3,431 research outputs found
Channel assembling and resource allocation in multichannel spectrum sharing wireless networks
Submitted in fulfilment of the academic requirements for the degree of
Doctor of Philosophy (Ph.D.) in Engineering, in the School of Electrical and
Information Engineering, Faculty of Engineering and the Built Environment,
at the University of the Witwatersrand, Johannesburg, South Africa, 2017The continuous evolution of wireless communications technologies has increasingly imposed a
burden on the use of radio spectrum. Due to the proliferation of new wireless networks applications
and services, the radio spectrum is getting saturated and becoming a limited resource. To a large
extent, spectrum scarcity may be a result of deficient spectrum allocation and management policies,
rather than of the physical shortage of radio frequencies. The conventional static spectrum
allocation has been found to be ineffective, leading to overcrowding and inefficient use. Cognitive
radio (CR) has therefore emerged as an enabling technology that facilitates dynamic spectrum
access (DSA), with a great potential to address the issue of spectrum scarcity and inefficient use.
However, provisioning of reliable and robust communication with seamless operation in cognitive
radio networks (CRNs) is a challenging task. The underlying challenges include development of
non-intrusive dynamic resource allocation (DRA) and optimization techniques.
The main focus of this thesis is development of adaptive channel assembling (ChA) and DRA
schemes, with the aim to maximize performance of secondary user (SU) nodes in CRNs, without
degrading performance of primary user (PU) nodes in a primary network (PN). The key objectives
are therefore four-fold. Firstly, to optimize ChA and DRA schemes in overlay CRNs. Secondly, to
develop analytical models for quantifying performance of ChA schemes over fading channels in
overlay CRNs. Thirdly, to extend the overlay ChA schemes into hybrid overlay and underlay
architectures, subject to power control and interference mitigation; and finally, to extend the
adaptive ChA and DRA schemes for multiuser multichannel access CRNs.
Performance analysis and evaluation of the developed ChA and DRA is presented, mainly through
extensive simulations and analytical models. Further, the cross validation has been performed
between simulations and analytical results to confirm the accuracy and preciseness of the novel
analytical models developed in this thesis. In general, the presented results demonstrate improved
performance of SU nodes in terms of capacity, collision probability, outage probability and forced
termination probability when employing the adaptive ChA and DRA in CRNs.CK201
Medium access in cognitive radio networks: From single hop to multiple hops
If channel assembling is enabled, this technique can be utilized for potential performance improvement in CRNs. Two use cases are envisaged for channel assembling. In the first use case, the system can accommodate parallel SU services in multiple channels, while in the second use case, the system allows only one SU service at a time. In the use case where parallel SU services are allowed, various channel assembling strategies are proposed and modeled in order to investigate their performance and to acquire better comprehension of the behavior of CRNs with channel assembling. Moreover, the capacity upper bound for CRNs with channel assembling in the quasistationary regime is derived. In the use case when there is only one SU service that can utilize the vacant channels at a time, we formulate channel access into two optimization problems on power allocation in multi-channel CRNs and propose various algorithms to solve these problems
A dynamic channel access strategy for underlay cognitive radio networks: Markov modelling and performance evaluation
[EN] Unlike in overlay cognitive radio networks, secondary users in underlay cognitive radio networks can access licensed
spectrum even at the presence of a primary user, given that the interference caused by the secondary transmission is
lower than a pre-specified threshold. Based on this underlay access principle, we propose in this paper a dynamic channel
access strategy for multi-channel cognitive radio networks. Different from existing underlay access techniques, channel
assembling, spectrum adaptation and restricted channel occupancy are also considered in the proposed strategy in order
to achieve better performance in the secondary network. Accordingly, a partial channel occupancy mode, which allows
secondary users to access a portion of a channel when co-existing with a primary user, is introduced in this study. The size
of this portion is adjusted by selecting an appropriate value of a configurable parameter ¿ in the partial channel occupancy
mode. The system performance is evaluated for both primary and secondary networks, and a comparison analysis is carried
out to assess the cost against the gain. Numerical results demonstrate that the proposed underlay channel access strategy
outperforms the corresponding overlay strategy in terms of secondary network capacity, blocking probability and dropping
probability. The cost and gain analysis identifies appropriate traffic conditions under which the overall system performance
could be improved by employing the proposed underlay strategy.The work of V. Pla was supported in part by the Ministry of Economy and Competitiveness of Spain under Grant TIN2013-47272-C2-1-R.Jalali, E.; Balapuwaduge, IAM.; Li, FY.; Pla, V. (2017). A dynamic channel access strategy for underlay cognitive radio networks: Markov modelling and performance evaluation. Transactions on Emerging Telecommunications Technologies. 28(1):1-11. https://doi.org/10.1002/ett.2928S11128
NS-2 based simulation framework for cognitive radio sensor networks
In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs
Optimization and Learning in Energy Efficient Cognitive Radio System
Energy efficiency and spectrum efficiency are two biggest concerns for wireless communication. The constrained power supply is always a bottleneck to the modern mobility communication system. Meanwhile, spectrum resource is extremely limited but seriously underutilized.
Cognitive radio (CR) as a promising approach could alleviate the spectrum underutilization and increase the quality of service. In contrast to traditional wireless communication systems, a distinguishing feature of cognitive radio systems is that the cognitive radios, which are typically equipped with powerful computation machinery, are capable of sensing the spectrum environment and making intelligent decisions. Moreover, the cognitive radio systems differ from traditional wireless systems that they can adapt their operating parameters, i.e. transmission power, channel, modulation according to the surrounding radio environment to explore the opportunity.
In this dissertation, the study is focused on the optimization and learning of energy efficiency in the cognitive radio system, which can be considered to better utilize both the energy and spectrum resources. Firstly, drowsy transmission, which produces optimized idle period patterns and selects the best sleep mode for each idle period between two packet transmissions through joint power management and transmission power control/rate selection, is introduced to cognitive radio transmitter. Both the optimal solution by dynamic programming and flexible solution by reinforcement learning are provided. Secondly, when cognitive radio system is benefited from the theoretically infinite but unsteady harvested energy, an innovative and flexible control framework mainly based on model predictive control is designed. The solution to combat the problems, such as the inaccurate model and myopic control policy introduced by MPC, is given. Last, after study the optimization problem for point-to-point communication, multi-objective reinforcement learning is applied to the cognitive radio network, an adaptable routing algorithm is proposed and implemented. Epidemic propagation is studied to further understand the learning process in the cognitive radio network
Channel assembling policies for heterogeneous fifth generation (5G) cognitive radio networks.
Doctor of Philosophy in Electronic Engineering. University of KwaZulu-Natal, Durban 2016.Abstract available in PDF file
Channel Access and Reliability Performance in Cognitive Radio Networks:Modeling and Performance Analysis
Doktorgradsavhandling ved Institutt for Informasjons- og kommunikasjonsteknologi, Universitetet i AgderAccording to the facts and figures published by the international telecommunication
union (ITU) regarding information and communication technology (ICT)
industry, it is estimated that over 3.2 billion people have access to the Internet in
2015 [1]. Since 2000, this number has been octupled. Meanwhile, by the end of
2015, there were more than 7 billion mobile cellular subscriptions in the world, corresponding
to a penetration rate of 97%. As the most dynamic segment in ICT,
mobile communication is providing Internet services and consequently the mobile broadband penetration rate has reached 47% globally. Accordingly, capacity,
throughput, reliability, service quality and resource availability of wireless services
become essential factors for future mobile and wireless communications. Essentially,
all these wireless technologies, standards, services and allocation policies
rely on one common natural resource, i.e., radio spectrum.
Radio spectrum spans over the electromagnetic frequencies between 3 kHz and
300 GHz. Existing radio spectrum access techniques are based on the fixed allocation
of radio resources. These methods with fixed assigned bandwidth for exclusive
usage of licensed users are often not efficient since most of the spectrum
bands are under-utilized, either/both in the space domain or/and in the time domain.
In reality, it is observed that many spectrum bands are largely un-occupied
in many places [2], [3]. For instance, the spectrum bands which are exclusively allocated
for TV broadcasting services in USA remain un-occupied from midnight to
early morning according to the real-life measurement performed in [4]. In addition
to the wastage of radio resources, spectrum under-utilization constraints spectrum
availability for other intended users. Furthermore, legacy fixed spectrum allocation
techniques are not capable of adapting to the changes and interactions in the system,
leading to degraded network performance.
Unlike in the static spectrum allocation, a fraction of the radio spectrum is
allocated for open access as license-free bands, e.g., the industrial, scientific and
medical (ISM) bands (902-928, 2400-2483.5, 5725-5850 MHz). In 1985, the federal
communications commission (FCC) permitted to use the ISM bands for private
and unlicensed occupancy, however, under certain restrictions on transmission
power [5]. Consequently, standards like IEEE 802.11 for wireless local area networks
(WLANs) and IEEE 802.15 for wireless personal area networks (WPAN)
have grown rapidly with open access spectrum policies in the 2.4 GHz and 5 GHz
ISM bands. With the co-existence of both similar and dissimilar radio technologies,
802.11 networks face challenges for providing satisfactory quality of service (QoS).
This and the above mentioned spectrum under-utilization issues motivate the spectrum
regulatory bodies to rethink about more flexible spectrum access for licenseexempt
users or more efficient radio spectrum management. Cognitive radio (CR) is
probably the most promising technology for achieving efficient spectrum utilization
in future wireless networks
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