Abstract
Radio channel reservation is used to alleviate call dropping which may occur in two situations: (i) hand-off between cells in cellular networks, and (ii) channel withdrawal in wireless networks with spectrum leasing. In this article, we study a radio resource reservation scheme for heterogeneous traffic in a cellular network with spectrum leasing, in which one reservation pool is used to alleviate the two types of call droppings. Since different types of traffic have different tolerances to the exhaustion of channels, it is critical for different types of traffic to select the optimal size of the reservation pool such that the channel requirements of different types of traffic are satisfied while throughput is maximized. A three-dimensional Markov chain is presented to find the optimal size of reservation pool. Numerical and simulation results show that (i) the selected parameters of reservation satisfy the quality-of-service requirements of different types of traffic while produce high throughput, and (ii) channel withdrawal yields higher impact on real-time traffic than non-real-time traffic in terms of throughput.
Highlights
Radio resource is scarce and precious; radio spectrum is underutilized in most wireless systems in which radio spectrum is statically assigned [1]
A system that leases out its radio channels to another always has the first priority to use its radio channels; that is, the system can withdraw its radio channels from another when the system requires the radio channels
When a channel is forcibly withdrawn from a mobile user, the mobile user releases the withdrawn channel and attempts to hand-off to another idle channel in order to continue its communication
Summary
Radio resource is scarce and precious; radio spectrum is underutilized in most wireless systems in which radio spectrum is statically assigned [1]. The thresholds reserve a number of free channels for those ongoing mobile users to continue their communications Under such a threshold based reservation architecture, call admission, inter-cell hand-off and channel withdrawal procedures are described in detail as follows. The quality-of-service metrics at different withdrawal ratios satisfy our objective; that is, (i) the inter-cell hand-off and withdrawal dropping probabilities of real-time and non-real-time users are kept below 0.04, and (ii) the waiting time of non-real-time users are below 5 seconds. Non-realtime users are less insensitive to the withdrawal ratio than real-time users
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