guard channels
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2021 ◽  
Vol 13 (04) ◽  
pp. 85-100
Author(s):  
Dang Thanh Chuong ◽  
Hoa Ly Cuong ◽  
Pham Trung Duc ◽  
Duong Duc Hung

In this article, a retrial queueing model will be considered with persevering customers for wireless cellular networks which can be frequently applied in the Fractional Guard Channel (FGC) policies, including Limited FGC (LFGC), Uniform FGC (UFGC), Limited Average FGC (LAFGC) and Quasi Uniform FGC (QUFGC). In this model, the examination on the retrial phenomena permits the analyses of important effectiveness measures pertained to the standard of services undergone by users with the probability that a fresh call first arrives the system and find all busy channels at the time, the probability that a fresh call arrives the system from the orbit and find all busy channels at the time and the probability that a handover call arrives the system and find all busy channels at the time. Comparison between four types of the FGC policy can befound to evaluate the performance of the system.


2021 ◽  
Vol 40 (1) ◽  
pp. 109-114
Author(s):  
O.A. Ojesanmi ◽  
O.A. Lawal ◽  
F.T. Ibharalu ◽  
I.A. Adejumobi

Dynamic Guard Channels (DCG) reduces the dropping and blocking rates in a network. However, most of the existing DGC allocations are not quite efficient because there were consideration for only the Handoff (HO) calls while the New calls (NC) were not considered; this leads to poor Quality of Service (QoS) for NC. Although it is better to give priority to HO calls over NC since the breaking of the connection of an established communicationis more annoying than blocking a NC. Thus, there is need to provide an alternative approach that guarantees an acceptable QoS in terms of both the HC and the NC. This paper presents the performance evaluation of an adaptive guard channel allocation; the scheme made use of two different models (1) guard channel with fuzzy logic (2) guard channel without fuzzy logic. Priority is given to handoff call due to the scarcity of radio spectrum. When all the guard channels have been allocated and the arrival rate of handoff calls keeps on increasing, new set of threshold values would be estimated by fuzzy logic model. Performance metrics are; Call Blocking Rate (CBR), Call Dropping Rate (CDR) and Throughput. Results showed that guard channel with fuzzy logic has the CBR values range from 24.02% to 69.015 and CDR values range from 12.025 to 18.90% while guard channel without fuzzy logic has CBR values range from 28.22% to 75.65% and CDR values range from 19.06% to 36.50%. The scheme proved to be more efficient in congestion control in wireless network.


Author(s):  
Adeyinka A. Adewale ◽  
Emmanuel R. Adagunodo ◽  
Samuel N. John ◽  
Victor O. Matthews ◽  
Adebiyi A. Adelakun

2016 ◽  
Vol 2016 ◽  
pp. 1-23 ◽  
Author(s):  
Kazuki Kajiwara ◽  
Tuan Phung-Duc

This paper considers a retrial queueing model where a group of guard channels is reserved for priority and retrial customers. Priority and normal customers arrive at the system according to two distinct Poisson processes. Priority customers are accepted if there is an idle channel upon arrival while normal customers are accepted if and only if the number of idle channels is larger than the number of guard channels. Blocked customers (priority or normal) join a virtual orbit and repeat their attempts in a later time. Customers from the orbit (retrial customers) are accepted if there is an idle channel available upon arrival. We formulate the queueing system using a level dependent quasi-birth-and-death (QBD) process. We obtain a Taylor series expansion for the nonzero elements of the rate matrices of the level dependent QBD process. Using the expansion results, we obtain an asymptotic upper bound for the joint stationary distribution of the number of busy channels and that of customers in the orbit. Furthermore, we develop an efficient numerical algorithm to calculate the joint stationary distribution.


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