A utility proportional fairness radio resource block allocation in cellular networks

Ghorbanzadeh, Mo; Abdelhadi, Ahmed; Clancy, T. Charles

doi:10.1109/iccnc.2015.7069394

Cited by 29 publications

(11 citation statements)

References 20 publications

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“…They considered QoS guaranteed for heterogeneous traffic in SG applications such that each traffic type has an associated fairness. Resource allocation strategies that utilize fairness criteria are also found in [66], [11], [96]- [101].…”

Section: Fairness Scheduling Criterionmentioning

confidence: 99%

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Ogbodo¹,

Dorrell²,

Abu‐Mahfouz³

2019

Preprint

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A cognitive radio sensor network (CRSN) based Smart Grid (SG) is a new paradigm for a modern SG. It is totally different from the traditional power grid and also different from the conventional SG that uses a static resource allocation technique to allocate resources to sensor nodes and communication devices in the SG network. Due to the challenges associated with competitive sensor nodes and communication devices in accessing and utilizing radio resources, the need for dynamic radio resource allocation (RRA) has been proposed as a solution for allocating radio resources to sensor nodes in a CRSN based smart grid ecosystem (network). These challenges include energy/power constraints, poor quality of service (QoS), interference, delay, spectrum efficiency issues, and excessive spectrum hand-offs. Hence, the optimization of resource allocation criteria, such as energy efficiency, throughput maximization, QoS guarantee, fairness, priority, interference mitigation/avoidance, etc., will go a long way in addressing the problems of RRA in a CRSN based SG. Consequently, this work explores RRA in CRSNs for SGs. Various resource allocation schemes, as well as its architecture in a CRSN for SG environment, are presented. The work reported in this paper introduces a model called the “guaranteed network connectivity channel allocation” for throughput maximization (GNC-TM) and optimal spectrum band determination in RRA for improved throughput criteria in CRSNs for SGs. The results show that the model outperforms the existing protocol in terms of throughput and error probability. Finally, the contribution to knowledge and future research direction, such as energy efficiency and hybrid energy harvesting schemes are highlighted.

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Section: Fairness Scheduling Criterionmentioning

confidence: 99%

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Ogbodo¹,

Dorrell²,

Abu‐Mahfouz³

2019

Preprint

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“…In [22] and [23], we present resource allocation with users discrimination algorithms to allocate the eNodeB resources optimally among mobile users with elastic and inelastic traffic. In [24], the authors have presented a radio resource block allocation optimization problem using a utility proportional fairness approach. The authors in [25] have presented an application-aware resource block scheduling approach for elastic and inelastic adaptive real-time traffic where users are assigned to resource blocks.…”

Section: A Related Workmentioning

confidence: 99%

Robust Resource Allocation With Joint Carrier Aggregation in Multi-Carrier Cellular Networks

Shajaiah

Abdelhadi

Clancy

2018

IEEE Trans. Cogn. Commun. Netw.

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Abstract-In this paper, we present a novel approach for robust optimal resource allocation with joint carrier aggregation to allocate multiple carriers resources optimally among users with elastic and inelastic traffic in cellular networks. We use utility proportional fairness allocation policy, where the fairness among users is in utility percentage of the application running on the user equipment (UE). Each 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 subscribing for mobile services. In addition, each user is guaranteed a minimum quality of service (QoS) that varies based on the user's application type. We present a robust algorithm that solves the drawback in the algorithm presented in [1] by preventing the fluctuations in the resource allocation process, in the case of scarce resources, and allocates optimal rates for both high-traffic and low-traffic situations. Our distributed resource allocation algorithm allocates an optimal rate to each user from all carriers in its range while providing the minimum price for the allocated rate. In addition, we analyze the convergence of the algorithm with different network traffic densities and show that our algorithm provides traffic dependent pricing for network providers. Finally, we present simulation results for the performance of our resource allocation algorithm.

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“…In [20] is presented the current problem in cellular communication systems, regarding the problem of optimization in the allocation of radio resources blocks, with users that are tolerant to delay and those who demand real time transmission, which were modeled as function of logarithmic and sigmoid utility. The optimization was carried out under the Proportional criterion with the purpose of maximizing the utility of these type of networks, while the allocation of the resources was carried out taking into account the QoS requirements of the application.…”

Section: Related Workmentioning

confidence: 99%

Multichannel allocation spectrum model with fairness criterion for cognitive radio networks

Hernández¹,

Marquez²,

Martínez³

2016

ces

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The inefficient use of the spectrum with the services which each time demand more bandwidth has generated a problem regarding the effective allocation of the spectrum and how to make a better use of it. The present paper develops a model of multiple channel allocation that allow to use in a more efficient way the spectrum opportunities in cognitive radio networks. The developed scheme allows doing the allocation of several contiguous and available frequency channels, to the secondary users that need higher bandwidth, in an environment of Fairness. The developed hybrid model of allocation is conformed by 3 algorithms, one in charge of locating the available frequency channels and gather them in multichannel bands, the second algorithm in charge of ranking these multichannel bands and finally the last algorithm in charge of establishing a fairness criterion to not restrict the spectral opportunities of the other secondary users who wish to transmit. The taken measurements correspond to the average bandwidth, average delay, average throughput and the fairness calculation in the allocation of several channels. The achieved results were evaluated with the experimental spectral occupation data, taken in GMS frequency band. The developed model shows an 1504 Cesar Hernández et al. improvement in the use of spectral opportunities and a higher average transmission bandwidth for each secondary user keeping the fairness criterion in the channel allocation.

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A utility proportional fairness radio resource block allocation in cellular networks

Cited by 29 publications

References 20 publications

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Radio Resource Allocation Improvements in CRSN for Smart Grid: A Survey

Robust Resource Allocation With Joint Carrier Aggregation in Multi-Carrier Cellular Networks

Multichannel allocation spectrum model with fairness criterion for cognitive radio networks

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