1,429 research outputs found
Device-Centric Cooperation in Mobile Networks
The increasing popularity of applications such as video streaming in today's
mobile devices introduces higher demand for throughput, and puts a strain
especially on cellular links. Cooperation among mobile devices by exploiting
both cellular and local area connections is a promising approach to meet the
increasing demand. In this paper, we consider that a group of cooperative
mobile devices, exploiting both cellular and local area links and within
proximity of each other, are interested in the same video content. Traditional
network control algorithms introduce high overhead and delay in this setup as
the network control and cooperation decisions are made in a source-centric
manner. Instead, we develop a device-centric stochastic cooperation scheme. Our
device-centric scheme; DcC allows mobile devices to make control decisions such
as flow control, scheduling, and cooperation without loss of optimality. Thanks
to being device-centric, DcC reduces; (i) overhead; i.e., the number of control
packets that should be transmitted over cellular links, so cellular links are
used more efficiently, and (ii) the amount of delay that each packet
experiences, which improves quality of service. The simulation results
demonstrate the benefits of DcC
Energy-Efficient Resource Allocation Optimization for Multimedia Heterogeneous Cloud Radio Access Networks
The heterogeneous cloud radio access network (H-CRAN) is a promising paradigm
which incorporates the cloud computing into heterogeneous networks (HetNets),
thereby taking full advantage of cloud radio access networks (C-RANs) and
HetNets. Characterizing the cooperative beamforming with fronthaul capacity and
queue stability constraints is critical for multimedia applications to
improving energy efficiency (EE) in H-CRANs. An energy-efficient optimization
objective function with individual fronthaul capacity and inter-tier
interference constraints is presented in this paper for queue-aware multimedia
H-CRANs. To solve this non-convex objective function, a stochastic optimization
problem is reformulated by introducing the general Lyapunov optimization
framework. Under the Lyapunov framework, this optimization problem is
equivalent to an optimal network-wide cooperative beamformer design algorithm
with instantaneous power, average power and inter-tier interference
constraints, which can be regarded as the weighted sum EE maximization problem
and solved by a generalized weighted minimum mean square error approach. The
mathematical analysis and simulation results demonstrate that a tradeoff
between EE and queuing delay can be achieved, and this tradeoff strictly
depends on the fronthaul constraint
Queue-Architecture and Stability Analysis in Cooperative Relay Networks
An abstraction of the physical layer coding using bit pipes that are coupled
through data-rates is insufficient to capture notions such as node cooperation
in cooperative relay networks. Consequently, network-stability analyses based
on such abstractions are valid for non-cooperative schemes alone and
meaningless for cooperative schemes. Motivated from this, this paper develops a
framework that brings the information-theoretic coding scheme together with
network-stability analysis. This framework does not constrain the system to any
particular achievable scheme, i.e., the relays can use any cooperative coding
strategy of its choice, be it amplify/compress/quantize or any
alter-and-forward scheme. The paper focuses on the scenario when coherence
duration is of the same order of the packet/codeword duration, the channel
distribution is unknown and the fading state is only known causally. The main
contributions of this paper are two-fold: first, it develops a low-complexity
queue-architecture to enable stable operation of cooperative relay networks,
and, second, it establishes the throughput optimality of a simple network
algorithm that utilizes this queue-architecture.Comment: 16 pages, 1 figur
Fuzzy-logic framework for future dynamic cellular systems
There is a growing need to develop more robust and energy-efficient network architectures to cope with ever increasing traffic and energy demands. The aim is also to achieve energy-efficient adaptive cellular system architecture capable of delivering a high quality of service (QoS) whilst optimising energy consumption. To gain significant energy savings, new dynamic architectures will allow future systems to achieve energy saving whilst maintaining QoS at different levels of traffic demand. We consider a heterogeneous cellular system where the elements of it can adapt and change their architecture depending on the network demand. We demonstrate substantial savings of energy, especially in low-traffic periods where most mobile systems are over engineered. Energy savings are also achieved in high-traffic periods by capitalising on traffic variations in the spatial domain. We adopt a fuzzy-logic algorithm for the multi-objective decisions we face in the system, where it provides stability and the ability to handle imprecise data
5G Ultra-dense networks with non-uniform Distributed Users
User distribution in ultra-dense networks (UDNs) plays a crucial role in
affecting the performance of UDNs due to the essential coupling between the
traffic and the service provided by the networks. Existing studies are mostly
based on the assumption that users are uniformly distributed in space. The
non-uniform user distribution has not been widely considered despite that it is
much closer to the real scenario. In this paper, Radiation and Absorbing model
(R&A model) is first adopted to analyze the impact of the non-uniformly
distributed users on the performance of 5G UDNs. Based on the R&A model and
queueing network theory, the stationary user density in each hot area is
investigated. Furthermore, the coverage probability, network throughput and
energy efficiency are derived based on the proposed theoretical model. Compared
with the uniformly distributed assumption, it is shown that non-uniform user
distribution has a significant impact on the performance of UDNs.Comment: 14 pages, 10 figure
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