12,317 research outputs found
Location-aided Distributed Primary User Identification in a Cognitive Radio Scenario
We address a cognitive radio scenario, where a number of secondary users
performs identification of which primary user, if any, is transmitting, in a
distributed way and using limited location information. We propose two fully
distributed algorithms: the first is a direct identification scheme, and in the
other a distributed sub-optimal detection based on a simplified Neyman-Pearson
energy detector precedes the identification scheme. Both algorithms are studied
analytically in a realistic transmission scenario, and the advantage obtained
by detection pre-processing is also verified via simulation. Finally, we give
details of their fully distributed implementation via consensus averaging
algorithms.Comment: Submitted to IEEE ICASSP201
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
201
Spatio-temporal spectrum sensing in cognitive radio networks using Beamformer-Aided SVM algorithms
This paper addresses the problem of spectrum sensing in multi-antenna cognitive radio system using support vector machine (SVM) algorithms. First, we formulated the spectrum
sensing problem under multiple primary users scenarios as a multiple state signal detection problem. Next, we propose a novel,
beamformer aided feature realization strategy for enhancing the capability of the SVM for signal classification under both single
and multiple primary users conditions. Then, we investigate the error correcting output codes (ECOC) based multi-class SVM algorithms and provide a multiple independent model
(MIM) alternative for solving the multiple state spectrum sensing problem. The performance of the proposed detectors is quantified in terms of probability of detection, probability of false alarm,
receiver operating characteristics (ROC), area under ROC curves (AuC) and overall classification accuracy. Simulation results show that the proposed detectors are robust to both temporal and joint spatio-temporal detection of spectrum holes in cognitive radio networks
Distributed primary user identification from imprecise location information
We study a cognitive radio scenario in which the network of sec- ondary users wishes to identify which primary user, if any, is trans- mitting. To achieve this, the nodes will rely on some form of location information. In our previous work we proposed two fully distributed algorithms for this task, with and without a pre-detection step, using propagation parameters as the only source of location information. In a real distributed deployment, each node must estimate its own po- sition and/or propagation parameters. Hence, in this work we study the effect of uncertainty, or error in these estimates on the proposed distributed identification algorithms. We show that the pre-detection step significantly increases robustness against uncertainty in nodes' locations
Information reuse in dynamic spectrum access
Dynamic spectrum access (DSA), where the permission to use slices of radio spectrum is dynamically shifted (in time an in different geographical areas) across various communications services and applications, has been an area of interest from technical and public policy perspectives over the last decade. The underlying belief is that this will increase spectrum utilization, especially since many spectrum bands are relatively unused, ultimately leading to the creation of new and innovative services that exploit the increase in spectrum availability. Determining whether a slice of spectrum, allocated or licensed to a primary user, is available for use by a secondary user at a certain time and in a certain geographic area is a challenging task. This requires 'context information' which is critical to the operation of DSA. Such context information can be obtained in several ways, with different costs, and different quality/usefulness of the information. In this paper, we describe the challenges in obtaining this context information, the potential for the integration of various sources of context information, and the potential for reuse of such information for related and unrelated purposes such as localization and enforcement of spectrum sharing. Since some of the infrastructure for obtaining finegrained context information is likely to be expensive, the reuse of this infrastructure/information and integration of information from less expensive sources are likely to be essential for the economical and technological viability of DSA. © 2013 IEEE
Byzantine Attack and Defense in Cognitive Radio Networks: A Survey
The Byzantine attack in cooperative spectrum sensing (CSS), also known as the
spectrum sensing data falsification (SSDF) attack in the literature, is one of
the key adversaries to the success of cognitive radio networks (CRNs). In the
past couple of years, the research on the Byzantine attack and defense
strategies has gained worldwide increasing attention. In this paper, we provide
a comprehensive survey and tutorial on the recent advances in the Byzantine
attack and defense for CSS in CRNs. Specifically, we first briefly present the
preliminaries of CSS for general readers, including signal detection
techniques, hypothesis testing, and data fusion. Second, we analyze the spear
and shield relation between Byzantine attack and defense from three aspects:
the vulnerability of CSS to attack, the obstacles in CSS to defense, and the
games between attack and defense. Then, we propose a taxonomy of the existing
Byzantine attack behaviors and elaborate on the corresponding attack
parameters, which determine where, who, how, and when to launch attacks. Next,
from the perspectives of homogeneous or heterogeneous scenarios, we classify
the existing defense algorithms, and provide an in-depth tutorial on the
state-of-the-art Byzantine defense schemes, commonly known as robust or secure
CSS in the literature. Furthermore, we highlight the unsolved research
challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral
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