134 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
Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks
Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum.
This has motivated the concept of opportunistic spectrum sharing or
the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic
user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction
of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques.
In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation
has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with
multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has
also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage
of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of
interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies
Degrees of Freedom and Achievable Rate of Wide-Band Multi-cell Multiple Access Channels With No CSIT
This paper considers a -cell multiple access channel with inter-symbol
interference. The primary finding of this paper is that, without instantaneous
channel state information at the transmitters (CSIT), the sum
degrees-of-freedom (DoF) of the considered channel is
with when the number of users per cell is sufficiently large,
where is the ratio of the maximum channel-impulse-response (CIR) length
of desired links to that of interfering links in each cell. Our finding implies
that even without instantaneous CSIT, \textit{interference-free DoF per cell}
is achievable as approaches infinity with a sufficiently large number
of users per cell. This achievability is shown by a blind interference
management method that exploits the relativity in delay spreads between desired
and interfering links. In this method, all inter-cell-interference signals are
aligned to the same direction by using a discrete-Fourier-transform-based
precoding with cyclic prefix that only depends on the number of CIR taps. Using
this method, we also characterize the achievable sum rate of the considered
channel, in a closed-form expression.Comment: Submitted to IEEE Transactions on Communication
MIMO Interference Alignment Over Correlated Channels with Imperfect CSI
Interference alignment (IA), given uncorrelated channel components and
perfect channel state information, obtains the maximum degrees of freedom in an
interference channel. Little is known, however, about how the sum rate of IA
behaves at finite transmit power, with imperfect channel state information, or
antenna correlation. This paper provides an approximate closed-form
signal-to-interference-plus-noise-ratio (SINR) expression for IA over
multiple-input-multiple-output (MIMO) channels with imperfect channel state
information and transmit antenna correlation. Assuming linear processing at the
transmitters and zero-forcing receivers, random matrix theory tools are
utilized to derive an approximation for the post-processing SINR distribution
of each stream for each user. Perfect channel knowledge and i.i.d. channel
coefficients constitute special cases. This SINR distribution not only allows
easy calculation of useful performance metrics like sum rate and symbol error
rate, but also permits a realistic comparison of IA with other transmission
techniques. More specifically, IA is compared with spatial multiplexing and
beamforming and it is shown that IA may not be optimal for some performance
criteria.Comment: 21 pages, 7 figures, submitted to IEEE Transactions on Signal
Processin
Multi-cell cooperation for future wireless systems
Portuguese CADWIN - PTDC/EEA TEL/099241/2008Portuguese Foundation for Science and Technology (FCT
Experimental evaluation of interference alignment for broadband WLAN systems
In this paper, we present an experimental study on the performance of spatial interference alignment (IA) in indoor wireless local area network scenarios that use orthogonal frequency division multiplexing (OFDM) according to the physical-layer specifications of the IEEE 802.11a standard. Experiments have been carried out using a wireless network testbed capable of implementing a 3-user MIMO interference channel. We have implemented IA decoding schemes that can be designed according to distinct criteria (e.g., zero-forcing or MaxSINR). The measurement methodology has been validated considering practical issues like the number of OFDM training symbols used for channel estimation or feedback time. In case of asynchronous users, a time-domain IA decoding filter is also compared to its frequency domain counterpart. We also evaluated the performance of IA from bit error ratio measurement-based results in comparison to different time-division multiple access transmission schemes. The comparison includes single- and multiple-antenna systems transmitting over the dominant mode of the MIMO channel. Our results indicate that spatial IA is suitable for practical indoor scenarios in which wireless channels often exhibit relatively large coherence times.This work has been supported by Xunta de Galicia, MINECO of Spain, and by
FEDER funds of the E.U. under Grant 2012/287, Grant TEC2013-47141-C4-R
(RACHEL project), Grant CSD2008-00010 (COMONSENS project), and FPU
Grants AP2010-2189 and AP2009-1105
Técnicas de pré-codificação para sistemas multicelulares coordenados
Doutoramento em TelecomunicaçõesCoordenação Multicélula é um tópico de investigação em rápido
crescimento e uma solução promissora para controlar a interferência entre
células em sistemas celulares, melhorando a equidade do sistema e
aumentando a sua capacidade. Esta tecnologia já está em estudo no LTEAdvanced
sob o conceito de coordenação multiponto (COMP). Existem
várias abordagens sobre coordenação multicélula, dependendo da
quantidade e do tipo de informação partilhada pelas estações base, através
da rede de suporte (backhaul network), e do local onde essa informação é
processada, i.e., numa unidade de processamento central ou de uma forma
distribuída em cada estação base.
Nesta tese, são propostas técnicas de pré-codificação e alocação de
potência considerando várias estratégias: centralizada, todo o
processamento é feito na unidade de processamento central; semidistribuída,
neste caso apenas parte do processamento é executado na
unidade de processamento central, nomeadamente a potência alocada a
cada utilizador servido por cada estação base; e distribuída em que o
processamento é feito localmente em cada estação base. Os esquemas
propostos são projectados em duas fases: primeiro são propostas soluções
de pré-codificação para mitigar ou eliminar a interferência entre células,
de seguida o sistema é melhorado através do desenvolvimento de vários
esquemas de alocação de potência. São propostas três esquemas de
alocação de potência centralizada condicionada a cada estação base e com
diferentes relações entre desempenho e complexidade. São também
derivados esquemas de alocação distribuídos, assumindo que um sistema
multicelular pode ser visto como a sobreposição de vários sistemas com
uma única célula. Com base neste conceito foi definido uma taxa de erro
média virtual para cada um desses sistemas de célula única que compõem
o sistema multicelular, permitindo assim projectar esquemas de alocação
de potência completamente distribuídos.
Todos os esquemas propostos foram avaliados em cenários realistas,
bastante próximos dos considerados no LTE. Os resultados mostram que
os esquemas propostos são eficientes a remover a interferência entre
células e que o desempenho das técnicas de alocação de potência
propostas é claramente superior ao caso de não alocação de potência. O
desempenho dos sistemas completamente distribuídos é inferior aos
baseados num processamento centralizado, mas em contrapartida podem
ser usados em sistemas em que a rede de suporte não permita a troca de
grandes quantidades de informação.Multicell coordination is a promising solution for cellular wireless systems
to mitigate inter-cell interference, improving system fairness and
increasing capacity and thus is already under study in LTE-A under the
coordinated multipoint (CoMP) concept. There are several coordinated
transmission approaches depending on the amount of information shared
by the transmitters through the backhaul network and where the
processing takes place i.e. in a central processing unit or in a distributed
way on each base station.
In this thesis, we propose joint precoding and power allocation techniques
considering different strategies: Full-centralized, where all the processing
takes place at the central unit; Semi-distributed, in this case only some
process related with power allocation is done at the central unit; and Fulldistributed,
where all the processing is done locally at each base station.
The methods are designed in two phases: first the inter-cell interference is
removed by applying a set of centralized or distributed precoding vectors;
then the system is further optimized by centralized or distributed power
allocation schemes. Three centralized power allocation algorithms with
per-BS power constraint and different complexity tradeoffs are proposed.
Also distributed power allocation schemes are proposed by considering
the multicell system as superposition of single cell systems, where we
define the average virtual bit error rate (BER) of interference-free single
cell system, allowing us to compute the power allocation coefficients in a
distributed manner at each BS.
All proposed schemes are evaluated in realistic scenarios considering LTE
specifications. The numerical evaluations show that the proposed schemes
are efficient in removing inter-cell interference and improve system
performance comparing to equal power allocation. Furthermore, fulldistributed
schemes can be used when the amounts of information to be
exchanged over the backhaul is restricted, although system performance is
slightly degraded from semi-distributed and full-centralized schemes, but
the complexity is considerably lower. Besides that for high degrees of
freedom distributed schemes show similar behaviour to centralized ones
Blind Interference Alignment in General Heterogeneous Networks
Heterogeneous networks have a key role in the design of future mobile
communication networks, since the employment of small cells around a macrocell
enhances the network's efficiency and decreases complexity and power demand.
Moreover, research on Blind Interference Alignment (BIA) has shown that optimal
Degrees of Freedom (DoF) can be achieved in certain network architectures, with
no requirement of Channel State Information (CSI) at the transmitters. Our
contribution is a generalised model of BIA in a heterogeneous network with one
macrocell with K users and K femtocells each with one user, by using Kronecker
(Tensor) Product representation. We introduce a solution on how to vary
beamforming vectors under power constraints to maximize the sum rate of the
network and how optimal DoF can be achieved over K+1 time slots.Comment: 5 pages, 7 figures, accepted to IEEE PIMRC'1
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