Artificial bee colony–based spectrum handoff algorithm in wireless cognitive radio networks

Abstract

In this work, we proposed a new artificial bee colony-based spectrum handoff algorithm for wireless cognitive radio systems. In our wireless cognitive radio system, primary users, secondary users, and related base stations exist in the same communication environment. For our artificial bee colony-based algorithm, secondary users that always struggle to discover an idle channel have a leading role. While honey bees work hard to find the best-quality nectar source for foraging, secondary users try to find idle channels for making communication. In this way, secondary users are organized for different missions such as sensing and handoff similar to honey bees to minimize spectrum handoff delay by working together. In the spectrum handoff stage, some secondary users must sense the spectrum so that the interrupted secondary user may perform the spectrum handoff process. In our developed spectrum handoff algorithm, the spectrum availability characteristic is observed on the basis of the missions of the bees in the artificial bee colony algorithm with the aim of minimizing the spectrum handoff delay and maximizing probability of finding an idle channel.With the help of the algorithm that is developed using the artificial bee colony, spectrum handoff delay of secondary users is considerably decreased for different number of users without reducing probability of finding an available channel.

Review on cross‐layer design for cognitive ad‐hoc and sensor network

“…It is also assumed that PU entrance rate into the channel can be Rate entrance and PU departure rate from channel can be Rate dep . Keeping this into mind, the probabilities of PU being in ON state (P (PU ON )) and PU being in OFF state (P (PU OFF )) can be expressed as follows: (1) The above equation gives an idea about the probabilities of PU's presence and absence in the network. This model is found to be most commonly used for PU activities in a CRAHN.…”

“…This leaves the nodes having incomplete topology information of the network leading to probability of more collision interference among SUs and even in PU network. Challenge 3: spectrum handover [1]; due to dynamic changes in the spectrum from one frequency channel to another, there exist good chances of wireless communication adversities like latency, path loss, interference, packet drop, retransmission and many more which are undesirable. Challenge 4: multihop routing; typical ad-hoc network consists of multi-hop architecture.…”

Dynamic Smart Grid Communication Parameters Based Cognitive Radio Network

“…Due to the rapid development of smart grids, an increasing number of smart meters have been installed in the HAN, thus the amount of data to be transmitted is growing rapidly. Furthermore, the emerging new paradigms, such as the internet of things (IoT), device-to-device (D2D) communication, and smart appliances, are expected to have a massive spectrum demand [5]. Therefore, more spectrum bands are required to provide an accurate and flexible wireless communication in the smart grid, and this requirement presents a significant challenge in originally scarce spectrum resources [6].…”