Title: Efficient call admission control in LTE networks with cascade feed forward network

Authors: Vaishali Satish Jadhav; Pallavi Vasant Sapkale; Moresh M. Mukhedkar

Addresses: Department of Electronics, Ramrao Adik Institute of Technology, Dr. D.Y. Patil University, Dr. D.Y. Patil Vidyanagar, Sector-7, Nerul Navi Mumbai, Maharashtra, 400706, India ' Department of Electronics and Telecommunication, Ramrao Adik Institute of Technology, Dr. D.Y. Patil University, Dr. D.Y. Patil Vidyanagar, Sector-7, Nerul Navi Mumbai, Maharashtra, 400706, India ' Department of Electronics, D. Y. Patil University, Pune, D. Y. Patil College of Engineering, Ambi, Pune, 410507, India

Abstract: This research proposes a cascade feed forward network (Cascade FFN) for the optimal call admission control (CAC) over networks. Initially, the long-term evolution (LTE) network is simulated and the incoming call is recognised as a new call or else handoff call. Likewise, the handoff call is identified by various channel parameters. Finally, the CAC is performed using the Cascade FFN, which is obtained by incorporating the deep feed forward network (DFN) and cascaded deep neuro-fuzzy network (DNFN). After the admission of the new user, number of active users in the individual cell is updated. The simulation is performed based on various parameters and the proposed model has gained throughput of 444058 bps, cell power of 54.267 dBm, delay of 0.081 s, user call drop of 940, call blocking probabilities of handoff and new user as 0.693, and 0.677; and the call dropping probabilities of handoff and new user is 0.733, and 0.740.

Keywords: long term evolution (LTE) networks; CAC; call admission control; QoS; quality-of-service; DL; deep learning; FFN; feed forward network.

DOI: 10.1504/IJNVO.2025.149573

International Journal of Networking and Virtual Organisations, 2025 Vol.33 No.1, pp.14 - 38

Received: 06 May 2024
Accepted: 22 Sep 2024
Published online: 07 Nov 2025 *