4,474 research outputs found
Energy-Efficient Downlink Power Control in mmWave Cell-Free and User-Centric Massive MIMO
This paper considers cell-free and user-centric approaches for coverage
improvement in wireless cellular systems operating at millimeter wave
frequencies, and proposes downlink power control algorithms aimed at maximizing
the global energy efficiency. To tackle the non-convexity of the problems, an
interaction between sequential and alternating optimization is considered. The
use of hybrid analog/digital beamformers is also taken into account. The
numerical results show the benefits obtained from the power control algorithm,
as well as that the user-centric approach generally outperforms the cell-free
one.Comment: 4 pages; to be presented at the IEEE 5G Worls Forum Conference, Santa
Clara, July 2018. arXiv admin note: text overlap with arXiv:1710.0781
Secure Full-Duplex Device-to-Device Communication
This paper considers full-duplex (FD) device-to-device (D2D) communications
in a downlink MISO cellular system in the presence of multiple eavesdroppers.
The D2D pair communicate sharing the same frequency band allocated to the
cellular users (CUs). Since the D2D users share the same frequency as the CUs,
both the base station (BS) and D2D transmissions interfere each other. In
addition, due to limited processing capability, D2D users are susceptible to
external attacks. Our aim is to design optimal beamforming and power control
mechanism to guarantee secure communication while delivering the required
quality-of-service (QoS) for the D2D link. In order to improve security,
artificial noise (AN) is transmitted by the BS. We design robust beamforming
for secure message as well as the AN in the worst-case sense for minimizing
total transmit power with imperfect channel state information (CSI) of all
links available at the BS. The problem is strictly non-convex with infinitely
many constraints. By discovering the hidden convexity of the problem, we derive
a rank-one optimal solution for the power minimization problem.Comment: Accepted in IEEE GLOBECOM 2017, Singapore, 4-8 Dec. 201
Secure Full-Duplex Device-to-Device Communication
This paper considers full-duplex (FD) device-to-device (D2D) communications
in a downlink MISO cellular system in the presence of multiple eavesdroppers.
The D2D pair communicate sharing the same frequency band allocated to the
cellular users (CUs). Since the D2D users share the same frequency as the CUs,
both the base station (BS) and D2D transmissions interfere each other. In
addition, due to limited processing capability, D2D users are susceptible to
external attacks. Our aim is to design optimal beamforming and power control
mechanism to guarantee secure communication while delivering the required
quality-of-service (QoS) for the D2D link. In order to improve security,
artificial noise (AN) is transmitted by the BS. We design robust beamforming
for secure message as well as the AN in the worst-case sense for minimizing
total transmit power with imperfect channel state information (CSI) of all
links available at the BS. The problem is strictly non-convex with infinitely
many constraints. By discovering the hidden convexity of the problem, we derive
a rank-one optimal solution for the power minimization problem.Comment: Accepted in IEEE GLOBECOM 2017, Singapore, 4-8 Dec. 201
Characterization of Posidonia Oceanica Seagrass Aerenchyma through Whole Slide Imaging: A Pilot Study
Characterizing the tissue morphology and anatomy of seagrasses is essential
to predicting their acoustic behavior. In this pilot study, we use histology
techniques and whole slide imaging (WSI) to describe the composition and
topology of the aerenchyma of an entire leaf blade in an automatic way
combining the advantages of X-ray microtomography and optical microscopy.
Paraffin blocks are prepared in such a way that microtome slices contain an
arbitrarily large number of cross sections distributed along the full length of
a blade. The sample organization in the paraffin block coupled with whole slide
image analysis allows high throughput data extraction and an exhaustive
characterization along the whole blade length. The core of the work are image
processing algorithms that can identify cells and air lacunae (or void) from
fiber strand, epidermis, mesophyll and vascular system. A set of specific
features is developed to adequately describe the convexity of cells and voids
where standard descriptors fail. The features scrutinize the local curvature of
the object borders to allow an accurate discrimination between void and cell
through machine learning. The algorithm allows to reconstruct the cells and
cell membrane features that are relevant to tissue density, compressibility and
rigidity. Size distribution of the different cell types and gas spaces, total
biomass and total void volume fraction are then extracted from the high
resolution slices to provide a complete characterization of the tissue along
the leave from its base to the apex
Spectrum optimization in multi-user multi-carrier systems with iterative convex and nonconvex approximation methods
Several practical multi-user multi-carrier communication systems are
characterized by a multi-carrier interference channel system model where the
interference is treated as noise. For these systems, spectrum optimization is a
promising means to mitigate interference. This however corresponds to a
challenging nonconvex optimization problem. Existing iterative convex
approximation (ICA) methods consist in solving a series of improving convex
approximations and are typically implemented in a per-user iterative approach.
However they do not take this typical iterative implementation into account in
their design. This paper proposes a novel class of iterative approximation
methods that focuses explicitly on the per-user iterative implementation, which
allows to relax the problem significantly, dropping joint convexity and even
convexity requirements for the approximations. A systematic design framework is
proposed to construct instances of this novel class, where several new
iterative approximation methods are developed with improved per-user convex and
nonconvex approximations that are both tighter and simpler to solve (in
closed-form). As a result, these novel methods display a much faster
convergence speed and require a significantly lower computational cost.
Furthermore, a majority of the proposed methods can tackle the issue of getting
stuck in bad locally optimal solutions, and hence improve solution quality
compared to existing ICA methods.Comment: 33 pages, 7 figures. This work has been submitted for possible
publicatio
Error Rates of the Maximum-Likelihood Detector for Arbitrary Constellations: Convex/Concave Behavior and Applications
Motivated by a recent surge of interest in convex optimization techniques,
convexity/concavity properties of error rates of the maximum likelihood
detector operating in the AWGN channel are studied and extended to
frequency-flat slow-fading channels. Generic conditions are identified under
which the symbol error rate (SER) is convex/concave for arbitrary
multi-dimensional constellations. In particular, the SER is convex in SNR for
any one- and two-dimensional constellation, and also in higher dimensions at
high SNR. Pairwise error probability and bit error rate are shown to be convex
at high SNR, for arbitrary constellations and bit mapping. Universal bounds for
the SER 1st and 2nd derivatives are obtained, which hold for arbitrary
constellations and are tight for some of them. Applications of the results are
discussed, which include optimum power allocation in spatial multiplexing
systems, optimum power/time sharing to decrease or increase (jamming problem)
error rate, an implication for fading channels ("fading is never good in low
dimensions") and optimization of a unitary-precoded OFDM system. For example,
the error rate bounds of a unitary-precoded OFDM system with QPSK modulation,
which reveal the best and worst precoding, are extended to arbitrary
constellations, which may also include coding. The reported results also apply
to the interference channel under Gaussian approximation, to the bit error rate
when it can be expressed or approximated as a non-negative linear combination
of individual symbol error rates, and to coded systems.Comment: accepted by IEEE IT Transaction
Cross-Layer Optimization of Fast Video Delivery in Cache-Enabled Relaying Networks
This paper investigates the cross-layer optimization of fast video delivery
and caching for minimization of the overall video delivery time in a two-hop
relaying network. The half-duplex relay nodes are equipped with both a cache
and a buffer which facilitate joint scheduling of fetching and delivery to
exploit the channel diversity for improving the overall delivery performance.
The fast delivery control is formulated as a two-stage functional non-convex
optimization problem. By exploiting the underlying convex and quasi-convex
structures, the problem can be solved exactly and efficiently by the developed
algorithm. Simulation results show that significant caching and buffering gains
can be achieved with the proposed framework, which translates into a reduction
of the overall video delivery time. Besides, a trade-off between caching and
buffering gains is unveiled.Comment: 7 pages, 4 figures; accepted for presentation at IEEE Globecom, San
Diego, CA, Dec. 201
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