4,474 research outputs found
Analysis of Multi-Cell Downlink Cooperation with a Constrained Spatial Model
Multi-cell cooperation (MCC) mitigates intercell interference and improves
throughput at the cell edge. This paper considers a cooperative downlink,
whereby cell-edge mobiles are served by multiple cooperative base stations. The
cooperating base stations transmit identical signals over paths with
non-identical path losses, and the receiving mobile performs diversity
combining. The analysis in this paper is driven by a new expression for the
conditional outage probability when signals arriving over different paths are
combined in the presence of noise and interference, where the conditioning is
with respect to the network topology and shadowing. The channel model accounts
for path loss, shadowing, and Nakagami fading, and the Nakagami fading
parameters do not need to be identical for all paths. To study performance over
a wide class of network topologies, a random spatial model is adopted, and
performance is found by statistically characterizing the rates provided on the
downlinks. To model realistic networks, the model requires a minimum separation
among base stations. Having adopted a realistic model and an accurate analysis,
the paper proceeds to determine performance under several resource-allocation
policies and provides insight regarding how the cell edge should be defined.Comment: 6 pages, 3 figures, IEEE Global Telecommun. Conf. (GLOBECOM), 2013,
to appear. arXiv admin note: text overlap with arXiv:1210.366
Large-Scale Distributed Internet-based Discovery Mechanism for Dynamic Spectrum Allocation
Scarcity of frequencies and the demand for more bandwidth is likely to
increase the need for devices that utilize the available frequencies more
efficiently. Radios must be able to dynamically find other users of the
frequency bands and adapt so that they are not interfered, even if they use
different radio protocols. As transmitters far away may cause as much
interference as a transmitter located nearby, this mechanism can not be based
on location alone. Central databases can be used for this purpose, but require
expensive infrastructure and planning to scale. In this paper, we propose a
decentralized protocol and architecture for discovering radio devices over the
Internet. The protocol has low resource requirements, making it suitable for
implementation on limited platforms. We evaluate the protocol through
simulation in network topologies with up to 2.3 million nodes, including
topologies generated from population patterns in Norway. The protocol has also
been implemented as proof-of-concept in real Wi-Fi routers.Comment: Accepted for publication at IEEE DySPAN 201
Collocation Games and Their Application to Distributed Resource Management
We introduce Collocation Games as the basis of a general framework for modeling, analyzing, and facilitating the interactions between the various stakeholders in distributed systems in general, and in cloud computing environments in particular. Cloud computing enables fixed-capacity (processing, communication, and storage) resources to be offered by infrastructure providers as commodities for sale at a fixed cost in an open marketplace to independent, rational parties (players) interested in setting up their own applications over the Internet. Virtualization technologies enable the partitioning of such fixed-capacity resources so as to allow each player to dynamically acquire appropriate fractions of the resources for unencumbered use. In such a paradigm, the resource management problem reduces to that of partitioning the entire set of applications (players) into subsets, each of which is assigned to fixed-capacity cloud resources. If the infrastructure and the various applications are under a single administrative domain, this partitioning reduces to an optimization problem whose objective is to minimize the overall deployment cost. In a marketplace, in which the infrastructure provider is interested in maximizing its own profit, and in which each player is interested in minimizing its own cost, it should be evident that a global optimization is precisely the wrong framework. Rather, in this paper we use a game-theoretic framework in which the assignment of players to fixed-capacity resources is the outcome of a strategic "Collocation Game". Although we show that determining the existence of an equilibrium for collocation games in general is NP-hard, we present a number of simplified, practically-motivated variants of the collocation game for which we establish convergence to a Nash Equilibrium, and for which we derive convergence and price of anarchy bounds. In addition to these analytical results, we present an experimental evaluation of implementations of some of these variants for cloud infrastructures consisting of a collection of multidimensional resources of homogeneous or heterogeneous capacities. Experimental results using trace-driven simulations and synthetically generated datasets corroborate our analytical results and also illustrate how collocation games offer a feasible distributed resource management alternative for autonomic/self-organizing systems, in which the adoption of a global optimization approach (centralized or distributed) would be neither practical nor justifiable.NSF (CCF-0820138, CSR-0720604, EFRI-0735974, CNS-0524477, CNS-052016, CCR-0635102); Universidad Pontificia Bolivariana; COLCIENCIAS–Instituto Colombiano para el Desarrollo de la Ciencia y la Tecnología "Francisco José de Caldas
A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks
Cell Switch-Off (CSO) is recognized as a promising approach to reduce the
energy consumption in next-generation cellular networks. However, CSO poses
serious challenges not only from the resource allocation perspective but also
from the implementation point of view. Indeed, CSO represents a difficult
optimization problem due to its NP-complete nature. Moreover, there are a
number of important practical limitations in the implementation of CSO schemes,
such as the need for minimizing the real-time complexity and the number of
on-off/off-on transitions and CSO-induced handovers. This article introduces a
novel approach to CSO based on multiobjective optimization that makes use of
the statistical description of the service demand (known by operators). In
addition, downlink and uplink coverage criteria are included and a comparative
analysis between different models to characterize intercell interference is
also presented to shed light on their impact on CSO. The framework
distinguishes itself from other proposals in two ways: 1) The number of
on-off/off-on transitions as well as handovers are minimized, and 2) the
computationally-heavy part of the algorithm is executed offline, which makes
its implementation feasible. The results show that the proposed scheme achieves
substantial energy savings in small cell deployments where service demand is
not uniformly distributed, without compromising the Quality-of-Service (QoS) or
requiring heavy real-time processing
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