Abstract:
Multi-Radio Access Technology (multi–RAT) carrier aggregation (CA), also known as multi-Flow CA, is an envisioned future technique that allows channels from different RATs to be aggregated and allocated to the end user. This technique allows for an efficient utilization of the fragmented and crowded spectrum, as well as for coordination and load balancing between the different RATs. The concept of CA was introduced in 3GPP’s Release 10 for the Long Term Evolution (LTE) systems, and the feasibility of LTE-LTE CA scenarios has been studied. In this work, we present a study of the feasibility of LTE-WiFi CA. We assume a CA mode where the LTE system borrows from the WiFi spectrum. Our study shows that this CA mode is compatible with the LTE-Advanced physical layer specifications, and is therefore theoretically achievable. This led us to propose a system design for achieving the LTE-WiFi CA mode, and to implement this design within the confines of the LTE and WiFi standards; that is, without introducing changes to these standards. Our scheme is suitable for small cell environments in which the LTE small base station and the WiFi Access Point are either collocated or are in close proximity, and provide cellular and WLAN access to a group of mobile users within a small geographical area. In the design, the LTE base station plays the role of a WiFi station that contends for accessing spectrum or requests access from the AP, and then aggregates this borrowed spectrum with the available LTE spectrum, thus increasing the cellular network throughput. We implemented the design using the OMNET++ network simulator, and generated results that highlight the performance of our scheme under different scenarios. The results show that about 40-50percent of the LTE scheduling intervals can benefit from our scheme in using the WiFi channels under typical WiFi load scenarios. Given this and the underutilized WiFi channels in certain scenarios, our scheme efficiently achieves higher bandwidths and thus higher data rates using cogn
Description:
Thesis. M.E. American University of Beirut. Department of Electrical and Computer Engineering, 2015. ET:6159
Advisor : Dr. Hassan Artail, Professor, Electrical and Computer Engineering ; Members of Committee : Dr. Zaher Dawy, Associate Professor, Electrical and Computer Engineering ; Dr. Haidar Safa, Associate Professor, Computer Science.
Includes bibliographical references (leaves 137-140)