2,038 research outputs found
An information-theoretic look at MIMO energy-efficient communications
International audienceOne of the main objectives of this paper is to provide an information-theoretic answer on how to maximize energy- effciency in MIMO (multiple input multiple output) systems. In static and fast fading channels, for which arbitrarily reliable communications are possible, it is shown that the best precoding scheme (which includes power allocation) is to transmit at very low power (Q ->0). Whereas energy-effciency is maximized in this regime, the latter also corresponds to communicating at very small transmission rates (R ->0). In slow fading or quasi-static MIMO systems (where reliability cannot be ensured), based on the proposed information-theoretic performance measure, it is proven that energy-effciency is maximized for a non-trivial precoding scheme; in particular, transmitting at zero power or saturating the transmit power constraint is suboptimal. The determination of the best precoding scheme is shown to be a new open problem. Based on this statement, the best precoding scheme is determined in several special but useful cases. As a second step, we show how to use the proposed energy-effciency measure to analyze the important case of distributed power allocation in MIMO multiple access channels. Simulations show the benefits brought by multiple antennas for saving energy while guaranteeing the system to reach a given transmission rate target
Cyclic division algebras: a tool for space-time coding
Multiple antennas at both the transmitter and receiver ends of a wireless digital transmission channel may increase both data rate and reliability. Reliable high rate transmission over such channels can only be achieved through Space–Time coding. Rank and determinant code design criteria have been proposed to enhance diversity and coding gain. The special case of full-diversity criterion requires that the difference of any two distinct codewords has full rank.
Extensive work has been done on Space–Time coding, aiming at
finding fully diverse codes with high rate. Division algebras have been proposed as a new tool for constructing Space–Time codes, since they are non-commutative algebras that naturally yield linear fully diverse codes. Their algebraic properties can thus be further exploited to
improve the design of good codes.
The aim of this work is to provide a tutorial introduction to the algebraic tools involved in the design of codes based on cyclic division algebras. The different design criteria involved will be illustrated, including the constellation shaping, the information lossless property, the non-vanishing determinant property, and the diversity multiplexing trade-off. The final target is to give the complete mathematical background underlying the construction of the Golden code and the other Perfect Space–Time block codes
Distributed stochastic optimization via matrix exponential learning
In this paper, we investigate a distributed learning scheme for a broad class
of stochastic optimization problems and games that arise in signal processing
and wireless communications. The proposed algorithm relies on the method of
matrix exponential learning (MXL) and only requires locally computable gradient
observations that are possibly imperfect and/or obsolete. To analyze it, we
introduce the notion of a stable Nash equilibrium and we show that the
algorithm is globally convergent to such equilibria - or locally convergent
when an equilibrium is only locally stable. We also derive an explicit linear
bound for the algorithm's convergence speed, which remains valid under
measurement errors and uncertainty of arbitrarily high variance. To validate
our theoretical analysis, we test the algorithm in realistic
multi-carrier/multiple-antenna wireless scenarios where several users seek to
maximize their energy efficiency. Our results show that learning allows users
to attain a net increase between 100% and 500% in energy efficiency, even under
very high uncertainty.Comment: 31 pages, 3 figure
Energy Efficiency in MIMO Underlay and Overlay Device-to-Device Communications and Cognitive Radio Systems
This paper addresses the problem of resource allocation for systems in which
a primary and a secondary link share the available spectrum by an underlay or
overlay approach. After observing that such a scenario models both cognitive
radio and D2D communications, we formulate the problem as the maximization of
the secondary energy efficiency subject to a minimum rate requirement for the
primary user. This leads to challenging non-convex, fractional problems. In the
underlay scenario, we obtain the global solution by means of a suitable
reformulation. In the overlay scenario, two algorithms are proposed. The first
one yields a resource allocation fulfilling the first-order optimality
conditions of the resource allocation problem, by solving a sequence of easier
fractional problems. The second one enjoys a weaker optimality claim, but an
even lower computational complexity. Numerical results demonstrate the merits
of the proposed algorithms both in terms of energy-efficient performance and
complexity, also showing that the two proposed algorithms for the overlay
scenario perform very similarly, despite the different complexity.Comment: to appear in IEEE Transactions on Signal Processin
Energy Harvesting Wireless Communications: A Review of Recent Advances
This article summarizes recent contributions in the broad area of energy
harvesting wireless communications. In particular, we provide the current state
of the art for wireless networks composed of energy harvesting nodes, starting
from the information-theoretic performance limits to transmission scheduling
policies and resource allocation, medium access and networking issues. The
emerging related area of energy transfer for self-sustaining energy harvesting
wireless networks is considered in detail covering both energy cooperation
aspects and simultaneous energy and information transfer. Various potential
models with energy harvesting nodes at different network scales are reviewed as
well as models for energy consumption at the nodes.Comment: To appear in the IEEE Journal of Selected Areas in Communications
(Special Issue: Wireless Communications Powered by Energy Harvesting and
Wireless Energy Transfer
Massive MIMO for Next Generation Wireless Systems
Multi-user Multiple-Input Multiple-Output (MIMO) offers big advantages over
conventional point-to-point MIMO: it works with cheap single-antenna terminals,
a rich scattering environment is not required, and resource allocation is
simplified because every active terminal utilizes all of the time-frequency
bins. However, multi-user MIMO, as originally envisioned with roughly equal
numbers of service-antennas and terminals and frequency division duplex
operation, is not a scalable technology. Massive MIMO (also known as
"Large-Scale Antenna Systems", "Very Large MIMO", "Hyper MIMO", "Full-Dimension
MIMO" & "ARGOS") makes a clean break with current practice through the use of a
large excess of service-antennas over active terminals and time division duplex
operation. Extra antennas help by focusing energy into ever-smaller regions of
space to bring huge improvements in throughput and radiated energy efficiency.
Other benefits of massive MIMO include the extensive use of inexpensive
low-power components, reduced latency, simplification of the media access
control (MAC) layer, and robustness to intentional jamming. The anticipated
throughput depend on the propagation environment providing asymptotically
orthogonal channels to the terminals, but so far experiments have not disclosed
any limitations in this regard. While massive MIMO renders many traditional
research problems irrelevant, it uncovers entirely new problems that urgently
need attention: the challenge of making many low-cost low-precision components
that work effectively together, acquisition and synchronization for
newly-joined terminals, the exploitation of extra degrees of freedom provided
by the excess of service-antennas, reducing internal power consumption to
achieve total energy efficiency reductions, and finding new deployment
scenarios. This paper presents an overview of the massive MIMO concept and
contemporary research.Comment: Final manuscript, to appear in IEEE Communications Magazin
Green inter-cluster interference management in uplink of multi-cell processing systems
This paper examines the uplink of cellular systems employing base station cooperation for joint signal processing. We consider clustered cooperation and investigate effective techniques for managing inter-cluster interference to improve users' performance in terms of both spectral and energy efficiency. We use information theoretic analysis to establish general closed form expressions for the system achievable sum rate and the users' Bit-per-Joule capacity while adopting a realistic user device power consumption model. Two main inter-cluster interference management approaches are identified and studied, i.e., through: 1) spectrum re-use; and 2) users' power control. For the former case, we show that isolating clusters by orthogonal resource allocation is the best strategy. For the latter case, we introduce a mathematically tractable user power control scheme and observe that a green opportunistic transmission strategy can significantly reduce the adverse effects of inter-cluster interference while exploiting the benefits from cooperation. To compare the different approaches in the context of real-world systems and evaluate the effect of key design parameters on the users' energy-spectral efficiency relationship, we fit the analytical expressions into a practical macrocell scenario. Our results demonstrate that significant improvement in terms of both energy and spectral efficiency can be achieved by energy-aware interference management
Full-Duplex Cloud Radio Access Network: Stochastic Design and Analysis
Full-duplex (FD) has emerged as a disruptive communications paradigm for
enhancing the achievable spectral efficiency (SE), thanks to the recent major
breakthroughs in self-interference (SI) mitigation. The FD versus half-duplex
(HD) SE gain, in cellular networks, is however largely limited by the
mutual-interference (MI) between the downlink (DL) and the uplink (UL). A
potential remedy for tackling the MI bottleneck is through cooperative
communications. This paper provides a stochastic design and analysis of FD
enabled cloud radio access network (C-RAN) under the Poisson point process
(PPP)-based abstraction model of multi-antenna radio units (RUs) and user
equipments (UEs). We consider different disjoint and user-centric approaches
towards the formation of finite clusters in the C-RAN. Contrary to most
existing studies, we explicitly take into consideration non-isotropic fading
channel conditions and finite-capacity fronthaul links. Accordingly,
upper-bound expressions for the C-RAN DL and UL SEs, involving the statistics
of all intended and interfering signals, are derived. The performance of the FD
C-RAN is investigated through the proposed theoretical framework and
Monte-Carlo (MC) simulations. The results indicate that significant FD versus
HD C-RAN SE gains can be achieved, particularly in the presence of
sufficient-capacity fronthaul links and advanced interference cancellation
capabilities
- …