CSPA: Channel Selection and Parameter Adaptation scheme based on genetic algorithm for cognitive radio Ad Hoc networks

Abstract

The cognitive radio (CR) is evolved as the potential technology to solve the problem of spectrum scarcity and to meet the stringent requirements of upcoming wireless services. CR has two distinct features, the spectrum sensing and the parameter adaptation. The former feature helps the CR to find the vacant spectrum slots/channels in the radio band while the latter mechanism allows it to adjust the operating parameters (e.g. frequency band, modulation and power, etc.) accordingly. The primary user (PU) activity has serious effects on the overall performance of the cognitive radio network (CRN).The CR should vacate the channel if it detects the arrival of the primary user (PU) in order to avoid the interference. The channel eviction/switching phenomenon severely degrade the quality of service (QoS) of the CR user and it is perhaps the key challenge for the CRN. In this paper, we propose the dynamic channel selection and parameter adaptation (CSPA) scheme based on the genetic algorithm to provide better QoS for the CR by selecting a best channel in terms of the quality, the power and the PU activity. The CSPA deals with the problem of channel switchings and it provides better QoS to the CR user. Simulation results prove that CSPA outperforms the existing schemes in terms of channel switchings, average service time, power and throughput.

A Decentralized Heuristic Approach towards Resource Allocation in Femtocell Networks

“…The related work presented here is divided into three parts including: broader survey on resource allocation and telecommunication networking [10][11][12][13][14], previous studies on resource allocation and power control in femtocells [15][16][17][18][19] and the decentralized approaches within the context of femtocells [20,21].…”

“…A survey of ant colony optimization within the context of resource allocation is presented in [13]. Also, the optimization of resource allocation within the context of cognitive radios is presented in [14].…”

Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks

“…However, most of the existing algorithms rank channels based only on the availability, which can lead to the selection of a channel with low occupancy, but it can be of low quality. Some other algorithms such as the one given in [27][28][29][30][31] consider the quality of the channel, but this occurs only after the selection of the channel to adapt the parameters of transmission according to the condition of the selected channel. …”

Device Centric Throughput and QoS Optimization for IoTsin a Smart Building Using CRN-Techniques

“…The work in the domain of channel assignment of CRNs can be classified based on their architecture (centralized or distributed), allocation behavior (cooperative or non-cooperative), access technology (underlay or overlay) and scope (intra or inter) [33,34,35]. The research articles [27,34,35] are focused on the QoS provisioning in CRNs, but they are inclined towards cellular communication.…”