1,583 research outputs found
D2D-Based Grouped Random Access to Mitigate Mobile Access Congestion in 5G Sensor Networks
The Fifth Generation (5G) wireless service of sensor networks involves
significant challenges when dealing with the coordination of ever-increasing
number of devices accessing shared resources. This has drawn major interest
from the research community as many existing works focus on the radio access
network congestion control to efficiently manage resources in the context of
device-to-device (D2D) interaction in huge sensor networks. In this context,
this paper pioneers a study on the impact of D2D link reliability in
group-assisted random access protocols, by shedding the light on beneficial
performance and potential limitations of approaches of this kind against
tunable parameters such as group size, number of sensors and reliability of D2D
links. Additionally, we leverage on the association with a Geolocation Database
(GDB) capability to assist the grouping decisions by drawing parallels with
recent regulatory-driven initiatives around GDBs and arguing benefits of the
suggested proposal. Finally, the proposed method is approved to significantly
reduce the delay over random access channels, by means of an exhaustive
simulation campaign.Comment: First submission to IEEE Communications Magazine on Oct.28.2017.
Accepted on Aug.18.2019. This is the camera-ready versio
Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks
This article explores one of the key enablers of beyond G wireless
networks leveraging small cell network deployments, namely proactive caching.
Endowed with predictive capabilities and harnessing recent developments in
storage, context-awareness and social networks, peak traffic demands can be
substantially reduced by proactively serving predictable user demands, via
caching at base stations and users' devices. In order to show the effectiveness
of proactive caching, we examine two case studies which exploit the spatial and
social structure of the network, where proactive caching plays a crucial role.
Firstly, in order to alleviate backhaul congestion, we propose a mechanism
whereby files are proactively cached during off-peak demands based on file
popularity and correlations among users and files patterns. Secondly,
leveraging social networks and device-to-device (D2D) communications, we
propose a procedure that exploits the social structure of the network by
predicting the set of influential users to (proactively) cache strategic
contents and disseminate them to their social ties via D2D communications.
Exploiting this proactive caching paradigm, numerical results show that
important gains can be obtained for each case study, with backhaul savings and
a higher ratio of satisfied users of up to and , respectively.
Higher gains can be further obtained by increasing the storage capability at
the network edge.Comment: accepted for publication in IEEE Communications Magazin
Energy-Efficient NOMA Enabled Heterogeneous Cloud Radio Access Networks
Heterogeneous cloud radio access networks (H-CRANs) are envisioned to be
promising in the fifth generation (5G) wireless networks. H-CRANs enable users
to enjoy diverse services with high energy efficiency, high spectral
efficiency, and low-cost operation, which are achieved by using cloud computing
and virtualization techniques. However, H-CRANs face many technical challenges
due to massive user connectivity, increasingly severe spectrum scarcity and
energy-constrained devices. These challenges may significantly decrease the
quality of service of users if not properly tackled. Non-orthogonal multiple
access (NOMA) schemes exploit non-orthogonal resources to provide services for
multiple users and are receiving increasing attention for their potential of
improving spectral and energy efficiency in 5G networks. In this article a
framework for energy-efficient NOMA H-CRANs is presented. The enabling
technologies for NOMA H-CRANs are surveyed. Challenges to implement these
technologies and open issues are discussed. This article also presents the
performance evaluation on energy efficiency of H-CRANs with NOMA.Comment: This work has been accepted by IEEE Network. Pages 18, Figure
- …