87 research outputs found
A Distributed Approach to Interference Alignment in OFDM-based Two-tiered Networks
In this contribution, we consider a two-tiered network and focus on the
coexistence between the two tiers at physical layer. We target our efforts on a
long term evolution advanced (LTE-A) orthogonal frequency division multiple
access (OFDMA) macro-cell sharing the spectrum with a randomly deployed second
tier of small-cells. In such networks, high levels of co-channel interference
between the macro and small base stations (MBS/SBS) may largely limit the
potential spectral efficiency gains provided by the frequency reuse 1. To
address this issue, we propose a novel cognitive interference alignment based
scheme to protect the macro-cell from the cross-tier interference, while
mitigating the co-tier interference in the second tier. Remarkably, only local
channel state information (CSI) and autonomous operations are required in the
second tier, resulting in a completely self-organizing approach for the SBSs.
The optimal precoder that maximizes the spectral efficiency of the link between
each SBS and its served user equipment is found by means of a distributed
one-shot strategy. Numerical findings reveal non-negligible spectral efficiency
enhancements with respect to traditional time division multiple access
approaches at any signal to noise (SNR) regime. Additionally, the proposed
technique exhibits significant robustness to channel estimation errors,
achieving remarkable results for the imperfect CSI case and yielding consistent
performance enhancements to the network.Comment: 15 pages, 10 figures, accepted and to appear in IEEE Transactions on
Vehicular Technology Special Section: Self-Organizing Radio Networks, 2013.
Authors' final version. Copyright transferred to IEE
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 in Frequency Hopping Ad Hoc Networks
Radio systems today exhibit a degree of flexibility that was unheard of only a few years ago. Software-defined radio architectures have emerged that are able to service large swathes of spectrum, covering up to several GHz in the UHF bands. This dissertation investigates interference mitigation techniques in frequency hopping ad hoc networks that are capable of exploiting the frequency agility of software-defined radio platforms
Rethinking Information Theory for Mobile Ad Hoc Networks
The subject of this paper is the long-standing open problem of developing a
general capacity theory for wireless networks, particularly a theory capable of
describing the fundamental performance limits of mobile ad hoc networks
(MANETs). A MANET is a peer-to-peer network with no pre-existing
infrastructure. MANETs are the most general wireless networks, with single-hop,
relay, interference, mesh, and star networks comprising special cases. The lack
of a MANET capacity theory has stunted the development and commercialization of
many types of wireless networks, including emergency, military, sensor, and
community mesh networks. Information theory, which has been vital for links and
centralized networks, has not been successfully applied to decentralized
wireless networks. Even if this was accomplished, for such a theory to truly
characterize the limits of deployed MANETs it must overcome three key
roadblocks. First, most current capacity results rely on the allowance of
unbounded delay and reliability. Second, spatial and timescale decompositions
have not yet been developed for optimally modeling the spatial and temporal
dynamics of wireless networks. Third, a useful network capacity theory must
integrate rather than ignore the important role of overhead messaging and
feedback. This paper describes some of the shifts in thinking that may be
needed to overcome these roadblocks and develop a more general theory that we
refer to as non-equilibrium information theory.Comment: Submitted to IEEE Communications Magazin
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