Resource Allocation in Heterogeneous Buffered Cognitive Radio Networks

Abstract

Resources available for operation in cognitive radio networks (CRN) are generally limited, making it imperative for efficient resource allocation (RA) models to be designed for them. However, in most RA designs, a significant limiting factor to the RA's productivity has hitherto been mostly ignored, the fact that different users or user categories do have different delay tolerance profiles. To address this, in this paper, an appropriate RA model for heterogeneous CRN with delay considerations is developed and analysed. In the model, the demands of users are first categorised and then, based on the distances of users from the controlling secondary user base station and with the assumption that the users are mobile, the user demands are placed in different queues having different service capacities and the resulting network is analysed using queueing theory. Furthermore, to achieve optimality in the RA process, an important concept is introduced whereby some demands from one queue are moved to another queue where they have a better chance of enhanced service, thereby giving rise to the possibility of an improvement in the overall performance of the network. The performance results obtained from the analysis, particularly the blocking probability and network throughput, show that the queueing model incorporated into the RA process can help in achieving optimality for the heterogeneous CRN with buffered data.

Optimal Channel Allocation for QoS Provisioning in Cognitive Multihop Radio Adhoc Network

“…The solution outlined is developed with minimum primary user interference. In [23,24] a queue based mechanism is proposed, where the resource allocation is developed for a heterogeneous network under the constraint of delay consideration. The approach defines a channel allocation based ion the demanded service and the distance of each of the user giving different queue order to different service demands.…”

Spectrum monitoring in heterogeneous cognitive radio network: How to cooperate?

“…In the proposed CRN, the homogeneous/heterogeneous nature is considered in terms of probability of SM error which is due to different channel conditions and hardware impairments to every CU.’]. Awoyemi et al [15] have analysed and developed a resource allocation model for heterogeneous CRN with delay considerations.…”

“…Therefore, we have considered a practical scenario in which every CU has a different value of SM error due to different channel conditions and hardware impairments. Moreover, there is no mechanism to diminish the effect of imperfections in spectrum sensing [15], however, the improvement is achieved by using queuing theory only.…”