Energy Efficiency Metrics in Cognitive Radio Networks: A Hollistic Overview

Orumwense, Efe Francis; Afullo, Thomas J.; Srivastava, Viranjay M.

doi:10.17762/ijcnis.v8i2.1805

Cited by 3 publications

(2 citation statements)

References 41 publications

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“…The component level metric measures the performance of specific wireless communications equipment such as power supply, power amplifier, and antennae [65]. Equipment level metrics serve to assess the operation of network nodes such as UEs and BSs, and network level metrics assess network access node performance in terms of coverage area and desired QoS [66].…”

Section: Energy and Spectrum Efficiencymentioning

confidence: 99%

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

et al. 2022

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One major influence on the future deployment of cellular networks will be a continuous increase in traffic inside mobile broadband systems. Moreover, traditional macrocell-based mobile communication networks will struggle to keep up with the enormous expansion in the demand for communications services in the future. Densification of networks is required if we are to meet the comprehensive needs for end terminals for a wide range of applications. One of the leading concepts in this competitive environment is the Ultra-Dense Network (UDN) where the access nodes and/or the communication links per unit area are densified, with the aim of improving overall network performance. The location of the UDN nodes meets the criteria for symmetry with a high probability. Ultra-dense cell deployment aims to reduce the physical distance between the transmitter and receiver in order to boost system performance and generally optimize the values of a wide variety of key performance indicators (KPIs). This paper aims to provide a taxonomy of UDNs and specifically of UDN-related KPIs. Initially, we address the complex questions “What is the current understanding of what ultra-dense networks are and what they should be, and how can we measure their performance?” by shedding light on the fundamental characteristics of UDNs.

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Section: Energy and Spectrum Efficiencymentioning

confidence: 99%

Ultra-Dense Networks: Taxonomy and Key Performance Indicators

et al. 2022

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“…Ad hoc networks consisting of portable devices (at least in part), energy management is of prime importance because of the limited energy availability in the portable devices. A key challenge in such networks is prolonging the lifetime of the networks by reducing energy consumption [19]. This can be supported by energy-efficient routing [20].…”

Section: Introductionmentioning

confidence: 99%

Energy Aware Multipath Routing Protocol for Cognitive Radio Ad Hoc Networks

Kamruzzaman

Fernando²,

Jaseemuddin³

2022

Int. j. commun. netw. inf. secur.

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Cognitive radio networks (CRNs) emerged as a paradigm to solve the problem of limited spectrum availability and the spectrum underutilization in wireless networks by opportunistically exploiting portions of the spectrum temporarily vacated by licensed primary users (PUs). Routing in CRNs is a challenging problem due to the PU activities and mobility. On the other hand, energy aware routing is very important in energy-constraint CRNs. In addition, it is crucial that CR users efficiently exchange data with each other before the appearance of PUs. To design a robust routing scheme for mobile CR ad hoc networks (CRANs), the constraints on residual energy of each CR user, reliability, and the protection of PUs must additionally be taken into account. Moreover, multipath routing has great potential for improving the end-to-end performance of ad hoc networks. Considering all these evidences, in this paper, we propose an energy aware on-demand multipath routing (EOMR) protocol for mobile CRANs to ensure the robustness and to improve the throughput. The proposed routing scheme involves energy efficient multipath route selection and spectrum allocation jointly. The simulation results show that our approach improves the overall performance of the network.

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