257 research outputs found
Sum-Rate Maximization for Linearly Precoded Downlink Multiuser MISO Systems with Partial CSIT: A Rate-Splitting Approach
This paper considers the Sum-Rate (SR) maximization problem in downlink
MU-MISO systems under imperfect Channel State Information at the Transmitter
(CSIT). Contrary to existing works, we consider a rather unorthodox
transmission scheme. In particular, the message intended to one of the users is
split into two parts: a common part which can be recovered by all users, and a
private part recovered by the corresponding user. On the other hand, the rest
of users receive their information through private messages. This
Rate-Splitting (RS) approach was shown to boost the achievable Degrees of
Freedom (DoF) when CSIT errors decay with increased SNR. In this work, the RS
strategy is married with linear precoder design and optimization techniques to
achieve a maximized Ergodic SR (ESR) performance over the entire range of SNRs.
Precoders are designed based on partial CSIT knowledge by solving a stochastic
rate optimization problem using means of Sample Average Approximation (SAA)
coupled with the Weighted Minimum Mean Square Error (WMMSE) approach. Numerical
results show that in addition to the ESR gains, the benefits of RS also include
relaxed CSIT quality requirements and enhanced achievable rate regions compared
to conventional transmission with NoRS.Comment: accepted to IEEE Transactions on Communication
Joint Scheduling and ARQ for MU-MIMO Downlink in the Presence of Inter-Cell Interference
User scheduling and multiuser multi-antenna (MU-MIMO) transmission are at the
core of high rate data-oriented downlink schemes of the next-generation of
cellular systems (e.g., LTE-Advanced). Scheduling selects groups of users
according to their channels vector directions and SINR levels. However, when
scheduling is applied independently in each cell, the inter-cell interference
(ICI) power at each user receiver is not known in advance since it changes at
each new scheduling slot depending on the scheduling decisions of all
interfering base stations. In order to cope with this uncertainty, we consider
the joint operation of scheduling, MU-MIMO beamforming and Automatic Repeat
reQuest (ARQ). We develop a game-theoretic framework for this problem and build
on stochastic optimization techniques in order to find optimal scheduling and
ARQ schemes. Particularizing our framework to the case of "outage service
rates", we obtain a scheme based on adaptive variable-rate coding at the
physical layer, combined with ARQ at the Logical Link Control (ARQ-LLC). Then,
we present a novel scheme based on incremental redundancy Hybrid ARQ (HARQ)
that is able to achieve a throughput performance arbitrarily close to the
"genie-aided service rates", with no need for a genie that provides
non-causally the ICI power levels. The novel HARQ scheme is both easier to
implement and superior in performance with respect to the conventional
combination of adaptive variable-rate coding and ARQ-LLC.Comment: Submitted to IEEE Transactions on Communications, v2: small
correction
Multiple Access in Aerial Networks: From Orthogonal and Non-Orthogonal to Rate-Splitting
Recently, interest on the utilization of unmanned aerial vehicles (UAVs) has
aroused. Specifically, UAVs can be used in cellular networks as aerial users
for delivery, surveillance, rescue search, or as an aerial base station (aBS)
for communication with ground users in remote uncovered areas or in dense
environments requiring prompt high capacity. Aiming to satisfy the high
requirements of wireless aerial networks, several multiple access techniques
have been investigated. In particular, space-division multiple access(SDMA) and
power-domain non-orthogonal multiple access (NOMA) present promising
multiplexing gains for aerial downlink and uplink. Nevertheless, these gains
are limited as they depend on the conditions of the environment. Hence, a
generalized scheme has been recently proposed, called rate-splitting multiple
access (RSMA), which is capable of achieving better spectral efficiency gains
compared to SDMA and NOMA. In this paper, we present a comprehensive survey of
key multiple access technologies adopted for aerial networks, where aBSs are
deployed to serve ground users. Since there have been only sporadic results
reported on the use of RSMA in aerial systems, we aim to extend the discussion
on this topic by modelling and analyzing the weighted sum-rate performance of a
two-user downlink network served by an RSMA-based aBS. Finally, related open
issues and future research directions are exposed.Comment: 16 pages, 6 figures, submitted to IEEE Journa
AMMSE Optimization for Multiuser MISO Systems with Imperfect CSIT and Perfect CSIR
In this paper, we consider the design of robust linear precoders for MU-MISO
systems where users have perfect Channel State Information (CSI) while the BS
has partial CSI. In particular, the BS has access to imperfect estimates of the
channel vectors, in addition to the covariance matrices of the estimation error
vectors. A closed-form expression for the Average Minimum Mean Square Error
(AMMSE) is obtained using the second order Taylor Expansion. This approximation
is used to formulate two fairness-based robust design problems: a maximum
AMMSE-constrained problem and a power-constrained problem. We propose an
algorithm based on convex optimization techniques to address the first problem,
while the second problem is tackled by exploiting the close relationship
between the two problems, in addition to their monotonic natures.Comment: IEEE Global Communications Conference (GLOBECOM) 201
Outage Efficient Strategies for Network MIMO with Partial CSIT
We consider a multi-cell MIMO downlink (network MIMO) where base-stations
(BS) with antennas connected to a central station (CS) serve
single-antenna user terminals (UT). Although many works have shown the
potential benefits of network MIMO, the conclusion critically depends on the
underlying assumptions such as channel state information at transmitters (CSIT)
and backhaul links. In this paper, by focusing on the impact of partial CSIT,
we propose an outage-efficient strategy. Namely, with side information of all
UT's messages and local CSIT, each BS applies zero-forcing (ZF) beamforming in
a distributed manner. For a small number of UTs (), the ZF beamforming
creates parallel MISO channels. Based on the statistical knowledge of these
parallel channels, the CS performs a robust power allocation that
simultaneously minimizes the outage probability of all UTs and achieves a
diversity gain of per UT. With a large number of UTs (),
we propose a so-called distributed diversity scheduling (DDS) scheme to select
a subset of \Ks UTs with limited backhaul communication. It is proved that
DDS achieves a diversity gain of B\frac{K}{\Ks}(M-\Ks+1), which scales
optimally with the number of cooperative BSs as well as UTs. Numerical
results confirm that even under realistic assumptions such as partial CSIT and
limited backhaul communications, network MIMO can offer high data rates with a
sufficient reliability to individual UTs.Comment: 26 pages, 8 figures, submitted to IEEE Trans. on Signal Processin
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