544 research outputs found
Energy-Aware Competitive Power Allocation for Heterogeneous Networks Under QoS Constraints
This work proposes a distributed power allocation scheme for maximizing
energy efficiency in the uplink of orthogonal frequency-division multiple
access (OFDMA)-based heterogeneous networks (HetNets). The user equipment (UEs)
in the network are modeled as rational agents that engage in a non-cooperative
game where each UE allocates its available transmit power over the set of
assigned subcarriers so as to maximize its individual utility (defined as the
user's throughput per Watt of transmit power) subject to minimum-rate
constraints. In this framework, the relevant solution concept is that of Debreu
equilibrium, a generalization of Nash equilibrium which accounts for the case
where an agent's set of possible actions depends on the actions of its
opponents. Since the problem at hand might not be feasible, Debreu equilibria
do not always exist. However, using techniques from fractional programming, we
provide a characterization of equilibrial power allocation profiles when they
do exist. In particular, Debreu equilibria are found to be the fixed points of
a water-filling best response operator whose water level is a function of
minimum rate constraints and circuit power. Moreover, we also describe a set of
sufficient conditions for the existence and uniqueness of Debreu equilibria
exploiting the contraction properties of the best response operator. This
analysis provides the necessary tools to derive a power allocation scheme that
steers the network to equilibrium in an iterative and distributed manner
without the need for any centralized processing. Numerical simulations are then
used to validate the analysis and assess the performance of the proposed
algorithm as a function of the system parameters.Comment: 37 pages, 12 figures, to appear IEEE Trans. Wireless Commu
Optimal Linear Precoding Strategies for Wideband Non-Cooperative Systems based on Game Theory-Part II: Algorithms
In this two-part paper, we address the problem of finding the optimal
precoding/multiplexing scheme for a set of non-cooperative links sharing the
same physical resources, e.g., time and bandwidth. We consider two alternative
optimization problems: P.1) the maximization of mutual information on each
link, given constraints on the transmit power and spectral mask; and P.2) the
maximization of the transmission rate on each link, using finite order
constellations, under the same constraints as in P.1, plus a constraint on the
maximum average error probability on each link. Aiming at finding decentralized
strategies, we adopted as optimality criterion the achievement of a Nash
equilibrium and thus we formulated both problems P.1 and P.2 as strategic
noncooperative (matrix-valued) games. In Part I of this two-part paper, after
deriving the optimal structure of the linear transceivers for both games, we
provided a unified set of sufficient conditions that guarantee the uniqueness
of the Nash equilibrium. In this Part II, we focus on the achievement of the
equilibrium and propose alternative distributed iterative algorithms that solve
both games. Specifically, the new proposed algorithms are the following: 1) the
sequential and simultaneous iterative waterfilling based algorithms,
incorporating spectral mask constraints; 2) the sequential and simultaneous
gradient projection based algorithms, establishing an interesting link with
variational inequality problems. Our main contribution is to provide sufficient
conditions for the global convergence of all the proposed algorithms which,
although derived under stronger constraints, incorporating for example spectral
mask constraints, have a broader validity than the convergence conditions known
in the current literature for the sequential iterative waterfilling algorithm.Comment: Paper submitted to IEEE Transactions on Signal Processing, February
22, 2006. Revised March 26, 2007. Accepted June 5, 2007. To appear on IEEE
Transactions on Signal Processing, 200
Free Probability based Capacity Calculation of Multiantenna Gaussian Fading Channels with Cochannel Interference
During the last decade, it has been well understood that communication over
multiple antennas can increase linearly the multiplexing capacity gain and
provide large spectral efficiency improvements. However, the majority of
studies in this area were carried out ignoring cochannel interference. Only a
small number of investigations have considered cochannel interference, but even
therein simple channel models were employed, assuming identically distributed
fading coefficients. In this paper, a generic model for a multi-antenna channel
is presented incorporating four impairments, namely additive white Gaussian
noise, flat fading, path loss and cochannel interference. Both point-to-point
and multiple-access MIMO channels are considered, including the case of
cooperating Base Station clusters. The asymptotic capacity limit of this
channel is calculated based on an asymptotic free probability approach which
exploits the additive and multiplicative free convolution in the R- and
S-transform domain respectively, as well as properties of the eta and Stieltjes
transform. Numerical results are utilized to verify the accuracy of the derived
closed-form expressions and evaluate the effect of the cochannel interference.Comment: 16 pages, 4 figures, 1 tabl
A Variational Inference Framework for Soft-In-Soft-Out Detection in Multiple Access Channels
We propose a unified framework for deriving and studying soft-in-soft-out
(SISO) detection in interference channels using the concept of variational
inference. The proposed framework may be used in multiple-access interference
(MAI), inter-symbol interference (ISI), and multiple-input multiple-outpu
(MIMO) channels. Without loss of generality, we will focus our attention on
turbo multiuser detection, to facilitate a more concrete discussion. It is
shown that, with some loss of optimality, variational inference avoids the
exponential complexity of a posteriori probability (APP) detection by
optimizing a closely-related, but much more manageable, objective function
called variational free energy. In addition to its systematic appeal, there are
several other advantages to this viewpoint. First of all, it provides unified
and rigorous justifications for numerous detectors that were proposed on
radically different grounds, and facilitates convenient joint detection and
decoding (utilizing the turbo principle) when error-control codes are
incorporated. Secondly, efficient joint parameter estimation and data detection
is possible via the variational expectation maximization (EM) algorithm, such
that the detrimental effect of inaccurate channel knowledge at the receiver may
be dealt with systematically. We are also able to extend BPSK-based SISO
detection schemes to arbitrary square QAM constellations in a rigorous manner
using a variational argument.Comment: Submitted to Transactions on Information Theor
Composite CDMA - A statistical mechanics analysis
Code Division Multiple Access (CDMA) in which the spreading code assignment
to users contains a random element has recently become a cornerstone of CDMA
research. The random element in the construction is particular attractive as it
provides robustness and flexibility in utilising multi-access channels, whilst
not making significant sacrifices in terms of transmission power. Random codes
are generated from some ensemble, here we consider the possibility of combining
two standard paradigms, sparsely and densely spread codes, in a single
composite code ensemble. The composite code analysis includes a replica
symmetric calculation of performance in the large system limit, and
investigation of finite systems through a composite belief propagation
algorithm. A variety of codes are examined with a focus on the high
multi-access interference regime. In both the large size limit and finite
systems we demonstrate scenarios in which the composite code has typical
performance exceeding sparse and dense codes at equivalent signal to noise
ratio.Comment: 23 pages, 11 figures, Sigma Phi 2008 conference submission -
submitted to J.Stat.Mec
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