Interference-aware adaptive spectrum management for wireless networks using unlicensed frequency bands
View/ Open
thesis files.zip (4.135Mb)
Date
29/11/2012Author
Pediaditaki, Sofia
Metadata
Abstract
The growing demand for ubiquitous broadband network connectivity and continuously
falling prices in hardware operating on the unlicensed bands have put Wi-Fi
technology in a position to lead the way in rapid innovation towards high performance
wireless for the future. The success story of Wi-Fi contributed to the development of
widespread variety of options for unlicensed access (e.g., Bluetooth, Zigbee) and has
even sparked regulatory bodies in several countries to permit access to unlicensed devices
in portions of the spectrum initially licensed to TV services. In this thesis we
present novel spectrum management algorithms for networks employing 802.11 and
TV white spaces broadly aimed at efficient use of spectrum under consideration, lower
contention (interference) and high performance.
One of the target scenarios of this thesis is neighbourhood or citywide wireless
access. For this, we propose the use of IEEE 802.11-based multi-radio wireless mesh
network using omnidirectional antennae. We develop a novel scalable protocol termed
LCAP for efficient and adaptive distributed multi-radio channel allocation. In LCAP,
nodes autonomously learn their channel allocation based on neighbourhood and channel
usage information. This information is obtained via a novel neighbour discovery
protocol, which is effective even when nodes do not share a common channel. Extensive
simulation-based evaluation of LCAP relative to the state-of-the-art Asynchronous
Distributed Colouring (ADC) protocol demonstrates that LCAP is able to achieve its
stated objectives. These objectives include efficient channel utilisation across diverse
traffic patterns, protocol scalability and adaptivity to factors such as external interference.
Motivated by the non-stationary nature of the network scenario and the resulting
difficulty of establishing convergence of LCAP, we consider a deterministic alternative.
This approach employs a novel distributed priority-based mechanism where nodes decide
on their channel allocations based on only local information. Key enabler of this
approach is our neighbour discovery mechanism. We show via simulations that this
mechanism exhibits similar performance to LCAP.
Another application scenario considered in this thesis is broadband access to rural
areas. For such scenarios, we consider the use of long-distance 802.11 mesh networks
and present a novel mechanism to address the channel allocation problem in a
traffic-aware manner. The proposed approach employs a multi-radio architecture using
directional antennae. Under this architecture, we exploit the capability of the 802.11
hardware to use different channel widths and assign widths to links based on their relative
traffic volume such that side-lobe interference is mitigated. We show that this
problem is NP-complete and propose a polynomial time, greedy channel allocation
algorithm that guarantees valid channel allocations for each node. Evaluation of the
proposed algorithm via simulations of real network topologies shows that it consistently
outperforms fixed width allocation due to its ability to adapt to spatio-temporal
variations in traffic demands.
Finally, we consider the use of TV-white-spaces to increase throughput for in-home
wireless networking and relieve the already congested unlicensed bands. To the best
of our knowledge, our work is the first to develop a scalable micro auctioning mechanism
for sharing of TV white space spectrum through a geolocation database. The goal
of our approach is to minimise contention among secondary users, while not interfering
with primary users of TV white space spectrum (TV receivers and microphone
users). It enables interference-free and dynamic sharing of TVWS among home networks
with heterogeneous spectrum demands, while resulting in revenue generation
for database and broadband providers. Using white space availability maps from the
UK, we validate our approach in real rural, urban and dense-urban residential scenarios.
Our results show that our mechanism is able to achieve its stated objectives of
attractiveness to both the database provider and spectrum requesters, scalability and
efficiency for dynamic spectrum distribution in an interference-free manner.