637 research outputs found
Full-Duplex Cognitive Radio: A New Design Paradigm for Enhancing Spectrum Usage
With the rapid growth of demand for ever-increasing data rate, spectrum
resources have become more and more scarce. As a promising technique to
increase the efficiency of the spectrum utilization, cognitive radio (CR)
technique has the great potential to meet such a requirement by allowing
un-licensed users to coexist in licensed bands. In conventional CR systems, the
spectrum sensing is performed at the beginning of each time slot before the
data transmission. This unfortunately results in two major problems: 1)
transmission time reduction due to sensing, and 2) sensing accuracy impairment
due to data transmission. To tackle these problems, in this paper we present a
new design paradigm for future CR by exploring the full-duplex (FD) techniques
to achieve the simultaneous spectrum sensing and data transmission. With FD
radios equipped at the secondary users (SUs), SUs can simultaneously sense and
access the vacant spectrum, and thus, significantly improve sensing
performances and meanwhile increase data transmission efficiency. The aim of
this article is to transform the promising conceptual framework into the
practical wireless network design by addressing a diverse set of challenges
such as protocol design and theoretical analysis. Several application scenarios
with FD enabled CR are elaborated, and key open research directions and novel
algorithms in these systems are discussed
Interference Alignment for Cognitive Radio Communications and Networks: A Survey
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).Interference alignment (IA) is an innovative wireless transmission strategy that has shown to be a promising technique for achieving optimal capacity scaling of a multiuser interference channel at asymptotically high-signal-to-noise ratio (SNR). Transmitters exploit the availability of multiple signaling dimensions in order to align their mutual interference at the receivers. Most of the research has focused on developing algorithms for determining alignment solutions as well as proving interference alignment’s theoretical ability to achieve the maximum degrees of freedom in a wireless network. Cognitive radio, on the other hand, is a technique used to improve the utilization of the radio spectrum by opportunistically sensing and accessing unused licensed frequency spectrum, without causing harmful interference to the licensed users. With the increased deployment of wireless services, the possibility of detecting unused frequency spectrum becomes diminished. Thus, the concept of introducing interference alignment in cognitive radio has become a very attractive proposition. This paper provides a survey of the implementation of IA in cognitive radio under the main research paradigms, along with a summary and analysis of results under each system model.Peer reviewe
Interference mitigation under degrees-of-freedom sensing uncertainties in opportunistic transmission
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Inter-system interference may limit the performance of co-existing systems in dense heterogeneous wireless networks. Context-aware waveform design can profitably overcome this limitation. However, the latter substantially depends on degrees-of-freedom (DoF) sensing mechanisms. In this work, we show that total least-squares (TLS)-based waveform design is robust against sensing uncertainties. Given the equivalence of minimum norm and TLS, the latter exhibits the good properties of linear predictors, which are of paramount importance to guarantee minimum inter-system interference and detectability by neighboring nodes. Additionally, since derived solution relies on orthogonal projector onto the so- called noise subspace, we can efficiently and iteratively construct an orthogonal waveform-book enabling the presented transmission scheme in multi-carrier scenarios. Simulation results are presented to support our theoretical contributions, and to highlight any potential advantage of proposed solution in crowded heterogenous wireless networks.This work has been supported by the Spanish Ministry of Science, Innovation and Universities through project WINTER: TEC2016-76409-C2-1-R (AEI/FEDER, UE) and fellowship FPI BES-2017-080071, and by the Catalan Government (AGAUR) under grant 2017 SGR 578.Peer ReviewedPostprint (published version
Joint Channel Assignment and Opportunistic Routing for Maximizing Throughput in Cognitive Radio Networks
In this paper, we consider the joint opportunistic routing and channel
assignment problem in multi-channel multi-radio (MCMR) cognitive radio networks
(CRNs) for improving aggregate throughput of the secondary users. We first
present the nonlinear programming optimization model for this joint problem,
taking into account the feature of CRNs-channel uncertainty. Then considering
the queue state of a node, we propose a new scheme to select proper forwarding
candidates for opportunistic routing. Furthermore, a new algorithm for
calculating the forwarding probability of any packet at a node is proposed,
which is used to calculate how many packets a forwarder should send, so that
the duplicate transmission can be reduced compared with MAC-independent
opportunistic routing & encoding (MORE) [11]. Our numerical results show that
the proposed scheme performs significantly better that traditional routing and
opportunistic routing in which channel assignment strategy is employed.Comment: 5 pages, 4 figures, to appear in Proc. of IEEE GlobeCom 201
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
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