7,812 research outputs found
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks
Future wireless networks have a substantial potential in terms of supporting
a broad range of complex compelling applications both in military and civilian
fields, where the users are able to enjoy high-rate, low-latency, low-cost and
reliable information services. Achieving this ambitious goal requires new radio
techniques for adaptive learning and intelligent decision making because of the
complex heterogeneous nature of the network structures and wireless services.
Machine learning (ML) algorithms have great success in supporting big data
analytics, efficient parameter estimation and interactive decision making.
Hence, in this article, we review the thirty-year history of ML by elaborating
on supervised learning, unsupervised learning, reinforcement learning and deep
learning. Furthermore, we investigate their employment in the compelling
applications of wireless networks, including heterogeneous networks (HetNets),
cognitive radios (CR), Internet of things (IoT), machine to machine networks
(M2M), and so on. This article aims for assisting the readers in clarifying the
motivation and methodology of the various ML algorithms, so as to invoke them
for hitherto unexplored services as well as scenarios of future wireless
networks.Comment: 46 pages, 22 fig
Infrastructure-Assisted Message Dissemination for Supporting Heterogeneous Driving Patterns
With the advances of Internet of Things technologies, individual vehicles can now exchange information to improve traffic safety, and some vehicles can further improve safety and efficiency by coordinating their mobility via cooperative driving. To facilitate these applications, many studies have been focused on the design of inter-vehicle message dissemination protocols. However, most existing designs either assume individual driving pattern or consider cooperative driving only. Moreover, few of them fully exploit infrastructures, such as cameras, sensors, and road-side units. In this paper, we address the design of message dissemination that supports heterogeneous driving patterns. Specifically, we first propose an infrastructure-assisted message dissemination framework that can utilize the capability of infrastructures. We then present a novel beacon scheduling algorithm that aims at guaranteeing the timely and reliable delivery of both periodic beacon messages for cooperative driving and event-triggered safety messages for individual driving. To evaluate the performance of the protocol, we develop both theoretical analysis and simulation experiments. Extensive numerical results confirm the effectiveness of the proposed protocol
Recommended from our members
Dynamic wireless mobile framework for distributed collaborative real-time information generation and control systems
Intelligent Transportation Systems (ITS) have only recently discovered the exciting possibilities in the nomadic and ubiquitous computing space to build a new generation of information systems by allowing the vehicle to act both as a carrier and consumer of wireless (and thus omnipresent) information. Wide deployment of such ITS systems may eventually allow for more dynamic and efficient transportation systems, which can contribute in several ways towards greater economic growth whilst respecting environmental sustainability. A great number of researchers have dedicated considerable time and resources to tackling traffic related issues by utilising the new wireless capabilities enabled by ITS; such initiatives cover a wide range of applications such as safety, knowledge sharing and infotainment. Indicative of the extent of such efforts is the plethora of research projects initiated by many national and multi-national organisations such as the EU Framework Programme for Research and Technological Development. To achieve their goals, proposed solutions from such organisations depend on the development and deployment of intelligent wireless mobile communication systems, where data dissemination issues make the prospect of efficient and effective communication a challenging proposition. Presently, Car-to-Car and Car-to-Infrastructure communications are two distinct avenues that make possible efficient and reliable delivery of messages via direct radio links in traffic areas. In all cases, high quality of communication performance is desirable for a communication system composed mostly of roaming participants; such a system needs to be dynamic, flexible and infrastructure-less. Consequently, Mobile Ad hoc Network (MANET)-based networks are a natural fit to ITS
- …