TY - GEN
T1 - Strategic Deployment and Optimization of Cloud-RAN Architectures for Future Wireless Networks
AU - Katif, Youssef
AU - Hadhbi, Youssouf
AU - Ljubić, Ivana
AU - Vanier, Sonia
AU - Albenque, Jean Christophe
N1 - Publisher Copyright:
© 2026 IEEE.
PY - 2026/1/1
Y1 - 2026/1/1
N2 - This study investigates optimization models and algorithms aimed at enhancing the deployment of Cloud Radio Access Network architectures, a key enabler for next-generation wireless communication systems. This study addresses key challenges such as efficient data routing, effective resource management, and the scalability of the network infrastructure. To achieve this, we aim to optimize the placement of Distributed Units and Centralized Units, along with the data routing processes, to minimize latency and maximize data transfer efficiency. The problem is initially formulated as a combinatorial optimization problem for which a compact model based on an integer linear programming formulation is proposed. Based on this model, we develop an optimization framework aimed at identifying the most efficient strategies for deploying Cloud-RAN. Furthermore, we conduct computational experiments across various instances and scenarios to evaluate the effectiveness of the proposed approach.
AB - This study investigates optimization models and algorithms aimed at enhancing the deployment of Cloud Radio Access Network architectures, a key enabler for next-generation wireless communication systems. This study addresses key challenges such as efficient data routing, effective resource management, and the scalability of the network infrastructure. To achieve this, we aim to optimize the placement of Distributed Units and Centralized Units, along with the data routing processes, to minimize latency and maximize data transfer efficiency. The problem is initially formulated as a combinatorial optimization problem for which a compact model based on an integer linear programming formulation is proposed. Based on this model, we develop an optimization framework aimed at identifying the most efficient strategies for deploying Cloud-RAN. Furthermore, we conduct computational experiments across various instances and scenarios to evaluate the effectiveness of the proposed approach.
UR - https://www.scopus.com/pages/publications/105047834458
U2 - 10.1109/CoDIT70676.2026.11630893
DO - 10.1109/CoDIT70676.2026.11630893
M3 - Conference contribution
AN - SCOPUS:105047834458
T3 - 12th 2026 International Conference on Control, Decision and Information Technologies, CoDIT 2026
SP - 3335
EP - 3340
BT - 12th 2026 International Conference on Control, Decision and Information Technologies, CoDIT 2026
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 12th International Conference on Control, Decision and Information Technologies, CoDIT 2026
Y2 - 13 July 2026 through 16 July 2026
ER -