7,820 research outputs found
Applications of Soft Computing in Mobile and Wireless Communications
Soft computing is a synergistic combination of artificial intelligence methodologies to model and solve real world problems that are either impossible or too difficult to model mathematically. Furthermore, the use of conventional modeling techniques demands rigor, precision and certainty, which carry computational cost. On the other hand, soft computing utilizes computation, reasoning and inference to reduce computational cost by exploiting tolerance for imprecision, uncertainty, partial truth and approximation. In addition to computational cost savings, soft computing is an excellent platform for autonomic computing, owing to its roots in artificial intelligence. Wireless communication networks are associated with much uncertainty and imprecision due to a number of stochastic processes such as escalating number of access points, constantly changing propagation channels, sudden variations in network load and random mobility of users. This reality has fuelled numerous applications of soft computing techniques in mobile and wireless communications. This paper reviews various applications of the core soft computing methodologies in mobile and wireless communications
Networking - A Statistical Physics Perspective
Efficient networking has a substantial economic and societal impact in a
broad range of areas including transportation systems, wired and wireless
communications and a range of Internet applications. As transportation and
communication networks become increasingly more complex, the ever increasing
demand for congestion control, higher traffic capacity, quality of service,
robustness and reduced energy consumption require new tools and methods to meet
these conflicting requirements. The new methodology should serve for gaining
better understanding of the properties of networking systems at the macroscopic
level, as well as for the development of new principled optimization and
management algorithms at the microscopic level. Methods of statistical physics
seem best placed to provide new approaches as they have been developed
specifically to deal with non-linear large scale systems. This paper aims at
presenting an overview of tools and methods that have been developed within the
statistical physics community and that can be readily applied to address the
emerging problems in networking. These include diffusion processes, methods
from disordered systems and polymer physics, probabilistic inference, which
have direct relevance to network routing, file and frequency distribution, the
exploration of network structures and vulnerability, and various other
practical networking applications.Comment: (Review article) 71 pages, 14 figure
Modeling radio networks
We describe a modeling framework and collection of foundational
composition results for the study of probabilistic distributed
algorithms in synchronous radio networks. Though the radio setting has
been studied extensively by the distributed algorithms community, their
results rely on informal descriptions of the channel behavior and therefore
lack easy comparability and are prone to error caused by definition subtleties.
Our framework rectifies these issues by providing: (1) a method
to precisely describe a radio channel as a probabilistic automaton; (2) a
mathematical notion of implementing one channel using another channel,
allowing for direct comparisons of channel strengths and a natural
decomposition of problems into implementing a more powerful channel
and solving the problem on the powerful channel; (3) a mathematical
definition of a problem and solving a problem; (4) a pair of composition
results that simplify the tasks of proving properties about channel
implementation algorithms and combining problems with channel implementations.
Our goal is to produce a model streamlined for the needs of
the radio network algorithms community
V2X Meets NOMA: Non-Orthogonal Multiple Access for 5G Enabled Vehicular Networks
Benefited from the widely deployed infrastructure, the LTE network has
recently been considered as a promising candidate to support the
vehicle-to-everything (V2X) services. However, with a massive number of devices
accessing the V2X network in the future, the conventional OFDM-based LTE
network faces the congestion issues due to its low efficiency of orthogonal
access, resulting in significant access delay and posing a great challenge
especially to safety-critical applications. The non-orthogonal multiple access
(NOMA) technique has been well recognized as an effective solution for the
future 5G cellular networks to provide broadband communications and massive
connectivity. In this article, we investigate the applicability of NOMA in
supporting cellular V2X services to achieve low latency and high reliability.
Starting with a basic V2X unicast system, a novel NOMA-based scheme is proposed
to tackle the technical hurdles in designing high spectral efficient scheduling
and resource allocation schemes in the ultra dense topology. We then extend it
to a more general V2X broadcasting system. Other NOMA-based extended V2X
applications and some open issues are also discussed.Comment: Accepted by IEEE Wireless Communications Magazin
Sum Rate Maximized Resource Allocation in Multiple DF Relays Aided OFDM Transmission
In relay-aided wireless transmission systems, one of the key issues is how to
decide assisting relays and manage the energy resource at the source and each
individual relay, to maximize a certain objective related to system
performance. This paper addresses the sum rate maximized resource allocation
(RA) problem in a point to point orthogonal frequency division modulation
(OFDM) transmission system assisted by multiple decode-and-forward (DF) relays,
subject to the individual sum power constraints of the source and the relays.
In particular, the transmission at each subcarrier can be in either the direct
mode without any relay assisting, or the relay-aided mode with one or several
relays assisting. We propose two RA algorithms which optimize the assignment of
transmission mode and source power for every subcarrier, as well as the
assisting relays and the power allocation to them for every {relay-aided}
subcarrier. First, it is shown that the considered RA problem has zero
Lagrangian duality gap when there is a big number of subcarriers. In this case,
a duality based algorithm that finds a globally optimum RA is developed.
Second, a coordinate-ascent based iterative algorithm, which finds a suboptimum
RA but is always applicable regardless of the duality gap of the RA problem, is
developed. The effectiveness of these algorithms has been illustrated by
numerical experiments.Comment: 13 pages in two-column format, 10 figures, to appear in IEEE Journal
on Selected Areas in Communication
A Taxonomy for Congestion Control Algorithms in Vehicular Ad Hoc Networks
One of the main criteria in Vehicular Ad hoc Networks (VANETs) that has
attracted the researchers' consideration is congestion control. Accordingly,
many algorithms have been proposed to alleviate the congestion problem,
although it is hard to find an appropriate algorithm for applications and
safety messages among them. Safety messages encompass beacons and event-driven
messages. Delay and reliability are essential requirements for event-driven
messages. In crowded networks where beacon messages are broadcasted at a high
number of frequencies by many vehicles, the Control Channel (CCH), which used
for beacons sending, will be easily congested. On the other hand, to guarantee
the reliability and timely delivery of event-driven messages, having a
congestion free control channel is a necessity. Thus, consideration of this
study is given to find a solution for the congestion problem in VANETs by
taking a comprehensive look at the existent congestion control algorithms. In
addition, the taxonomy for congestion control algorithms in VANETs is presented
based on three classes, namely, proactive, reactive and hybrid. Finally, we
have found the criteria in which fulfill prerequisite of a good congestion
control algorithm
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