In this thesis, resource allocation and multiple access in cognitive radio (CR) and compressed sensing (CS)-based wireless networks are studied. Energy-efficiency oriented design becomes more and more important in wireless systems, which motivates us to propose a location-aware power strategy for single user and multiple users in CR systems and a CS-based processing in wireless sensor networks (WSNs) which reduces the number of data transmissions and energy consumption by utilizing sparsity of the transmitted data due to spatial correlation and temporal correlation.
In particular, the work on location-aware power allocation in CR system gives
a brief overview of the existing power allocation design in the literature and unifies
them into a general power allocation framework. The impact of the network topology on the system performance is highlighted, which motivates us to propose a novel
location-aware strategy that intelligently utilizes frequency and space opportunities
and minimizes the overall power consumption while maintaining the quality of service
(QoS) of the primary system. This work shows that in addition to exploring the
spectrum holes in time and frequency domains, spatial opportunities can be utilized
to further enhance energy efficiency for CR systems.
Then the work of resource allocation is extended to finding the power strategy
and channel allocation optimization for multiple secondary users in an orthogonal
frequency division multiplexing (OFDM) based cognitive radio network. Three different
spectrum access methods are considered and utilized adaptively according to
the different locations of the secondary users, and we unify these spectrum access
methods into a general resource allocation framework. An interference violation test
is proposed to decide the parameters in this framework that indicate the set of licensed
channels to be sensed. The proposed scheme intelligently utilizes frequency and space
opportunities, avoids unnecessary spectrum sensing and minimizes the overall power
consumption while maintaining the quality of service of the primary system. The
uncertainty of channel state information between the secondary users (SUs) and the
primary users (PUs) is also taken into account in the study of power and channel allocation
optimization of the SUs. Simulation results validate the effectiveness of the
proposed method in terms of energy efficiency and show that enhanced performance
can be obtained by utilizing spatial opportunities.
The work on CS-based WSNs considers the application of compressed sensing
to WSNs for data measurement communication and reconstruction, where N sensor
nodes compete for medium access to a single receiver. Sparsity of the sensor data in
three domains due to time correlation, space correlation and multiple access are being
utilized. A CS-based medium access control (MAC) scheme is proposed and an in depth analysis on this scheme from a physical layer perspective is provided to reveal
the impact of communication signal-to-noise ratio on the reconstruction performance.
We show the process of the sensor data converted to the modulated symbols for
physical layer transmission and how the modulated symbols recovered via compressed
sensing. This work further identifies the decision problem of distinguishing between
active and inactive transmitters after symbol recovery and provides a comprehensive
performance comparison between carrier sense multiple access and the proposed CSbased
scheme. Moreover, a network data recovery scheme that exploits both spatial
and temporal correlations is proposed. Simulation results validate the effectiveness of
the proposed method in terms of communication throughput and show that enhanced
performance can be obtained by utilizing the sensed signal’s temporal and spatial
correlations. / Graduate
Identifer | oai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/5916 |
Date | 18 March 2015 |
Creators | Xue, Tong |
Contributors | Dong, Xiaodai |
Source Sets | University of Victoria |
Language | English, English |
Detected Language | English |
Type | Thesis |
Rights | Available to the World Wide Web, http://creativecommons.org/licenses/by-nc-nd/2.5/ca/ |
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