Figures 1 and 2 schematically illustrate considered scenarios of processing of high and low priority users in the cell of Cognitive Radio Network with servers reservation...
Abstract:
We analyse a cell of Cognitive Radio Network ( CRN ) as the multiline queueing system supplying service to two Markovian arrival flows of users. Primary (or licensed) u...Show MoreMetadata
Abstract:
We analyse a cell of Cognitive Radio Network ( CRN ) as the multiline queueing system supplying service to two Markovian arrival flows of users. Primary (or licensed) users called as High Priority Users ( HPU\text{s} ) have a preemptive priority over the secondary (cognitive) users called as Low Priority Users ( LPU\text{s} ). The HPU\text{s} are dropped upon the arrival only if all servers are occupied by HPU\text{s} . If at the arrival epoch all servers are busy but some of them provide service to LPU\text{s} , service of one LPU is immediately interrupted and service of the HPU begins in the released server. A LPU is accepted only if the number of busy servers at arrival epoch is less than the defined in advance threshold M . Otherwise, the LPU is permanently lost or becomes a retrial user. A retrial user repeats attempts to receive service later after random time intervals. The LPU whose service is interrupted is either lost or transferred to a virtual place called as orbit. The users placed in the orbit may be impatient and can renege the system. The service time follows an exponential probability distribution with the rate determined by the user’s type. After loss of a HPU , admission of LPU\text{s} is blocked. LPU\text{s} are informed that their access is temporarily suspended and do not generate new requests until blocking expires. The purpose of the research is the optimization of threshold M and admission blocking period duration. Behavior of the system is described by a multidimensional continuous-time Markov chain. Its generator, ergodicity condition and invariant distribution are derived. Expressions for performance indicators are given. Numerical results demonstrating usefulness of blocking and significance of account of correlation in arrivals are presented. E.g., in the presented example of cost criterion optimization blocking gives 18 percent profit comparing to the system without blocking.
Figures 1 and 2 schematically illustrate considered scenarios of processing of high and low priority users in the cell of Cognitive Radio Network with servers reservation...
Published in: IEEE Access ( Volume: 11)