579 research outputs found
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
An Economic User-Centric WiFi Offloading Algorithm for Heterogeneous Network
An economic user-centric WiFi offloading algorithm is proposed to satisfy the major concerns of
wireless users, who wish to have better network performance with even less network expense. Thus in this paper
both system throughput and network expense are considered, and the goal of the proposed offloading algorithm is
to obtain an optimal offloading ratio, which can both maximize the system throughput and minimize the network
expense. Firstly, a practical system model is set up on the basis of a typical scenario of heterogeneous network. In this
model, the average throughput of both cellular network and WiFi network is analyzed carefully. Then an economic
user-centric WiFi offloading algorithm is proposed with an evaluation function to evaluate the system, and the optimal
offloading ratio can be obtained by minimizing the evaluation function. At last, numerical results represent a direct
calculating process of the optimal offloading ratio. These results in return validate the efficiency of the proposed
offloading algorithm as well
Will 5G See its Blind Side? Evolving 5G for Universal Internet Access
Internet has shown itself to be a catalyst for economic growth and social
equity but its potency is thwarted by the fact that the Internet is off limits
for the vast majority of human beings. Mobile phones---the fastest growing
technology in the world that now reaches around 80\% of humanity---can enable
universal Internet access if it can resolve coverage problems that have
historically plagued previous cellular architectures (2G, 3G, and 4G). These
conventional architectures have not been able to sustain universal service
provisioning since these architectures depend on having enough users per cell
for their economic viability and thus are not well suited to rural areas (which
are by definition sparsely populated). The new generation of mobile cellular
technology (5G), currently in a formative phase and expected to be finalized
around 2020, is aimed at orders of magnitude performance enhancement. 5G offers
a clean slate to network designers and can be molded into an architecture also
amenable to universal Internet provisioning. Keeping in mind the great social
benefits of democratizing Internet and connectivity, we believe that the time
is ripe for emphasizing universal Internet provisioning as an important goal on
the 5G research agenda. In this paper, we investigate the opportunities and
challenges in utilizing 5G for global access to the Internet for all (GAIA). We
have also identified the major technical issues involved in a 5G-based GAIA
solution and have set up a future research agenda by defining open research
problems
Next Generation M2M Cellular Networks: Challenges and Practical Considerations
In this article, we present the major challenges of future machine-to-machine
(M2M) cellular networks such as spectrum scarcity problem, support for
low-power, low-cost, and numerous number of devices. As being an integral part
of the future Internet-of-Things (IoT), the true vision of M2M communications
cannot be reached with conventional solutions that are typically cost
inefficient. Cognitive radio concept has emerged to significantly tackle the
spectrum under-utilization or scarcity problem. Heterogeneous network model is
another alternative to relax the number of covered users. To this extent, we
present a complete fundamental understanding and engineering knowledge of
cognitive radios, heterogeneous network model, and power and cost challenges in
the context of future M2M cellular networks
Five Facets of 6G: Research Challenges and Opportunities
Whilst the fifth-generation (5G) systems are being rolled out across the
globe, researchers have turned their attention to the exploration of radical
next-generation solutions. At this early evolutionary stage we survey five main
research facets of this field, namely {\em Facet~1: next-generation
architectures, spectrum and services, Facet~2: next-generation networking,
Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing,
as well as Facet~5: applications of deep learning in 6G networks.} In this
paper, we have provided a critical appraisal of the literature of promising
techniques ranging from the associated architectures, networking, applications
as well as designs. We have portrayed a plethora of heterogeneous architectures
relying on cooperative hybrid networks supported by diverse access and
transmission mechanisms. The vulnerabilities of these techniques are also
addressed and carefully considered for highlighting the most of promising
future research directions. Additionally, we have listed a rich suite of
learning-driven optimization techniques. We conclude by observing the
evolutionary paradigm-shift that has taken place from pure single-component
bandwidth-efficiency, power-efficiency or delay-optimization towards
multi-component designs, as exemplified by the twin-component ultra-reliable
low-latency mode of the 5G system. We advocate a further evolutionary step
towards multi-component Pareto optimization, which requires the exploration of
the entire Pareto front of all optiomal solutions, where none of the components
of the objective function may be improved without degrading at least one of the
other components
- …