Delay analysis of multihop cognitive radio networks using network of virtual priority queues

Abstract

In this paper, we characterize the average end-toend delay and maximum achievable per-node throughput in an opportunistic secondary cognitive radio network co-existing with a primary network where both networks consist of static nodes that use random medium access schemes. Assuming an ideal sensing mechanism, we first model the secondary network as a two-class priority queuing network and use queuing approximation techniques to obtain a set of relations involving the mean and second moments of the inter-arrival time and service-time of packets at a secondary node. Then, utilizing these parameters in an equivalent open G/G/1 queuing network, we obtain closed form expressions for average end-to-end delay of a packet in the secondary network and the maximum achievable throughput of a secondary node. The results are validated against extensive simulations.

A Comprehensive Review on Spectrum Management, Security and Energy-Efficient Cognitive Radio Networks

“…This methodology in traditional MANET cannot use CR ad hoc networks and fails to indicate unique characteristics in multi-channel multi-hop ad hoc CR network. Dibakar et al, [89] developed two multi-hop ad-hoc networks, That uses IEEE 802.11 based MAC protocol. It allows variant channel priority of access and probabilistic routing protocol considered ideal sensing process.…”

Spatial–Temporal Queuing Theoretic Modeling of Opportunistic Multihop Wireless Networks With and Without Cooperation

“…The assumption of exponential distributions is motivated by[30]. In[30] authors exploit the memoryless property of exponential distributions to show that this assumption leads to tractable analysis for IEEE 802.11 networks.Results obtained using their model were found to be highly accurate in predicting behavior of the IEEE 802.11 MAC protocol 3. In general ξ is not constant but depends on number of contending nodes.…”

“…The average end-toend delay is the end-to-end delay averaged over all received packets and network topologies and it depends on the traffic pattern, number of nodes, MAC scheme and routing protocol. To the best of our knowledge, no previous work (except our preliminary work in [3]) addressed the average end-to-end de-D. Das lay in such a setting. We introduce a modified protocol model of interference to account for packet loss during transmission due to fading.…”