8,539 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
Matching with Externalities for Context-Aware User-Cell Association in Small Cell Networks
In this paper, we propose a novel user-cell association approach for wireless
small cell networks that exploits previously unexplored context information
extracted from users' devices, i.e., user equipments (UEs). Beyond
characterizing precise quality of service (QoS) requirements that accurately
reflect the UEs' application usage, our proposed cell association approach
accounts for the devices' hardware type (e.g., smartphone, tablet, laptop).
This approach has the practical benefit of enabling the small cells to make
better informed cell association decisions that handle practical
device-specific QoS characteristics. We formulate the problem as a matching
game between small cell base stations (SBSs) and UEs. In this game, the SBSs
and UEs rank one another based on well-designed utility functions that capture
composite QoS requirements, extracted from the context features (i.e.,
application in use, hardware type). We show that the preferences used by the
nodes to rank one another are interdependent and influenced by the existing
network-wide matching. Due to this unique feature of the preferences, we show
that the proposed game can be classified as a many-to-one matching game with
externalities. To solve this game, we propose a distributed algorithm that
enables the players (i.e., UEs and SBSs) to self-organize into a stable
matching that guarantees the required applications' QoS. Simulation results
show that the proposed context-aware cell association scheme yields significant
gains, reaching up to 52% improvement compared to baseline context-unaware
approaches.Comment: 6 pages, 3 figures, conferenc
Matching Theory for Future Wireless Networks: Fundamentals and Applications
The emergence of novel wireless networking paradigms such as small cell and
cognitive radio networks has forever transformed the way in which wireless
systems are operated. In particular, the need for self-organizing solutions to
manage the scarce spectral resources has become a prevalent theme in many
emerging wireless systems. In this paper, the first comprehensive tutorial on
the use of matching theory, a Nobelprize winning framework, for resource
management in wireless networks is developed. To cater for the unique features
of emerging wireless networks, a novel, wireless-oriented classification of
matching theory is proposed. Then, the key solution concepts and algorithmic
implementations of this framework are exposed. Then, the developed concepts are
applied in three important wireless networking areas in order to demonstrate
the usefulness of this analytical tool. Results show how matching theory can
effectively improve the performance of resource allocation in all three
applications discussed
Matching theory for priority-based cell association in the downlink of wireless small cell networks
The deployment of small cells, overlaid on existing cellular infrastructure,
is seen as a key feature in next-generation cellular systems. In this paper,
the problem of user association in the downlink of small cell networks (SCNs)
is considered. The problem is formulated as a many-to-one matching game in
which the users and SCBSs rank one another based on utility functions that
account for both the achievable performance, in terms of rate and fairness to
cell edge users, as captured by newly proposed priorities. To solve this game,
a novel distributed algorithm that can reach a stable matching is proposed.
Simulation results show that the proposed approach yields an average utility
gain of up to 65% compared to a common association algorithm that is based on
received signal strength. Compared to the classical deferred acceptance
algorithm, the results also show a 40% utility gain and a more fair utility
distribution among the users.Comment: 5 page
- …