1,699 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
Feasibility Conditions of Interference Alignment via Two Orthogonal Subcarriers
Conditions are derived on line-of-sight channels to ensure the feasibility of
interference alignment. The conditions involve choosing only the spacing
between two subcarriers of an orthogonal frequency division multiplexing (OFDM)
scheme. The maximal degrees-of-freedom are achieved and even an upper bound on
the sum-rate of interference alignment is approached arbitrarily closely.Comment: Submitted to ISIT 201
Interference Mitigation in Large Random Wireless Networks
A central problem in the operation of large wireless networks is how to deal
with interference -- the unwanted signals being sent by transmitters that a
receiver is not interested in. This thesis looks at ways of combating such
interference.
In Chapters 1 and 2, we outline the necessary information and communication
theory background, including the concept of capacity. We also include an
overview of a new set of schemes for dealing with interference known as
interference alignment, paying special attention to a channel-state-based
strategy called ergodic interference alignment.
In Chapter 3, we consider the operation of large regular and random networks
by treating interference as background noise. We consider the local performance
of a single node, and the global performance of a very large network.
In Chapter 4, we use ergodic interference alignment to derive the asymptotic
sum-capacity of large random dense networks. These networks are derived from a
physical model of node placement where signal strength decays over the distance
between transmitters and receivers. (See also arXiv:1002.0235 and
arXiv:0907.5165.)
In Chapter 5, we look at methods of reducing the long time delays incurred by
ergodic interference alignment. We analyse the tradeoff between reducing delay
and lowering the communication rate. (See also arXiv:1004.0208.)
In Chapter 6, we outline a problem that is equivalent to the problem of
pooled group testing for defective items. We then present some new work that
uses information theoretic techniques to attack group testing. We introduce for
the first time the concept of the group testing channel, which allows for
modelling of a wide range of statistical error models for testing. We derive
new results on the number of tests required to accurately detect defective
items, including when using sequential `adaptive' tests.Comment: PhD thesis, University of Bristol, 201
Feedback-Topology Designs for Interference Alignment in MIMO Interference Channels
Interference alignment (IA) is a joint-transmission technique that achieves
the capacity of the interference channel for high signal-to-noise ratios
(SNRs). Most prior work on IA is based on the impractical assumption that
perfect and global channel-state information(CSI) is available at all
transmitters. To implement IA, each receiver has to feed back CSI to all
interferers, resulting in overwhelming feedback overhead. In particular, the
sum feedback rate of each receiver scales quadratically with the number of
users even if the quantized CSI is fed back. To substantially suppress feedback
overhead, this paper focuses on designing efficient arrangements of feedback
links, called feedback topologies, under the IA constraint. For the
multiple-input-multiple-output (MIMO) K-user interference channel, we propose
the feedback topology that supports sequential CSI exchange (feedback and
feedforward) between transmitters and receivers so as to achieve IA
progressively. This feedback topology is shown to reduce the network feedback
overhead from a cubic function of K to a linear one. To reduce the delay in the
sequential CSI exchange, an alternative feedback topology is designed for
supporting two-hop feedback via a control station, which also achieves the
linear feedback scaling with K. Next, given the proposed feedback topologies,
the feedback-bit allocation algorithm is designed for allocating feedback bits
by each receiver to different feedback links so as to regulate the residual
interference caused by the finite-rate feedback. Simulation results demonstrate
that the proposed bit allocation leads to significant throughput gains
especially in strong interference environments.Comment: 28 pages; 11 figures ; submitted to IEEE Trans. on Signal Processin
Técnicas de equalização e pré-codificação para sistemas MC-CDMA
Mestrado em Engenharia Eletrónica e TelecomunicaçõesO número de dispositivos com ligações e aplicações sem fios está a aumentar exponencialmente, causando problemas de interferência e diminuindo a capacidade do sistema. Isto desencadeou uma procura por uma eficiência espectral superior e, consequentemente, tornou-se necessário desenvolver novas arquitecturas celulares que suportem estas novas exigências.
Coordenação ou cooperação multicelular é uma arquitectura promissora para sistemas celulares sem fios. Esta ajuda a mitigar a interferência entre células, melhorando a equidade e a capacidade do sistema. É, portanto, uma arquitectura já em estudo ao abrigo da tecnologia LTE-Advanced sob o conceito de coordenação multiponto (CoMP). Nesta dissertação, considerámos um sistema coordenado MC-CDMA com pré-codificação e equalização iterativas.
Uma das técnicas mais eficientes de pré-codificação é o alinhamento de interferências (IA). Este é um conceito relativamente novo que permite aumentar a capacidade do sistema em canais de elevada interferência. Sabe-se que, para os sistemas MC-CDMA, os equalizadores lineares convencionais não são os mais eficientes, devido à interferência residual entre portadoras (ICI). No entanto, a equalização iterativa no domínio da frequência (FDE) foi identificada como sendo uma das técnicas mais eficientes para lidar com ICI e explorar a diversidade oferecida pelos sistemas MIMO MC-CDMA. Esta técnica é baseada no conceito Iterative Block Decision Feedback Equalization (IB-DFE).
Nesta dissertação, é proposto um sistema MC-CDMA que une a pré-codificação iterativa do alinhamento de interferências no transmissor ao equalizador baseado no IB-DFE, com cancelamento sucessivo de interferências (SIC) no receptor. Este é construído por dois blocos: um filtro linear, que mitiga a interferência inter-utilizador, seguido por um bloco iterativo no domínio da frequência, que separa eficientemente os fluxos de dados espaciais na presença de interferência residual inter-utilizador alinhada. Este esquema permite atingir o número máximo de graus de liberdade e permite simultaneamente um ganho óptimo de diversidade espacial. O desempenho deste esquema está perto do filtro adaptado- Matched Filter Bound (MFB).The number of devices with wireless connections and applications is increasing exponentially, causing interference problems and reducing the system’s capacity gain. This initiated a search for a higher spectral efficiency and therefore it became necessary to develop new cellular architectures that support these new requirements.
Multicell cooperation or coordination is a promising architecture for cellular wireless systems to mitigate intercell interference, improving system fairness and increasing capacity, and thus is already under study in LTE-Advanced under the coordinated multipoint (CoMP) concept. In this thesis, efficient iterative precoding and equalization is considered for coordinated MC-CDMA based systems.
One of the most efficient precoding techniques is interference alignment (IA), which is a relatively new concept that allows high capacity gains in interfering channels. It is well known that for MC-CDMA systems standard linear equalizers are not the most efficient due to residual inter carrier interference (ICI). However, iterative frequency-domain equalization (FDE) has been identified as one of the most efficient technique to deal with ICI and exploit the inherent space-frequency diversity of the MIMO MC-CDMA systems, namely the one based on Iterative Block Decision Feedback Equalization (IB-DFE) concept.
In this thesis, it is proposed a MC-CDMA system that joins iterative IA precoding at the transmitter with IB-DFE successive interference cancellation (SIC) based receiver structure. The receiver is implemented in two steps: a linear filter, which mitigates the inter-user aligned interference, followed by an iterative frequency-domain receiver, which efficiently separates the spatial streams in the presence of residual inter-user aligned interference. This scheme provides the maximum degrees of freedom (DoF) and allows almost the optimum space-diversity gain. The scheme performance is close to the matched filter bound (MFB)
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