TY - GEN
T1 - Joint Caching in Fronthaul and Backhaul Constrained C-RAN
AU - Yao, Jingjing
AU - Ansari, Nirwan
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Caching popular contents closer to users has been proposed to alleviate wireless network traffic and improve user quality of experience (QoE). Decisions on where and what to cache is of great importance. In this paper, we propose a hierarchical cache-enabled cloud radio access network (C-RAN) architecture where joint caching is considered in both remote radio heads (RRHs) and baseband units (BBUs) with the constraints of backhaul and fronthaul links. We formulate the content placement problem as an integer linear programming (ILP) model with the objective of minimizing the average content download time. A heuristic algorithm is proposed in order to reduce the time complexity. Simulation results of the average download delay are analyzed from different aspects including caching locations, total file lengths, cache sizes and file popularities, and they demonstrate that the performance of the proposed popularity-based algorithm approximates ILP solutions closely but with high time efficiency.
AB - Caching popular contents closer to users has been proposed to alleviate wireless network traffic and improve user quality of experience (QoE). Decisions on where and what to cache is of great importance. In this paper, we propose a hierarchical cache-enabled cloud radio access network (C-RAN) architecture where joint caching is considered in both remote radio heads (RRHs) and baseband units (BBUs) with the constraints of backhaul and fronthaul links. We formulate the content placement problem as an integer linear programming (ILP) model with the objective of minimizing the average content download time. A heuristic algorithm is proposed in order to reduce the time complexity. Simulation results of the average download delay are analyzed from different aspects including caching locations, total file lengths, cache sizes and file popularities, and they demonstrate that the performance of the proposed popularity-based algorithm approximates ILP solutions closely but with high time efficiency.
UR - http://www.scopus.com/inward/record.url?scp=85046375428&partnerID=8YFLogxK
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U2 - 10.1109/GLOCOM.2017.8254679
DO - 10.1109/GLOCOM.2017.8254679
M3 - Conference contribution
T3 - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
SP - 1
EP - 6
BT - 2017 IEEE Global Communications Conference, GLOBECOM 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE Global Communications Conference, GLOBECOM 2017
Y2 - 4 December 2017 through 8 December 2017
ER -