Efficient Backhaul Design for 5G Ultra Dense Cells
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In 5G Ultra-Dense Cells, a distributed wireless backhaul is an attractive solution for forwarding traffic to the core. In this thesis, we investigate Gateway Location Problem and show that finding near optimal gateway locations improves the Backhaul Network Capacity(BNC). Toward this end, the p-median problem has been formulated as Integer Linear Program. Subsequently, we use Genetic Algorithm in combination with K-means algorithm to find gateway locations that maximize the BNC. We evaluate the performance of our new heuristic, K-GA, in comparison with six different approaches in terms of Average Number of Hops(ANH) and BNC at different node densities through extensive Monte Carlo simulations. All approaches are tested under different small cell distribution scenarios. K-GA achieves ANH and BNC within 3% of optimal and saves on-average 95% of time. We also analyze the effect of the number of gateways on ANH and BNC. The results show that more gateways are beneficial.
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Copyright © 2020 the author(s). Theses may be used for non-commercial research, educational, or related academic purposes only. Such uses include personal study, research, scholarship, and teaching. Theses may only be shared by linking to Carleton University Institutional Repository and no part may be used without proper attribution to the author. No part may be used for commercial purposes directly or indirectly via a for-profit platform; no adaptation or derivative works are permitted without consent from the copyright owner.
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- 2020
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raithatha-efficientbackhauldesignfor5gultradensecells.pdf | 2023-05-05 | Public | Download |