465 research outputs found
Wi-Fi Offload: Tragedy of the Commons or Land of Milk and Honey?
Fueled by its recent success in provisioning on-site wireless Internet
access, Wi-Fi is currently perceived as the best positioned technology for
pervasive mobile macro network offloading. However, the broad transitions of
multiple collocated operators towards this new paradigm may result in fierce
competition for the common unlicensed spectrum at hand. In this light, our
paper game-theoretically dissects market convergence scenarios by assessing the
competition between providers in terms of network performance, capacity
constraints, cost reductions, and revenue prospects. We will closely compare
the prospects and strategic positioning of fixed line operators offering Wi-Fi
services with respect to competing mobile network operators utilizing
unlicensed spectrum. Our results highlight important dependencies upon
inter-operator collaboration models, and more importantly, upon the ratio
between backhaul and Wi-Fi access bit-rates. Furthermore, our investigation of
medium- to long-term convergence scenarios indicates that a rethinking of
control measures targeting the large-scale monetization of unlicensed spectrum
may be required, as otherwise the used free bands may become subject to
tragedy-of-commons type of problems.Comment: Workshop on Spectrum Sharing Strategies for Wireless Broadband
Services, IEEE PIMRC'13, to appear 201
A Multi-Game Framework for Harmonized LTE-U and WiFi Coexistence over Unlicensed Bands
The introduction of LTE over unlicensed bands (LTE-U) will enable LTE base
stations (BSs) to boost their capacity and offload their traffic by exploiting
the underused unlicensed bands. However, to reap the benefits of LTE-U, it is
necessary to address various new challenges associated with LTE-U and WiFi
coexistence. In particular, new resource management techniques must be
developed to optimize the usage of the network resources while handling the
interdependence between WiFi and LTE users and ensuring that WiFi users are not
jeopardized. To this end, in this paper, a new game theoretic tool, dubbed as
\emph{multi-game} framework is proposed as a promising approach for modeling
resource allocation problems in LTE-U. In such a framework, multiple,
co-existing and coupled games across heterogeneous channels can be formulated
to capture the specific characteristics of LTE-U. Such games can be of
different properties and types but their outcomes are largely interdependent.
After introducing the basics of the multi-game framework, two classes of
algorithms are outlined to achieve the new solution concepts of multi-games.
Simulation results are then conducted to show how such a multi-game can
effectively capture the specific properties of LTE-U and make of it a
"friendly" neighbor to WiFi.Comment: Accepted for publication at IEEE Wireless Communications Magazine,
Special Issue on LTE in Unlicensed Spectru
When Cellular Meets WiFi in Wireless Small Cell Networks
The deployment of small cell base stations(SCBSs) overlaid on existing
macro-cellular systems is seen as a key solution for offloading traffic,
optimizing coverage, and boosting the capacity of future cellular wireless
systems. The next-generation of SCBSs is envisioned to be multi-mode, i.e.,
capable of transmitting simultaneously on both licensed and unlicensed bands.
This constitutes a cost-effective integration of both WiFi and cellular radio
access technologies (RATs) that can efficiently cope with peak wireless data
traffic and heterogeneous quality-of-service requirements. To leverage the
advantage of such multi-mode SCBSs, we discuss the novel proposed paradigm of
cross-system learning by means of which SCBSs self-organize and autonomously
steer their traffic flows across different RATs. Cross-system learning allows
the SCBSs to leverage the advantage of both the WiFi and cellular worlds. For
example, the SCBSs can offload delay-tolerant data traffic to WiFi, while
simultaneously learning the probability distribution function of their
transmission strategy over the licensed cellular band. This article will first
introduce the basic building blocks of cross-system learning and then provide
preliminary performance evaluation in a Long-Term Evolution (LTE) simulator
overlaid with WiFi hotspots. Remarkably, it is shown that the proposed
cross-system learning approach significantly outperforms a number of benchmark
traffic steering policies
The impact of bundling licensed and unlicensed wireless service
Unlicensed spectrum has been viewed as a way to increase competition in
wireless access and promote innovation in new technologies and business models.
However, several recent papers have shown that the openness of such spectrum
can also lead to it becoming over congested when used by competing wireless
service providers (SPs). This in turn can result in the SPs making no profit
and may deter them from entering the market. However, this prior work assumes
that unlicensed access is a separate service from any service offered using
licensed spectrum. Here, we instead consider the more common case were service
providers bundle both licensed and unlicensed spectrum as a single service and
offer this with a single price. We analyze a model for such a market and show
that in this case SPs are able to gain higher profit than the case without
bundling. It is also possible to get higher social welfare with bundling.
Moreover, we explore the case where SPs are allowed to manage the customers'
average percentage of time they receive service on unlicensed spectrum and
characterize the social welfare gap between the profit maximizing and social
welfare maximizing setting.Comment: 15 pages, 10 figures, accepted and to appear at IEEE International
Conference on Computer Communications (INFOCOM), 201
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