1,300 research outputs found
A Price Selective Centralized Algorithm for Resource Allocation with Carrier Aggregation in LTE Cellular Networks
In this paper, we consider a resource allocation with carrier aggregation
optimization problem in long term evolution (LTE) cellular networks. In our
proposed model, users are running elastic or inelastic traffic. Each user
equipment (UE) is assigned an application utility function based on the type of
its application. Our objective is to allocate multiple carriers resources
optimally among users in their coverage area while giving the user the ability
to select one of the carriers to be its primary carrier and the others to be
its secondary carriers. The UE's decision is based on the carrier price per
unit bandwidth. We present a price selective centralized resource allocation
with carrier aggregation algorithm to allocate multiple carriers resources
optimally among users while providing a minimum price for the allocated
resources. In addition, we analyze the convergence of the algorithm with
different carriers rates. Finally, we present simulation results for the
performance of the proposed algorithm.Comment: Submitted to IEE
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
Context-Aware Resource Allocation in Cellular Networks
We define and propose a resource allocation architecture for cellular
networks. The architecture combines content-aware, time-aware and
location-aware resource allocation for next generation broadband wireless
systems. The architecture ensures content-aware resource allocation by
prioritizing real-time applications users over delay-tolerant applications
users when allocating resources. It enables time-aware resource allocation via
traffic-dependent pricing that varies during different hours of day (e.g. peak
and off-peak traffic hours). Additionally, location-aware resource allocation
is integrable in this architecture by including carrier aggregation of various
frequency bands. The context-aware resource allocation is an optimal and
flexible architecture that can be easily implemented in practical cellular
networks. We highlight the advantages of the proposed network architecture with
a discussion on the future research directions for context-aware resource
allocation architecture. We also provide experimental results to illustrate a
general proof of concept for this new architecture.Comment: (c) 2015 IEEE. Personal use of this material is permitted. Permission
from IEEE must be obtained for all other uses, in any current or future
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