different combination of distributions on the first and second moments of the response times of the requests, and the utilization of the

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Modelling opportunistic spectrum renting in mobile cellular networks

Cited by 7 publications

References 15 publications

Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

Performance evaluation of finite-source Cognitive Radio Networks with impatient customers

Simulation of the performance of CognitiveRadio Networks with unreliable servers

Performance evaluation of finite-source cognitive radio networks with non-reliable services using simulation

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