6,810 research outputs found
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
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
On the Real-Time Hardware Implementation Feasibility of Joint Radio Resource Management Policies for Heterogeneous Wireless Networks
The study and design of Joint Radio Resource Management (JRRM) techniques is a key and challenging aspect in
future heterogeneous wireless systems where different Radio Access Technologies will physically coexist. In these systems, the
total available radio resources need to be used in a coordinated way to guarantee adequate satisfaction levels to all users, and
maximize the system revenues. In addition to carry out an efficient use of the available radio resources, JRRM algorithms need
to exhibit good computational performance to guarantee their future implementation viability. In this context, this paper proposes
novel JRRM techniques based on linear programming techniques, and investigates their computational cost when implemented
in DSP platforms commonly used in mobile base stations. The obtained results demonstrate the feasibility to implement the
proposed JRRM algorithms in future heterogeneous wireless systems
Integer Linear Programming Optimization of Joint RRM Policies for Heterogeneous Wireless Systems
Wireless systems will be characterized by the coexistence of heterogeneous Radio
Access Technologies (RATs) with different, but also complementary, performance and technical
characteristics. These heterogeneous wireless networks will provide network operators the
possibility to efficiently and coordinately use the heterogeneous radio resources, for which novel
Joint Radio Resource Management (JRRM) policies need to be designed. In this context, this work
proposes and evaluates a JRRM policy that simultaneously determines for each user an adequate
combination of RAT and number of radio resources within such RAT to guarantee the user/service
QoS requirements, and efficiently distribute the radio resources considering a user fairness
approach aimed at maximizing the system capacity. To this aim, the JRRM algorithm, which takes
into account the discrete nature of radio resources, is based on integer linear programming
optimization mechanisms
Common Radio Resource Management Policy for Multimedia Traffic in Beyond 3G Heterogeneous Wireless Systems
Beyond 3G wireless systems will be composed of a
variety of Radio Access Technologies (RATs) with different, but
also complementary, performance and technical characteristics.
To exploit such diversity while guaranteeing the interoperability
and efficient management of the different RATs, common radio
resource management (CRRM) techniques need to be defined.
This work proposes and evaluates a CRRM policy that
simultaneously assigns to each user an adequate combination of
RAT and number of radio resources within such RAT to
guarantee its QoS requirements. The proposed CRRM technique
is based on linear objective functions and programming tools
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