Utility Proportional Fairness Resource Allocation with Carrier Aggregation in 4G-LTE

Shajaiah, Haya; Abdelhadi, Ahmed; Clancy, T. Charles

doi:10.1109/milcom.2013.77

Cited by 51 publications

(58 citation statements)

References 5 publications

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“…Therefore, it emerges the new method called CA technique [9][10]. There are three different modes of CA, namely intra-band contiguous, intraband non-contiguous, and inter-band CA [14][15][16][17][18]. 3GPP's radio access network (RAN) working group 4 (RAN 4) is responsible for setting performance requirements of CA technique which initially limits the aggregation up to two component carriers only.…”

Section: Carrier Aggregation Techniquesmentioning

confidence: 99%

Carrier Aggregation Technique to Improve Capacity in LTE-Advanced Network

Iskandar

Galih

2016

TELKOMNIKA

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Section: Carrier Aggregation Techniquesmentioning

confidence: 99%

Carrier Aggregation Technique to Improve Capacity in LTE-Advanced Network

Iskandar

Galih

2016

TELKOMNIKA

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“…The LTE Advanced carrier optimization problem, is similar to the one described in [7], can be written as:…”

Section: Spectrum Sharing Through Ra With Camentioning

confidence: 99%

“…A tractable optimal solution to the optimization problem exists as the authors have proven that the optimization problem is convex. A resource allocation optimization problem with carrier aggregation is formulated in [7]. The proposed resource allocation algorithm allocates the primary carrier resources optimally among users.…”

Section: Introductionmentioning

confidence: 99%

Resource allocation with carrier aggregation in LTE Advanced cellular system sharing spectrum with S-band radar

Shajaiah

Khawar

Abdelhadi

et al. 2014

2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN)

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Spectrum sharing is a promising solution for the problem of spectrum congestion. We consider a spectrum sharing scenario between a multiple-input multiple-output (MIMO) radar and Long Term Evolution (LTE) Advanced cellular system. In this paper, we consider resource allocation optimization problem with carrier aggregation. The LTE Advanced system has N BS base stations (BS) which it operates in the radar band on a sharing basis. Our objective is to allocate resources from the LTE Advanced carrier and the MIMO radar carrier to each user equipment (UE) in an LTE Advanced cell based on the running application of UE. Each user application is assigned a utility function based on the type of application. We propose a carrier aggregation resource allocation algorithm to allocate the LTE Advanced and the radar carriers' resources optimally among users based on the type of user application. The algorithm gives priority to users running inelastic traffic when allocating resources. Finally we present simulation results on the performance of the proposed carrier aggregation resource allocation algorithm.

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“…In the systems, the radio resources such as power and bandwidth are limited while the channel condition of each user may vary from time to time. Given channel state information (CSI), the available system resource is allocated to users according to certain performance metrics such as throughput and the traffic requirements [3]. Three traditional allocation algorithms, i.e., Max C/I, Round Robin (RR) and Proportional Fair (PF) Scheduling are widely deployed in practice [4].…”

Section: Introductionmentioning

confidence: 99%

Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems

Zhao

Xin

et al. 2015

Proceedings of the 11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustn

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Abstract-This paper presents a joint radio resource allocation scheme in LTE/LTE-A systems. In order to maximize system throughput while satisfying the minimum user rate requirement, the resource allocation is modeled as a convex optimization with constraints in this paper, which is proved to be NP-hard. Hence, a heuristic approach based on joint Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed. The proposed method exploits the benefits of GA and PSO so that it could avoid the low speed problem of genetic algorithm and the local optimum trap concern in particle swarm optimization algorithm. Simulation results show that the proposed algorithm can overcome the disadvantages of genetic algorithm and particle swarm optimization algorithm, and achieve better performance, e.g., a faster convergence and global optimum.

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Utility Proportional Fairness Resource Allocation with Carrier Aggregation in 4G-LTE

Cited by 51 publications

References 5 publications

Carrier Aggregation Technique to Improve Capacity in LTE-Advanced Network

Carrier Aggregation Technique to Improve Capacity in LTE-Advanced Network

Resource allocation with carrier aggregation in LTE Advanced cellular system sharing spectrum with S-band radar

Using Joint Particle Swarm Optimization and Genetic Algorithm for Resource Allocation in TD-LTE Systems

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