2,373 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
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
Exploiting Multi-Antennas for Opportunistic Spectrum Sharing in Cognitive Radio Networks
In cognitive radio (CR) networks, there are scenarios where the secondary
(lower priority) users intend to communicate with each other by
opportunistically utilizing the transmit spectrum originally allocated to the
existing primary (higher priority) users. For such a scenario, a secondary user
usually has to trade off between two conflicting goals at the same time: one is
to maximize its own transmit throughput; and the other is to minimize the
amount of interference it produces at each primary receiver. In this paper, we
study this fundamental tradeoff from an information-theoretic perspective by
characterizing the secondary user's channel capacity under both its own
transmit-power constraint as well as a set of interference-power constraints
each imposed at one of the primary receivers. In particular, this paper
exploits multi-antennas at the secondary transmitter to effectively balance
between spatial multiplexing for the secondary transmission and interference
avoidance at the primary receivers. Convex optimization techniques are used to
design algorithms for the optimal secondary transmit spatial spectrum that
achieves the capacity of the secondary transmission. Suboptimal solutions for
ease of implementation are also presented and their performances are compared
with the optimal solution. Furthermore, algorithms developed for the
single-channel transmission are also extended to the case of multi-channel
transmission whereby the secondary user is able to achieve opportunistic
spectrum sharing via transmit adaptations not only in space, but in time and
frequency domains as well.Comment: Extension of IEEE PIMRC 2007. 35 pages, 6 figures. Submitted to IEEE
Journal of Special Topics in Signal Processing, special issue on Signal
Processing and Networking for Dynamic Spectrum Acces
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