1,546 research outputs found
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Transmit without regrets: Online optimization in MIMO-OFDM cognitive radio systems
In this paper, we examine cognitive radio systems that evolve dynamically
over time due to changing user and environmental conditions. To combine the
advantages of orthogonal frequency division multiplexing (OFDM) and
multiple-input, multiple-output (MIMO) technologies, we consider a MIMO-OFDM
cognitive radio network where wireless users with multiple antennas communicate
over several non-interfering frequency bands. As the network's primary users
(PUs) come and go in the system, the communication environment changes
constantly (and, in many cases, randomly). Accordingly, the network's
unlicensed, secondary users (SUs) must adapt their transmit profiles "on the
fly" in order to maximize their data rate in a rapidly evolving environment
over which they have no control. In this dynamic setting, static solution
concepts (such as Nash equilibrium) are no longer relevant, so we focus on
dynamic transmit policies that lead to no regret: specifically, we consider
policies that perform at least as well as (and typically outperform) even the
best fixed transmit profile in hindsight. Drawing on the method of matrix
exponential learning and online mirror descent techniques, we derive a
no-regret transmit policy for the system's SUs which relies only on local
channel state information (CSI). Using this method, the system's SUs are able
to track their individually evolving optimum transmit profiles remarkably well,
even under rapidly (and randomly) changing conditions. Importantly, the
proposed augmented exponential learning (AXL) policy leads to no regret even if
the SUs' channel measurements are subject to arbitrarily large observation
errors (the imperfect CSI case), thus ensuring the method's robustness in the
presence of uncertainties.Comment: 25 pages, 3 figures, to appear in the IEEE Journal on Selected Areas
in Communication
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
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
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