382 research outputs found
Spectrum sensing and occupancy prediction for cognitive machine-to-machine wireless networks
A thesis submitted to the University of Bedfordshire, in partial
fulfil ment of the requirements for the degree of Doctor of Philosophy (PhD)The rapid growth of the Internet of Things (IoT) introduces an additional challenge to the existing spectrum under-utilisation problem as large scale deployments of thousands devices are expected to require wireless connectivity. Dynamic Spectrum
Access (DSA) has been proposed as a means of improving the spectrum utilisation of wireless systems. Based on the Cognitive Radio (CR) paradigm, DSA enables unlicensed spectrum users to sense their spectral environment and adapt their operational parameters to opportunistically access any temporally unoccupied bands without causing interference to the primary spectrum users. In the same context, CR inspired Machine-to-Machine (M2M) communications have recently been proposed as a potential solution to the spectrum utilisation problem, which has been driven by the ever increasing number of interconnected devices. M2M communications introduce new challenges for CR in terms of operational environments and design requirements. With spectrum sensing being the key function for CR, this
thesis investigates the performance of spectrum sensing and proposes novel sensing approaches and models to address the sensing problem for cognitive M2M deployments.
In this thesis, the behaviour of Energy Detection (ED) spectrum sensing for cognitive M2M nodes is modelled using the two-wave with dffi use power fading model. This channel model can describe a variety of realistic fading conditions including
worse than Rayleigh scenarios that are expected to occur within the operational environments of cognitive M2M communication systems. The results suggest that ED based spectrum sensing fails to meet the sensing requirements over worse than Rayleigh conditions and consequently requires the signal-to-noise ratio (SNR) to be increased by up to 137%. However, by employing appropriate diversity and node
cooperation techniques, the sensing performance can be improved by up to 11.5dB in terms of the required SNR. These results are particularly useful in analysing the eff ects of severe fading in cognitive M2M systems and thus they can be used
to design effi cient CR transceivers and to quantify the trade-o s between detection performance and energy e fficiency.
A novel predictive spectrum sensing scheme that exploits historical data of past sensing events to predict channel occupancy is proposed and analysed. This approach allows CR terminals to sense only the channels that are predicted to be
unoccupied rather than the whole band of interest. Based on this approach, a spectrum occupancy predictor is developed and experimentally validated. The proposed scheme achieves a prediction accuracy of up to 93% which in turn can lead to up to
84% reduction of the spectrum sensing cost. Furthermore, a novel probabilistic model for describing the channel availability
in both the vertical and horizontal polarisations is developed. The proposed model is validated based on a measurement campaign for operational scenarios where CR terminals may change their polarisation during their operation. A Gaussian approximation is used to model the empirical channel availability data with more than 95% confi dence bounds. The proposed model can be used as a means of improving
spectrum sensing performance by using statistical knowledge on the primary users occupancy pattern
Performance analyses and design for cognitive radios
Cognitive radio has been proposed as a promising solution to the conflict between
the spectrum scarcity and spectrum under-utilization. As the demand increases for
wireless communication services, cognitive radio technology attracts huge attention
from both commercial industries and academic researches. The purpose of this thesis
is to provide an analytical evaluation of the cognitive radio system performance
while taking into consideration of some realistic conditions. Several problems are
investigated in this thesis. First, by adopting a dynamic primary user traffic model
with one primary user occupancy status change and exponentially distributed channel
holding times, its effect on the cognitive radio system performance is evaluated.
In the evaluation, the sensing-throughput tradeoff of the cognitive radio is used
as the examination criteria, while energy detection is applied during the spectrum
sensing. The thesis then takes the investigation further by establishing a primary
user multiple changes traffic model which considers multiple primary user occupancy
status changes and any reasonable channel holding time distributions. The effect of
the primary user multiple changes traffic on the spectrum sensing performance is investigated
while the channel holding times are assumed to be exponential, Gamma,
Erlang and log-normal distributed. The analytical evaluation of cognitive radio is
also carried out from the secondary user transmission perspective, where the performance of the adaptive modulation in cognitive radio system is investigated. The
effect of the cognitive radio distinctive features on the performance of both the adaptive
continuous rate scheme and the adaptive discrete rate scheme of the adaptive
modulation are examined. The BER performance and the link spectral efficiency
performance are derived for both schemes.
A novel frame structure where the spectrum sensing is performed by using the
recovered received secondary frames is also evaluated in this thesis. A realistic
scenario which considers the secondary user signal decoding errors is examined for
the novel structure, while an ideal upper bound performance is given when the
decoding process is assumed perfect. By extending the system to include multiple
consecutive secondary frames, the performance of the novel structure is compared
to the performance of the traditional frame structure proposed by the IEEE 802.22
WRAN standard. The effect of the primary user multiple changes traffic is also
examined for the novel structure.
Several major findings are made from the analytical evaluations presented in
this thesis. Through numerical examinations, it was shown that, first, the dynamic
primary user traffic degrades the performance of cognitive radio systems. Second,
the degree of the performance degradation of the cognitive radio systems is related
to the number of primary user status changes and the primary user traffic intensity.
Different primary user channel holding times distributions also lead to different
sensitivities of the system performance to the primary user traffic. Third, cognitive
radio distinctive features degrades the performance of the adaptive modulation.
When the novel structure is applied for cognitive radio, a higher secondary achievable
throughput can be obtained with a limited saturation threshold
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Intelligent spectrum management techniques for wireless cognitive radio networks
PhD ThesisThis thesis addresses many of the unique spectrum management chal-
lenges in CR networks for the rst time. These challenges have a vital
e ect on the network performance and are particularly di cult to solve
due to the unique characteristics of CR networks. Speci cally, this thesis
proposes and investigates three intelligent spectrum management tech-
niques for CR networks. The issues investigated in this thesis have a
fundamental impact on the establishment, functionality and security of
CR networks.
First, an intelligent primary receiver-aware message exchange protocol
for CR ad hoc networks is proposed. It considers the problem of alleviat-
ing the interference collision risk to primary user communication, explic-
itly to protect primary receivers that are not detected during spectrum
sensing. The proposed protocol achieves a higher measure of safeguard-
ing. A practical scenario is considered where no global network topology
is known and no common control channel is assumed to exist.
Second, a novel CR broadcast protocol (CRBP) to reliably disseminate
the broadcast messages to all or most of the possible CR nodes in the
network is proposed. The CRBP formulates the broadcast problem as a
bipartite-graph problem. Thus, CRBP achieves a signi cant successful
delivery ratio by connecting di erent local topologies, which is a unique
feature in CR ad hoc networks.
Finally, a new defence strategy to defend against spectrum sensing data
falsi cation attacks in CR networks is proposed. In order to identify
malicious users, the proposed scheme performs multiple veri cations of
sensory data with the assistance of trusted nodes.Higher Committee For Education Devel-
opment in Iraq (HCED-Iraq
Interference Characterization in Multiple Access Wireless Networks
Contrarily to the point to point wireless link approach adopted in several wireless networks, where
a dedicated channel is usually supporting an exclusive-use wireless link, in the last years several
wireless communication systems have followed a different approach. In the so called “multiple
access wireless networks”, multiple transmitters share the same communication channel in a
simultaneous way, supporting a shared-use of the wireless link. The deployment of multiple access
networks has also originated the emergence of various communication networks operating in the
same geographical area and spectrum space, which is usually referred to as wireless coexistence.
As a consequence of the presence of multiple networks with different technologies that share the
same spectral bands, robust methods of interference management are needed. At the same time,
the adoption of in-band Full-duplex (IBFDX) communication schemes, in which a given node
transmit and receive simultaneously over the same frequency band, is seen as a disruptive topic in
multiple access networks, capable of doubling the network’s capacity.
Motivated by the importance of the interference in multiple access networks, this thesis addresses
new approaches to characterize the interference in multiple access networks. A special
focus is given to the assumption of mobility for the multiple transmitters. The problem of coexistence
interference caused by multiple networks operating in the same band is also considered.
Moreover, given the importance of the residual self-interference (SI) in practical IBFDX multiple
access networks, we study the distribution of the residual SI power in a wireless IBFDX
communication system. In addition, different applications of the proposed interference models
are presented, including the definition of a new sensing capacity metric for cognitive radio networks,
the performance evaluation of wireless-powered coexisting networks, the computation of
an optimal carrier-sensing range in coexisting CSMA networks, and the estimation of residual
self-interference in IBFDX communication systems
Providing efficient services for smartphone applications
Mobile applications are becoming an indispensable part of people\u27s lives, as they allow access to a broad range of services when users are on the go. We present our efforts towards enabling efficient mobile applications in smartphones. Our goal is to improve efficiency of the underlying services, which provide essential functionality to smartphone applications. In particular, we are interested in three fundamental services in smartphones: wireless communication service, power management service, and location reporting service.;For the wireless communication service, we focus on improving spectrum utilization efficiency for cognitive radio communications. We propose ETCH, a set of channel hopping based MAC layer protocols for communication rendezvous in cognitive radio communications. ETCH can fully utilize spectrum diversity in communication rendezvous by allowing all the rendezvous channels to be utilized at the same time.;For the power management service, we improve its efficiency from three different angles. The first angle is to reduce energy consumption of WiFi communications. We propose HoWiES, a system-for WiFi energy saving by utilizing low-power ZigBee radio. The second angle is to reduce energy consumption of web based smartphone applications. We propose CacheKeeper, which is a system-wide web caching service to eliminate unnecessary energy consumption caused by imperfect web caching in many smartphone applications. The third angle is from the perspective of smartphone CPUs. We found that existing CPU power models are ill-suited for modern multicore smartphone CPUs. We present a new approach of CPU power modeling for smartphones. This approach takes CPU idle power states into consideration, and can significantly improve power estimation accuracy and stability for multicore smartphones.;For the location reporting service, we aim to design an efficient location proof solution for mobile location based applications. We propose VProof, a lightweight and privacy-preserving location proof scheme that allows users to construct location proofs by simply extracting unforgeable information from the received packets
Performance analysis of spectrum sensing techniques for future wireless networks
In this thesis, spectrum sensing techniques are investigated for cognitive radio (CR) networks
in order to improve the sensing and transmission performance of secondary networks.
Specifically, the detailed exploration comprises of three areas, including single-node spectrum
sensing based on eigenvalue-based detection, cooperative spectrum sensing under random
secondary networks and full-duplex (FD) spectrum sensing and sharing techniques.
In the first technical chapter of this thesis, eigenvalue-based spectrum sensing techniques,
including maximum eigenvalue detection (MED), maximum minimum eigenvalue (MME)
detection, energy with minimum eigenvalue (EME) detection and the generalized likelihood
ratio test (GLRT) eigenvalue detector, are investigated in terms of total error rates and achievable
throughput. Firstly, in order to consider the benefits of primary users (PUs) and secondary
users (SUs) simultaneously, the optimal decision thresholds are investigated to minimize
the total error rate, i.e. the summation of missed detection and false alarm rate. Secondly,
the sensing-throughput trade-off is studied based on the GLRT detector and the optimal
sensing time is obtained for maximizing the achievable throughput of secondary communications
when the target probability of detection is achieved.
In the second technical chapter, the centralized GLRT-based cooperative sensing technique
is evaluated by utilizing a homogeneous Poisson point process (PPP). Firstly, since collaborating
all the available SUs does not always achieve the best sensing performance under a
random secondary network, the optimal number of cooperating SUs is investigated to minimize
the total error rate of the final decision. Secondly, the achievable ergodic capacity and
throughput of SUs are studied and the technique of determining an appropriate number of
cooperating SUs is proposed to optimize the secondary transmission performance based on a
target total error rate requirement.
In the last technical chapter, FD spectrum sensing (FDSS) and sensing-based spectrum sharing
(FD-SBSS) are investigated. There exists a threshold pair, not a single threshold, due to
the self-interference caused by the simultaneous sensing and transmission. Firstly, by utilizing
the derived expressions of false alarm and detection rates, the optimal decision threshold
pair is obtained to minimize total error rate for the FDSS scheme. Secondly, in order to further
improve the secondary transmission performance, the FD-SBSS scheme is proposed and
the collision and spectrum waste probabilities are studied. Furthermore, different antenna
partitioning methods are proposed to maximize the achievable throughput of SUs under both
FDSS and FD-SBSS schemes
Machine learning algorithms for cognitive radio wireless networks
In this thesis new methods are presented for achieving spectrum sensing in cognitive radio wireless networks. In particular, supervised, semi-supervised and unsupervised machine learning based spectrum sensing algorithms are developed and various techniques to improve their performance are described.
Spectrum sensing problem in multi-antenna cognitive radio networks is considered and a novel eigenvalue based feature is proposed which has the capability to enhance the performance of support vector machines algorithms for signal classification. Furthermore, spectrum sensing under multiple primary users condition is studied and a new re-formulation of the sensing task as a multiple class signal detection problem where each class embeds one or more states is presented. Moreover, the error correcting output codes based multi-class support vector machines algorithms is proposed and investigated for solving the multiple class signal detection problem using two different coding strategies.
In addition, the performance of parametric classifiers for spectrum sensing under slow fading channel is studied. To address the attendant performance degradation problem, a Kalman filter based channel estimation technique is proposed for tracking the temporally correlated slow fading channel and updating the decision boundary of the classifiers in real time. Simulation studies are included to assess the performance of the proposed schemes.
Finally, techniques for improving the quality of the learning features and improving the detection accuracy of sensing algorithms are studied and a novel beamforming based pre-processing technique is presented for feature realization in multi-antenna cognitive radio systems. Furthermore, using the beamformer derived features, new algorithms are developed for multiple hypothesis testing facilitating joint spatio-temporal spectrum sensing. The key performance metrics of the classifiers are evaluated to demonstrate the superiority of the proposed methods in comparison with previously proposed alternatives
Medium access control design for distributed opportunistic radio networks
Existing wireless networks are characterized by a fixed spectrum assignment policy. However, the scarcity of available spectrum and its inefficient usage demands for a new communication paradigm to exploit the existing spectrum opportunistically. Future Cognitive Radio (CR) devices should be able to sense unoccupied spectrum and will allow the deployment of real opportunistic networks. Still, traditional Physical (PHY) and Medium Access Control (MAC) protocols are not suitable for this new type of networks because they are optimized to operate over fixed assigned frequency bands. Therefore, novel PHY-MAC cross-layer protocols should be developed to cope with the specific features of opportunistic networks.
This thesis is mainly focused on the design and evaluation of MAC protocols for Decentralized Cognitive Radio Networks (DCRNs). It starts with a characterization of the spectrum sensing framework based on the Energy-Based Sensing (EBS) technique considering multiple scenarios. Then, guided by the sensing results obtained by the aforementioned technique, we present two novel decentralized CR MAC schemes: the first one designed to operate in single-channel scenarios and
the second one to be used in multichannel scenarios. Analytical models for the network goodput, packet service time and individual transmission probability are derived and used to compute the performance of both protocols. Simulation results assess the accuracy of the analytical models as well as the benefits of the proposed CR MAC schemes
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