Abstract
A cellular communication system is divided into two main parts, core network, and radio access network. This research is concerned with the radio access network part which consists of multiple-cells, each served by a central located base station. Furthermore, the users in each cell are considered to be uniformly distributed inside the cell. In the downlink context, the users’ packets usually arrive at the base station via fiber optic and then are relayed to the users via radio waves of certain frequency/ies. The speeds of delivering users’ packets vary, depending on the users’ location. In this paper, the actual distribution of the service time over different users whose locations are uniformly distributed in a cell served by one base station is analytically found. Simulation results are presented to validate the derived model.
Highlights
Deploying a wireless system can be quite costly
In the cellular radio access network (RAN) where each cell is served by one central base station (BS), users are usually distributed within the cell according to a uniform distribution
From queuing theory perspective, when the packets arrive at a service facility according to Poison distribution, and being serviced in a time that is exponentially distributed, the resulted queue is denoted by M/M/1
Summary
Deploying a wireless system can be quite costly. vendors and operators do extensive simulations before deploying any system to make sure that it is going to work properly as anticipated, and the investment will pay off. M stands for “Memoryless” which is a property of the exponential distribution, and 1 indicates the existence of only one server in the facility This model is the simplest among different queue models [3]. Since the backhaul of the BS is connected to a single reliable fiber optic channel, the inter-arrival time of the packets to the BS may be modeled as an exponential random variable [6]. The time required to send packets is a random variable, but cannot be modeled as exponentially distributed because these packets belong to many users with different channels to the BS. The statistical distribution of the service time required to deliver packets from the BS to the users is analytically derived. The impact of the derived service time distribution is highlighted from the queuing theory perspective
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