5G Based on Cognitive Radio

Badoi, Cornelia-Ionela; Prasad, Neeli R.; Croitoru, Victor; Prasad, Ramjee

doi:10.1007/s11277-010-0082-9

Cited by 105 publications

(33 citation statements)

References 35 publications

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“…Researcher has divided cognitive radio resources into in to three major categories radio resources, computing resources and application resources [19]. Another major application of cognitive radio is adaptation which means selecting proper value of cognitive radio parameter…”

Section: Hybrid Technique: Coherent / Energy Detection Based Sensingmentioning

confidence: 99%

Journey of Mobile Generation and Cognitive Radio Technology in 5G

De¹,

Singh²

2016

IJMNCT

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Section: Hybrid Technique: Coherent / Energy Detection Based Sensingmentioning

confidence: 99%

Journey of Mobile Generation and Cognitive Radio Technology in 5G

De¹,

Singh²

2016

IJMNCT

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“…This helps in reducing the energy consumption, but the issue of smooth handoff is a major concern. Badoi et al [42] discuss the potential of combining cognitive radio with 5G network to provide smart application (WISDOM) [43] service for mobile users. As suggested by the authors, 5G converges the various existing technologies like 3G, 4G, Bluetooth, WiFi and the main task is to intelligently choose the medium for connecting with the outside world.…”

Section: Compatibility With Future Technologiesmentioning

confidence: 99%

Handoff Strategy for Improving Energy Efficiency and Cloud Service Availability for Mobile Devices

Ravi

Peddoju

2014

Wireless Pers Commun

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The increase in capabilities of mobile devices to perform computation tasks has led to increase in energy consumption. While offloading the computation tasks helps in reducing the energy consumption, service availability is a cause of major concern. Thus, the main objective of this work is to reduce the energy consumption of mobile device, while maximising the service availability for users. The multi-criteria decision making (MCDM) TOPSIS method prioritises among the service providing resources such as Cloud, Cloudlet and peer mobile devices. The superior one is chosen for offloading. While availing service from a resource, the proposed fuzzy vertical handoff algorithm triggers handoff from a resource to another, when the energy consumption of the device increases or the connection time with the resource decreases. In addition, parallel execution of tasks is performed to conserve energy of the mobile device. The results of experimental setup with opennebula Cloud platform, Cloudlets and Android mobile devices on various network environments, suggest that handoff from one resource to another is by far more beneficial in terms of energy consumption and service availability for mobile users.

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“…A heterogeneous network architecture exploits Radio Access Network (RAN) cell topologies, employing macro and various kinds of smaller (e.g. micro, pico and femto) cells, as well as several technologies together to offer wireless services [9,10].…”

Section: Existing Mobile Technologies For Energy Conservationmentioning

confidence: 99%

An energy-aware scheme for efficient spectrum utilization in a 5G mobile cognitive radio network architecture

et al. 2014

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This paper proposes an energy-efficient delayaware cooperative scheme, exploited for efficient resource management and maximum energy conservation in a 5G mobile cognitive radio network architecture. The proposed scheme is based on the comparison of the queuing delays of both the secondary nodes and the Radio Access Points, when delay sensitive transmission is requested, providing optimal TV White Spaces exploitation via a spectrum broker. The spectrum broker manages the process of the energy consumption of the 5G mobile communication systems, according to the proposed delay-aware cooperative scheme and the comparative evaluation of the queuing delays. The validity of the performance of the scheme is verified through extended simulation tests, carried out under controlled experimental conditions.

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5G Based on Cognitive Radio

Cited by 105 publications

References 35 publications

Journey of Mobile Generation and Cognitive Radio Technology in 5G

Journey of Mobile Generation and Cognitive Radio Technology in 5G

Handoff Strategy for Improving Energy Efficiency and Cloud Service Availability for Mobile Devices

An energy-aware scheme for efficient spectrum utilization in a 5G mobile cognitive radio network architecture

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