201 research outputs found
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
Dynamic Resource Allocation in Cognitive Radio Networks: A Convex Optimization Perspective
This article provides an overview of the state-of-art results on
communication resource allocation over space, time, and frequency for emerging
cognitive radio (CR) wireless networks. Focusing on the
interference-power/interference-temperature (IT) constraint approach for CRs to
protect primary radio transmissions, many new and challenging problems
regarding the design of CR systems are formulated, and some of the
corresponding solutions are shown to be obtainable by restructuring some
classic results known for traditional (non-CR) wireless networks. It is
demonstrated that convex optimization plays an essential role in solving these
problems, in a both rigorous and efficient way. Promising research directions
on interference management for CR and other related multiuser communication
systems are discussed.Comment: to appear in IEEE Signal Processing Magazine, special issue on convex
optimization for signal processin
Convolutive superposition for multicarrier cognitive radio systems
Recently, we proposed a spectrum-sharing paradigm for single-carrier
cognitive radio (CR) networks, where a secondary user (SU) is able to maintain
or even improve the performance of a primary user (PU) transmission, while also
obtaining a low-data rate channel for its own communication. According to such
a scheme, a simple multiplication is used to superimpose one SU symbol on a
block of multiple PU symbols.The scope of this paper is to extend such a
paradigm to a multicarrier CR network, where the PU employs an orthogonal
frequency-division multiplexing (OFDM) modulation scheme. To improve its
achievable data rate, besides transmitting over the subcarriers unused by the
PU, the SU is also allowed to transmit multiple block-precoded symbols in
parallel over the OFDM subcarriers used by the primary system. Specifically,
the SU convolves its block-precoded symbols with the received PU data in the
time-domain, which gives rise to the term convolutive superposition. An
information-theoretic analysis of the proposed scheme is developed, which
considers different amounts of network state information at the secondary
transmitter, as well as different precoding strategies for the SU. Extensive
simulations illustrate the merits of our analysis and designs, in comparison
with conventional CR schemes, by considering as performance indicators the
ergodic capacity of the considered systems.Comment: 29 pages, 8 figure
A Cooperative Overlay Approach at the Physical Layer of Cognitive Radio for Digital Agriculture
In digital agriculture, the cognitive radio technology is being envisaged as solution to spectral shortage problems by allowing agricultural cognitive users to co-exist with noncognitive users in the same spectrum on the field. Cognitive radios increase system capacity and spectral efficiency by sensing the spectrum and adapting the transmission parameters. This design requires a robust, adaptable and flexible physical layer to support cognitive radio functionality. In this paper, a novel physical layer architecture for cognitive radio based on cognition, cooperation, and cognitive interference avoidance has been developed by using power control for digital agriculture applications. The design is based on sensing of spectrum usage, detecting the message/spreading code of noncognitive users, cognitive relaying, cooperation, and cognition of channel parameters. Moreover, the power and rate allocation, ergodic, and outage capacity formulas are also presented
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