4,730 research outputs found
An Optimal Application-Aware Resource Block Scheduling in LTE
In this paper, we introduce an approach for application-aware resource block
scheduling of elastic and inelastic adaptive real-time traffic in fourth
generation Long Term Evolution (LTE) systems. The users are assigned to
resource blocks. A transmission may use multiple resource blocks scheduled over
frequency and time. In our model, we use logarithmic and sigmoidal-like utility
functions to represent the users applications running on different user
equipments (UE)s. We present an optimal problem with utility proportional
fairness policy, where the fairness among users is in utility percentage (i.e
user satisfaction with the service) of the corresponding applications. Our
objective is to allocate the resources to the users with priority given to the
adaptive real-time application users. In addition, a minimum resource
allocation for users with elastic and inelastic traffic should be guaranteed.
Every user subscribing for the mobile service should have a minimum
quality-of-service (QoS) with a priority criterion. We prove that our
scheduling policy exists and achieves the maximum. Therefore the optimal
solution is tractable. We present a centralized scheduling algorithm to
allocate evolved NodeB (eNodeB) resources optimally with a priority criterion.
Finally, we present simulation results for the performance of our scheduling
algorithm and compare our results with conventional proportional fairness
approaches. The results show that the user satisfaction is higher with our
proposed method.Comment: 5 page
Fairness Evaluation in Cooperative Hybrid Cellular Systems
Many method has been applied previously to improve the fairness of a wireless communication system. In this paper, we propose using hybrid schemes, where more than one transmission scheme are used in one system, to achieve this objective. These schemes consist of cooperative transmission schemes, maximal ratio transmission and interference alignment, and non-cooperative schemes, orthogonal and non-orthogonal schemes used alongside and in combinations in the same system to improve the fairness. We provide different weight calculation methods to vary the output of the fairness problem. We show the solution of the radio resource allocation problem for the transmission schemes used. Finally, simulation results is provided to show fairness achieved, in terms of Jain's fairness index, by applying the hybrid schemes proposed and the different weight calculation methods at different inter-site distances
An Application-Aware Spectrum Sharing Approach for Commercial Use of 3.5 GHz Spectrum
In this paper, we introduce an application-aware spectrum sharing approach
for sharing the Federal under-utilized 3.5 GHz spectrum with commercial users.
In our model, users are running elastic or inelastic traffic and each
application running on the user equipment (UE) is assigned a utility function
based on its type. Furthermore, each of the small cells users has a minimum
required target utility for its application. In order for users located under
the coverage area of the small cells' eNodeBs, with the 3.5 GHz band resources,
to meet their minimum required quality of experience (QoE), the network
operator makes a decision regarding the need for sharing the macro cell's
resources to obtain additional resources. Our objective is to provide each user
with a rate that satisfies its application's minimum required utility through
spectrum sharing approach and improve the overall QoE in the network. We
present an application-aware spectrum sharing algorithm that is based on
resource allocation with carrier aggregation to allocate macro cell permanent
resources and small cells' leased resources to UEs and allocate each user's
application an aggregated rate that can at minimum achieves the application's
minimum required utility. Finally, we present simulation results for the
performance of the proposed algorithm.Comment: Submitted to IEE
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