Authors:
Mzoughi Houda
1
;
Faouzi Zarai
1
;
Mohammad S. Obaidat
2
;
Balqies Sadoun
3
and
Lotfi Kamoun
1
Affiliations:
1
University of Sfax, Tunisia
;
2
Fordham University, United States
;
3
Al-Balqa Applied University, Jordan
Keyword(s):
LTE-Advanced, Radio Resource Allocation, MIH, LTE-a System Level Simulator.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Biomedical Instruments and Devices
;
Wireless Systems
Abstract:
Heterogeneity and convergence are two distinctive features for new generation networks like the Long Term Evolution-Advanced (LTE-A) system. LTE-A is now being deployed and is the way forward for high speed cellular services. LTE-A enhancements the four areas of capacity, coverage, inter-cells coordination, and cost. Improvements in these areas are based on using several technologies. Multiple-Input Multiple Output along with Orthogonal Frequency Division Multiple Access (MIMO/OFDMA) are two of the base technologies that are enablers. In addition, self-organizing and optimization (SON) technologies have been also developed to enable automatic configuration, optimization of network operations, including the 802.21 Media Independent Handover protocol (MIH), which is designed to optimize the vertical handover process. In this paper, we show the importance of inter-technologies and inter-entities cooperation, which can exploit heterogeneity as an enabler to improve the system capacity as
well as the quality of service (QoS) for users. We present a new cooperative radio resource allocation scheme for LTE-A network to coordinate better the utilization of network’s available radio resources. We adopted the MIH framework, in order to facilitate the exchange between heterogeneous network entities to insure self-configuration of radio resource management parameters. We worked on allocating the right PRB to the right user at the right time. We also analyze some existing solutions and evaluate our proposed scheme using simulation analysis. Simulation results illustrate the performance gains brought by the proposed optimization, especially for average throughput of macro-cell users comparing to their initial performance within two-tier LTE-A network.
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