17,636 research outputs found
Cell Selection in Wireless Two-Tier Networks: A Context-Aware Matching Game
The deployment of small cell networks is seen as a major feature of the next
generation of wireless networks. In this paper, a novel approach for cell
association in small cell networks is proposed. The proposed approach exploits
new types of information extracted from the users' devices and environment to
improve the way in which users are assigned to their serving base stations.
Examples of such context information include the devices' screen size and the
users' trajectory. The problem is formulated as a matching game with
externalities and a new, distributed algorithm is proposed to solve this game.
The proposed algorithm is shown to reach a stable matching whose properties are
studied. Simulation results show that the proposed context-aware matching
approach yields significant performance gains, in terms of the average utility
per user, when compared with a classical max-SINR approach.Comment: 11 pages, 11 figures, Journal article in ICST Wireless Spectrum, 201
Joint Resource Allocation for eICIC in Heterogeneous Networks
Interference coordination between high-power macros and low-power picos
deeply impacts the performance of heterogeneous networks (HetNets). It should
deal with three challenges: user association with macros and picos, the amount
of almost blank subframe (ABS) that macros should reserve for picos, and
resource block (RB) allocation strategy in each eNB. We formulate the three
issues jointly for sum weighted logarithmic utility maximization while
maintaining proportional fairness of users. A class of distributed algorithms
are developed to solve the joint optimization problem. Our framework can be
deployed for enhanced inter-cell interference coordination (eICIC) in existing
LTE-A protocols. Extensive evaluation are performed to verify the effectiveness
of our algorithms.Comment: Accepted by Globecom 201
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