15 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
A Utility Proportional Fairness Resource Allocation in Spectrally Radar-Coexistent Cellular Networks
Spectrum sharing is an elegant solution to addressing the scarcity of the
bandwidth for wireless communications systems. This research studies the
feasibility of sharing the spectrum between sectorized cellular systems and
stationary radars interfering with certain sectors of the communications
infrastructure. It also explores allocating optimal resources to mobile devices
in order to provide with the quality of service for all running applications
whilst growing the communications network spectrally coexistent with the radar
systems. The rate allocation problem is formulated as two convex optimizations,
where the radar-interfering sector assignments are extracted from the portion
of the spectrum non-overlapping with the radar operating frequency. Such a
double-stage resource allocation procedure inherits the fairness into the rate
allocation scheme by first assigning the spectrally radar-overlapping
resources
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
media, including reprinting/republishing this material for advertising or
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this work in other work
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
On the use of prioritization and network slicing features for mission critical and commercial traffic multiplexing in 5G Radio Access Networks
© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The Public Protection and Disaster Relief (PPDR) sector is undergoing an important transition with the deployment of Mission Critical (MC) mobile broadband technology based on 3GPP standards, with multiple initiatives on-going worldwide for providing PPDR agencies with broadband communications capabilities. One common approach being adopted is the delivery of MC services together with commercial traffic over public mobile networks and the use of prioritization mechanisms to protect the MC connections in congestion situations. However, this approach leaves commercial traffic unprotected in front of a noncontrolled surge of MC traffic in specific cells since all resources would be allocated to serve this traffic. In this context, this paper proposes a solution to properly multiplex MC and commercial services with congestion protection for both types of services. The solution is based on the exploitation of the network slicing features brought into the new 5G standards. In particular, the paper describes how different slices can be parameterized in a 5G Radio Access Network (RAN) so that radio load guarantees can be established for each type of service. The proposed solution is evaluated in an illustrative scenario by means of simulations. Obtained results show the improvements in traffic isolation achievable by the slicing configuration when compared to the solution that only relies on prioritization mechanismsPeer ReviewedPostprint (author's final draft