1,258 research outputs found
DISTRIBUTED INTELLIGENT SPECTRUM MANAGEMENT IN COGNITIVE RADIO AD HOC NETWORKS
The rapid growth of the number of wireless devices has brought an exponential increase in the demand of the radio spectrum. However, according to the Federal Communications Commission (FCC), almost all the radio spectrum for wireless com- munications has already been allocated. In addition, according to FCC, up to 85% of the allocated spectrum is underutilized due to the current fixed spectrum alloca- tion policy. To alleviate the spectrum scarcity problem, FCC has suggested a new paradigm for dynamically accessing the allocated spectrum. Cognitive radio (CR) technology has emerged as a promising solution to realize dynamic spectrum access (DSA). With the capability of sensing the frequency bands in a time and location- varying spectrum environment and adjusting the operating parameters based on the sensing outcome, CR technology allows an unlicensed user to exploit the licensed channels which are not used by licensed users in an opportunistic manner.
In this dissertation, distributed intelligent spectrum management in CR ad hoc networks is explored. In particular, four spectrum management issues in CR ad hoc networks are investigated: 1) distributed broadcasting in CR ad hoc networks; 2) distributed optimal HELLO message exchange in CR ad hoc networks; 3) distributed protocol to defend a particular network security attack in CR ad hoc networks; and 4) distributed spectrum handoff protocol in CR ad hoc networks. The research in this dissertation has fundamental impact on CR ad hoc network establishment, net- work functionality, network security, and network performance. In addition, many of the unique challenges of distributed intelligent spectrum management in CR ad hoc networks are addressed for the first time in this dissertation. These challenges are extremely difficult to solve due to the dynamic spectrum environment and they have significant effects on network functionality and performance. This dissertation
is essential for establishing a CR ad hoc network and realizing networking protocols for seamless communications in CR ad hoc networks. Furthermore, this dissertation provides critical theoretical insights for future designs in CR ad hoc networks
Capacity scaling law by multiuser diversity in cognitive radio systems
This paper analyzes the multiuser diversity gain in a cognitive radio (CR)
system where secondary transmitters opportunistically utilize the spectrum
licensed to primary users only when it is not occupied by the primary users. To
protect the primary users from the interference caused by the missed detection
of primary transmissions in the secondary network, minimum average throughput
of the primary network is guaranteed by transmit power control at the secondary
transmitters. The traffic dynamics of a primary network are also considered in
our analysis. We derive the average achievable capacity of the secondary
network and analyze its asymptotic behaviors to characterize the multiuser
diversity gains in the CR system.Comment: 5 pages, 2 figures, ISIT2010 conferenc
Channels Reallocation In Cognitive Radio Networks Based On DNA Sequence Alignment
Nowadays, It has been shown that spectrum scarcity increased due to
tremendous growth of new players in wireless base system by the evolution of
the radio communication. Resent survey found that there are many areas of the
radio spectrum that are occupied by authorized user/primary user (PU), which
are not fully utilized. Cognitive radios (CR) prove to next generation wireless
communication system that proposed as a way to reuse this under-utilised
spectrum in an opportunistic and non-interfering basis. A CR is a self-directed
entity in a wireless communications environment that senses its environment,
tracks changes, and reacts upon its findings and frequently exchanges
information with the networks for secondary user (SU). However, CR facing
collision problem with tracks changes i.e. reallocating of other empty channels
for SU while PU arrives. In this paper, channels reallocation technique based
on DNA sequence alignment algorithm for CR networks has been proposed.Comment: 12 page
Deep Learning Meets Cognitive Radio: Predicting Future Steps
Learning the channel occupancy patterns to reuse
the underutilised spectrum frequencies without interfering with
the incumbent is a promising approach to overcome the spectrum
limitations. In this work we proposed a Deep Learning (DL)
approach to learn the channel occupancy model and predict its
availability in the next time slots. Our results show that the
proposed DL approach outperforms existing works by 5%. We
also show that our proposed DL approach predicts the availability
of channels accurately for more than one time slot
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
Cognitive Radio Networks: Realistic or Not?
A large volume of research has been conducted in the cognitive radio (CR)
area the last decade. However, the deployment of a commercial CR network is yet
to emerge. A large portion of the existing literature does not build on real
world scenarios, hence, neglecting various important interactions of the
research with commercial telecommunication networks. For instance, a lot of
attention has been paid to spectrum sensing as the front line functionality
that needs to be completed in an efficient and accurate manner to enable an
opportunistic CR network architecture. This is necessary to detect the
existence of spectrum holes without which no other procedure can be fulfilled.
However, simply sensing (cooperatively or not) the energy received from a
primary transmitter cannot enable correct dynamic spectrum access. For example,
the low strength of a primary transmitter's signal does not assure that there
will be no interference to a nearby primary receiver. In addition, the presence
of a primary transmitter's signal does not mean that CR network users cannot
access the spectrum since there might not be any primary receiver in the
vicinity. Despite the existing elegant and clever solutions to the DSA problem
no robust, implementable scheme has emerged. In this paper, we challenge the
basic premises of the proposed schemes. We further argue that addressing the
technical challenges we face in deploying robust CR networks can only be
achieved if we radically change the way we design their basic functionalities.
In support of our argument, we present a set of real-world scenarios, inspired
by realistic settings in commercial telecommunications networks, focusing on
spectrum sensing as a basic and critical functionality in the deployment of
CRs. We use these scenarios to show why existing DSA paradigms are not amenable
to realistic deployment in complex wireless environments.Comment: Work in progres
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