14,703 research outputs found
Survey of End-to-End Mobile Network Measurement Testbeds, Tools, and Services
Mobile (cellular) networks enable innovation, but can also stifle it and lead
to user frustration when network performance falls below expectations. As
mobile networks become the predominant method of Internet access, developer,
research, network operator, and regulatory communities have taken an increased
interest in measuring end-to-end mobile network performance to, among other
goals, minimize negative impact on application responsiveness. In this survey
we examine current approaches to end-to-end mobile network performance
measurement, diagnosis, and application prototyping. We compare available tools
and their shortcomings with respect to the needs of researchers, developers,
regulators, and the public. We intend for this survey to provide a
comprehensive view of currently active efforts and some auspicious directions
for future work in mobile network measurement and mobile application
performance evaluation.Comment: Submitted to IEEE Communications Surveys and Tutorials. arXiv does
not format the URL references correctly. For a correctly formatted version of
this paper go to
http://www.cs.montana.edu/mwittie/publications/Goel14Survey.pd
Saving Energy in Mobile Devices for On-Demand Multimedia Streaming -- A Cross-Layer Approach
This paper proposes a novel energy-efficient multimedia delivery system
called EStreamer. First, we study the relationship between buffer size at the
client, burst-shaped TCP-based multimedia traffic, and energy consumption of
wireless network interfaces in smartphones. Based on the study, we design and
implement EStreamer for constant bit rate and rate-adaptive streaming.
EStreamer can improve battery lifetime by 3x, 1.5x and 2x while streaming over
Wi-Fi, 3G and 4G respectively.Comment: Accepted in ACM Transactions on Multimedia Computing, Communications
and Applications (ACM TOMCCAP), November 201
Autonomous Mobility and Energy Service Management in Future Smart Cities: An Overview
With the rise of transportation electrification, autonomous driving and
shared mobility in urban mobility systems, and increasing penetrations of
distributed energy resources and autonomous demand-side management techniques
in energy systems, tremendous opportunities, as well as challenges, are
emerging in the forging of a sustainable and converged urban mobility and
energy future. This paper is motivated by these disruptive transformations and
gives an overview of managing autonomous mobility and energy services in future
smart cities. First, we propose a three-layer architecture for the convergence
of future mobility and energy systems. For each layer, we give a brief overview
of the disruptive transformations that directly contribute to the rise of
autonomous mobility-on-demand (AMoD) systems. Second, we propose the concept of
autonomous flexibility-on-demand (AFoD), as an energy service platform built
directly on existing infrastructures of AMoD systems. In the vision of AFoD,
autonomous electric vehicles provide charging flexibilities as a service on
demand in energy systems. Third, we analyze and compare AMoD and AFoD, and we
identify four key decisions that, if appropriately coordinated, will create a
synergy between AMoD and AFoD. Finally, we discuss key challenges towards the
success of AMoD and AFoD in future smart cities and present some key research
directions regarding the system-wide coordination between AMoD and AFoD.Comment: 19 pages, 4 figure
Towards Massive Machine Type Communications in Ultra-Dense Cellular IoT Networks: Current Issues and Machine Learning-Assisted Solutions
The ever-increasing number of resource-constrained Machine-Type Communication
(MTC) devices is leading to the critical challenge of fulfilling diverse
communication requirements in dynamic and ultra-dense wireless environments.
Among different application scenarios that the upcoming 5G and beyond cellular
networks are expected to support, such as eMBB, mMTC and URLLC, mMTC brings the
unique technical challenge of supporting a huge number of MTC devices, which is
the main focus of this paper. The related challenges include QoS provisioning,
handling highly dynamic and sporadic MTC traffic, huge signalling overhead and
Radio Access Network (RAN) congestion. In this regard, this paper aims to
identify and analyze the involved technical issues, to review recent advances,
to highlight potential solutions and to propose new research directions. First,
starting with an overview of mMTC features and QoS provisioning issues, we
present the key enablers for mMTC in cellular networks. Along with the
highlights on the inefficiency of the legacy Random Access (RA) procedure in
the mMTC scenario, we then present the key features and channel access
mechanisms in the emerging cellular IoT standards, namely, LTE-M and NB-IoT.
Subsequently, we present a framework for the performance analysis of
transmission scheduling with the QoS support along with the issues involved in
short data packet transmission. Next, we provide a detailed overview of the
existing and emerging solutions towards addressing RAN congestion problem, and
then identify potential advantages, challenges and use cases for the
applications of emerging Machine Learning (ML) techniques in ultra-dense
cellular networks. Out of several ML techniques, we focus on the application of
low-complexity Q-learning approach in the mMTC scenarios. Finally, we discuss
some open research challenges and promising future research directions.Comment: 37 pages, 8 figures, 7 tables, submitted for a possible future
publication in IEEE Communications Surveys and Tutorial
PAPR In LTE UPLINK : Problem and Improvement
LTE-Advanced is one of the most competing and widely adopted families of standards that will meet the 4G broadband wireless mobile communications requirements recommended by the IMT-Advanced for the terrestrial radio interface specifications. Pre-commercial deployments have proved that LTE-Advanced will ensure the competitiveness of the 4G mobile networks by providing a high-data-rate , low latency and optimized system.
Unlike the IEEE802.16m WiMAX which uses OFDMA in both downlink and uplink multiple access schemes, LTE and its advanced version systems continue to use different multiple access transmissions in which OFDMA and SC-FDMA are supported in the downlink and the uplink, respectively. The idea to use OFDMA in the LTE uplink communications invoked discord among the members of the 3GPP standardization body because of the growing concern over the signal peakiness which degrades the efficiency of mobile station power battery consumption. The dire consequence of the peak amplitudes generated by the superposition of several subcarriers of identical phases led 3GPP to adopt SC-FDMA as an uplink multiple access method.
Thus in this paper , the effect of pulse shaping on the performance of the uplink PAPR of distributed FDMA and localized FDMA will be dealt deeply. The performance improvement will be done by varying the roll-off factor of the raised-cosine filter for pulse shaping after IFFT.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format
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