Efficient Spectrum-Handoff Schemes For Cognitive Radio Networks

Abstract

Radio spectrum access is important for terrestrial wireless networks, commercial earth observations and

terrestrial radio astronomy observations. The services offered by terrestrial wireless networks, commercial

earth observations and terrestrial radio astronomy observations have evolved due to technological advances.

They are expected to meet increasing users’ demands which will require more spectrum. The increasing

demand for high throughput by users necessitates allocating additional spectrum to terrestrial wireless

networks. Terrestrial radio astronomy observations s require additional bandwidth to observe more spectral

windows. Commercial earth observation requires more spectrum for enhanced transmission of earth

observation data. The evolution of terrestrial wireless networks, commercial earth observations and terrestrial

radio astronomy observations leads to the emergence of new interference scenarios. For instance, terrestrial

wireless networks pose interference risks to mobile ground stations; while inter-satellite links can interfere

with terrestrial radio astronomy observations. Terrestrial wireless networks, commercial earth observations

and terrestrial radio astronomy observations also require mechanisms that will enhance the performance of

their users.

This thesis proposes a framework that prevents interference between terrestrial wireless networks,

commercial earth observations and terrestrial radio astronomy observations when they co-exist; and enhance

the performance of their users. The framework uses the cognitive radio; because it is capable of multi-context

operation.

In the thesis, two interference avoidance mechanisms are presented. The first mechanism prevents

interference between terrestrial radio astronomy observations and inter-satellite links. The second mechanism

prevent interference between terrestrial wireless networks and the commercial earth observation ground

segment. The first interference reductionmechanism determines the inter-satellite link transmission duration.

Analysis shows that interference-free inter-satellite links transmission is achievable during terrestrial radio

astronomy observation switching for up to 50.7 seconds. The second mechanism enables the mobile ground

station, with a trained neural network, to predict the terrestrial wireless network channel idle state. The

prediction of the TWN channel idle state prevents interference between the terrestrial wireless network and

the mobile ground station. Simulation shows that incorporating prediction in the mobile ground station

enhances uplink throughput by 40.6% and reduces latency by 18.6%.

In addition, the thesis also presents mechanisms to enhance the performance of the users in terrestrial

wireless network, commercial earth observations and terrestrial radio astronomy observations. The thesis

presents mechanisms that enhance user performance in homogeneous and heterogeneous terrestrial wireless

networks. Mechanisms that enhance the performance of LTE-Advanced users with learning diversity are

also presented. Furthermore, a future commercial earth observation network model that increases the

accessible earth climatic data is presented. The performance of terrestrial radio astronomy observation users is enhanced by presenting mechanisms that improve angular resolution, power efficiency and reduce

infrastructure costs.

The thesis develops a dual mode mechanism that uses learning and enhances user performance in

homogeneous and heterogeneous terrestrial wireless networks. It also proposes the incorporation of learningdiversity

selection and learning-classification pause to enhance performance of users (with learning diversity).

The mechanisms proposed to enhance user performance in terrestrial wireless network reduce the overhead

associated with learning-algorithm development in intelligent terrestrial wireless network users.

Terrestrial radio astronomy observation user performance is enhanced in a scenario comprising

multimode earth stations, ground based telescopes and high performance computing infrastructure. The

multimode earth stations and ground based telescopes co-exist with cognitive terrestrial wireless networks.

Interactions between terrestrial wireless networks and the high performance computing infrastructure enables

the terrestrial wireless network to make opportunistic use of the underutilised high performance computing

infrastructure. The terrestrial wireless network uses the underutilised high performance computing

infrastructure to train its learning algorithms thereby enhancing terrestrial radio astronomy observation power

efficiency and terrestrial wireless network autonomy. The use of multimode earth stations alongside ground

based telescopes enhance angular resolution and reduce terrestrial radio astronomy observation infrastructure

cost.

In addition, user performance in commercial earth observation networks is enhanced in the proposed

cognitive earth observation network. The cognitive earth observation network incorporates fractionated small

satellites and mobile ground stations in the space and ground segment, respectively. The space segment uses

a bio-inspired mechanism for fractionated satellite module sharing thereby making the cognitive earth

observation network robust to module failures. The cognitive earth observation network also enables users to

access more earth climatic data at higher throughput and low latency.

Furthermore, the thesis formulates performance models for mechanisms that improve user performance in

terrestrial wireless networks, commercial earth observations and terrestrial radio astronomy observations. The

performance benefits of these mechanisms are investigated via numerical simulation. The performance of the

dual mode mechanism proposed for terrestrial wireless network users without learning diversity is compared

with the existing channel state and the idle time. Analysis shows that the dual mode mechanism enhances

throughput by 31% and 36% in the homogeneous and heterogeneous mode, respectively. Numerical

simulations also show that using multimode earth station enhances terrestrial radio astronomy observation

angular resolution by 59.2%. In addition, high performance computing infrastructure-cognitive terrestrial

wireless network sharing enhances high performance computing infrastructure power efficiency by 8.31%.

Furthermore, the use of cognitive radio for fractionated satellite-module soft sharing increases the commercial

earth observation network’s accessible data by 20%.