1,174 research outputs found
A Review of Interference Reduction in Wireless Networks Using Graph Coloring Methods
The interference imposes a significant negative impact on the performance of
wireless networks. With the continuous deployment of larger and more
sophisticated wireless networks, reducing interference in such networks is
quickly being focused upon as a problem in today's world. In this paper we
analyze the interference reduction problem from a graph theoretical viewpoint.
A graph coloring methods are exploited to model the interference reduction
problem. However, additional constraints to graph coloring scenarios that
account for various networking conditions result in additional complexity to
standard graph coloring. This paper reviews a variety of algorithmic solutions
for specific network topologies.Comment: 10 pages, 5 figure
D-ADMM: A Communication-Efficient Distributed Algorithm For Separable Optimization
We propose a distributed algorithm, named Distributed Alternating Direction
Method of Multipliers (D-ADMM), for solving separable optimization problems in
networks of interconnected nodes or agents. In a separable optimization problem
there is a private cost function and a private constraint set at each node. The
goal is to minimize the sum of all the cost functions, constraining the
solution to be in the intersection of all the constraint sets. D-ADMM is proven
to converge when the network is bipartite or when all the functions are
strongly convex, although in practice, convergence is observed even when these
conditions are not met. We use D-ADMM to solve the following problems from
signal processing and control: average consensus, compressed sensing, and
support vector machines. Our simulations show that D-ADMM requires less
communications than state-of-the-art algorithms to achieve a given accuracy
level. Algorithms with low communication requirements are important, for
example, in sensor networks, where sensors are typically battery-operated and
communicating is the most energy consuming operation.Comment: To appear in IEEE Transactions on Signal Processin
Distributed Basis Pursuit
We propose a distributed algorithm for solving the optimization problem Basis
Pursuit (BP). BP finds the least L1-norm solution of the underdetermined linear
system Ax = b and is used, for example, in compressed sensing for
reconstruction. Our algorithm solves BP on a distributed platform such as a
sensor network, and is designed to minimize the communication between nodes.
The algorithm only requires the network to be connected, has no notion of a
central processing node, and no node has access to the entire matrix A at any
time. We consider two scenarios in which either the columns or the rows of A
are distributed among the compute nodes. Our algorithm, named D-ADMM, is a
decentralized implementation of the alternating direction method of
multipliers. We show through numerical simulation that our algorithm requires
considerably less communications between the nodes than the state-of-the-art
algorithms.Comment: Preprint of the journal version of the paper; IEEE Transactions on
Signal Processing, Vol. 60, Issue 4, April, 201
Beyond Geometry : Towards Fully Realistic Wireless Models
Signal-strength models of wireless communications capture the gradual fading
of signals and the additivity of interference. As such, they are closer to
reality than other models. However, nearly all theoretic work in the SINR model
depends on the assumption of smooth geometric decay, one that is true in free
space but is far off in actual environments. The challenge is to model
realistic environments, including walls, obstacles, reflections and anisotropic
antennas, without making the models algorithmically impractical or analytically
intractable.
We present a simple solution that allows the modeling of arbitrary static
situations by moving from geometry to arbitrary decay spaces. The complexity of
a setting is captured by a metricity parameter Z that indicates how far the
decay space is from satisfying the triangular inequality. All results that hold
in the SINR model in general metrics carry over to decay spaces, with the
resulting time complexity and approximation depending on Z in the same way that
the original results depends on the path loss term alpha. For distributed
algorithms, that to date have appeared to necessarily depend on the planarity,
we indicate how they can be adapted to arbitrary decay spaces.
Finally, we explore the dependence on Z in the approximability of core
problems. In particular, we observe that the capacity maximization problem has
exponential upper and lower bounds in terms of Z in general decay spaces. In
Euclidean metrics and related growth-bounded decay spaces, the performance
depends on the exact metricity definition, with a polynomial upper bound in
terms of Z, but an exponential lower bound in terms of a variant parameter phi.
On the plane, the upper bound result actually yields the first approximation of
a capacity-type SINR problem that is subexponential in alpha
A Review and Evaluation of Queue Based Control Power Efficient Spectrum Allocation Method for LTE Networks
The cognitive radio based wireless regional area networks (WRAN) is nothing but IEEE-802.22 standard. IEEE 802.22 standard enables opportunistic access to in-use or free 900 MHz TV sub bands by secondary networks. There are many other standards presented; however there is no efficient methods for cognitive networks like LTE for channel access and bandwidth utilization. The existing methods for spectrum access in LTE networks, however most of methods are not flexible, power consuming. Also in literature, we studied that existing methods of spectrum allocation in LTE networks does not efficiently achieve the tradeoff between network QoS (Quality of Service) and power efficiency. The goal of this paper is to present the review on such different spectrum efficiency techniques for LTE networks and then evaluate the recent Queue Based Control (QBC) for power efficient spectrum allocation with its limitations and benefits. QBC approach helps in solving the research problem related to the energy efficiency as well as QoS efficiency to some extent. There are two variants of QBC method such as QBC1 and QBC2 with different objectives and configurations. We are evaluating both this approach on LTE network which is composed of Spectrum Manager (SM), evolved Nodes B (eNBs) and number of user’s. The experimental work is conducted using network simulator (NS2) for delay and energy consumption parameters
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