338 research outputs found
Linear Precoding and Equalization for Network MIMO with Partial Cooperation
A cellular multiple-input multiple-output (MIMO) downlink system is studied
in which each base station (BS) transmits to some of the users, so that each
user receives its intended signal from a subset of the BSs. This scenario is
referred to as network MIMO with partial cooperation, since only a subset of
the BSs are able to coordinate their transmission towards any user. The focus
of this paper is on the optimization of linear beamforming strategies at the
BSs and at the users for network MIMO with partial cooperation. Individual
power constraints at the BSs are enforced, along with constraints on the number
of streams per user. It is first shown that the system is equivalent to a MIMO
interference channel with generalized linear constraints (MIMO-IFC-GC). The
problems of maximizing the sum-rate(SR) and minimizing the weighted sum mean
square error (WSMSE) of the data estimates are non-convex, and suboptimal
solutions with reasonable complexity need to be devised. Based on this,
suboptimal techniques that aim at maximizing the sum-rate for the MIMO-IFC-GC
are reviewed from recent literature and extended to the MIMO-IFC-GC where
necessary. Novel designs that aim at minimizing the WSMSE are then proposed.
Extensive numerical simulations are provided to compare the performance of the
considered schemes for realistic cellular systems.Comment: 13 pages, 5 figures, published in IEEE Transactions on Vehicular
Technology, June 201
Network MIMO with Partial Cooperation between Radar and Cellular Systems
To meet the growing spectrum demands, future cellular systems are expected to
share the spectrum of other services such as radar. In this paper, we consider
a network multiple-input multiple-output (MIMO) with partial cooperation model
where radar stations cooperate with cellular base stations (BS)s to deliver
messages to intended mobile users. So the radar stations act as BSs in the
cellular system. However, due to the high power transmitted by radar stations
for detection of far targets, the cellular receivers could burnout when
receiving these high radar powers. Therefore, we propose a new projection
method called small singular values space projection (SSVSP) to mitigate these
harmful high power and enable radar stations to collaborate with cellular base
stations. In addition, we formulate the problem into a MIMO interference
channel with general constraints (MIMO-IFC-GC). Finally, we provide a solution
to minimize the weighted sum mean square error minimization problem (WSMMSE)
with enforcing power constraints on both radar and cellular stations.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission
from IEEE must be obtained for all other uses, in any current or future
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redistribution to servers or lists, or reuse of any copyrighted component of
this work in other work
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
Ubiquitous Cell-Free Massive MIMO Communications
Since the first cellular networks were trialled in the 1970s, we have
witnessed an incredible wireless revolution. From 1G to 4G, the massive traffic
growth has been managed by a combination of wider bandwidths, refined radio
interfaces, and network densification, namely increasing the number of antennas
per site. Due its cost-efficiency, the latter has contributed the most. Massive
MIMO (multiple-input multiple-output) is a key 5G technology that uses massive
antenna arrays to provide a very high beamforming gain and spatially
multiplexing of users, and hence, increases the spectral and energy efficiency.
It constitutes a centralized solution to densify a network, and its performance
is limited by the inter-cell interference inherent in its cell-centric design.
Conversely, ubiquitous cell-free Massive MIMO refers to a distributed Massive
MIMO system implementing coherent user-centric transmission to overcome the
inter-cell interference limitation in cellular networks and provide additional
macro-diversity. These features, combined with the system scalability inherent
in the Massive MIMO design, distinguishes ubiquitous cell-free Massive MIMO
from prior coordinated distributed wireless systems. In this article, we
investigate the enormous potential of this promising technology while
addressing practical deployment issues to deal with the increased
back/front-hauling overhead deriving from the signal co-processing.Comment: Published in EURASIP Journal on Wireless Communications and
Networking on August 5, 201
Robust Joint Precoder and Equalizer Design in MIMO Communication Systems
We address joint design of robust precoder and equalizer in a MIMO
communication system using the minimization of weighted sum of mean square
errors. In addition to imperfect knowledge of channel state information, we
also account for inaccurate awareness of interference plus noise covariance
matrix and power shaping matrix. We follow the worst-case model for imperfect
knowledge of these matrices. First, we derive the worst-case values of these
matrices. Then, we transform the joint precoder and equalizer optimization
problem into a convex scalar optimization problem. Further, the solution to
this problem will be simplified to a depressed quartic equation, the
closed-form expressions for roots of which are known. Finally, we propose an
iterative algorithm to obtain the worst-case robust transceivers.Comment: 2 figures, 5 pages, conferenc
Cooperative Feedback for MIMO Interference Channels
Multi-antenna precoding effectively mitigates the interference in wireless
networks. However, the precoding efficiency can be significantly degraded by
the overhead due to the required feedback of channel state information (CSI).
This paper addresses such an issue by proposing a systematic method of
designing precoders for the two-user multiple-input-multiple-output (MIMO)
interference channels based on finite-rate CSI feedback from receivers to their
interferers, called cooperative feedback. Specifically, each precoder is
decomposed into inner and outer precoders for nulling interference and
improving the data link array gain, respectively. The inner precoders are
further designed to suppress residual interference resulting from finite-rate
cooperative feedback. To regulate residual interference due to precoder
quantization, additional scalar cooperative feedback signals are designed to
control transmitters' power using different criteria including applying
interference margins, maximizing sum throughput, and minimizing outage
probability. Simulation shows that such additional feedback effectively
alleviates performance degradation due to quantized precoder feedback.Comment: 5 pages; submitted to IEEE ICC 201
Improving Macrocell - Small Cell Coexistence through Adaptive Interference Draining
The deployment of underlay small base stations (SBSs) is expected to
significantly boost the spectrum efficiency and the coverage of next-generation
cellular networks. However, the coexistence of SBSs underlaid to an existing
macro-cellular network faces important challenges, notably in terms of spectrum
sharing and interference management. In this paper, we propose a novel
game-theoretic model that enables the SBSs to optimize their transmission rates
by making decisions on the resource occupation jointly in the frequency and
spatial domains. This procedure, known as interference draining, is performed
among cooperative SBSs and allows to drastically reduce the interference
experienced by both macro- and small cell users. At the macrocell side, we
consider a modified water-filling policy for the power allocation that allows
each macrocell user (MUE) to focus the transmissions on the degrees of freedom
over which the MUE experiences the best channel and interference conditions.
This approach not only represents an effective way to decrease the received
interference at the MUEs but also grants the SBSs tier additional transmission
opportunities and allows for a more agile interference management. Simulation
results show that the proposed approach yields significant gains at both
macrocell and small cell tiers, in terms of average achievable rate per user,
reaching up to 37%, relative to the non-cooperative case, for a network with
150 MUEs and 200 SBSs
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