Load based dynamic channel allocation model to enhance the performance of device-to-device communication in WPAN

• Published in: Wireless networks Vol. 30; no. 4; pp. 2477 - 2509
• Main Authors: Logeshwaran, J., Shanmugasundaram, R. N., Lloret, Jaime
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.05.2024; Springer Nature B.V
• Subjects: Communication; Communications Engineering; Computer Communication Networks; Efficiency; Electrical Engineering; Energy consumption; Engineering; Interference; IT in Business; Load balancing; Networks; Original Paper; Personal area networks; Power control; Radio; Signal quality; Radio frequency; Efficiency; Network traffic; Channel; D2D; Dynamic channel allocation; Devices; Static; WPAN; Communication; Interferences
• ISSN: 1022-0038; 1572-8196
• DOI: 10.1007/s11276-024-03680-x

The modern communication network has advanced to such an extent that it is now possible for devices within a wireless personal area network (WPAN) to communicate among themselves directly. However, the limited shared radio resources of a WPAN lead to numerous issues, such as cross-layer interference and data collisions, which wind up affecting the quality of communication. A load based dynamic channel allocation (LB-DCA) model has been proposed to enhance the performance of device-to-device communication in WPAN. This model uses several control schemes in collaboration with interference estimation and channel load balancing mechanisms to allocate and manage the radio resources efficiently. The objective of this model is to achieve high throughput, low interference and low energy consumption. The control schemes implemented are based on distributed coordination and a cell-splitting approach. These schemes are utilized to estimate the channel usage and number of active nodes in a network. The interference estimation is done by using a new efficiency formula. Further, channel load balancing takes into account the hops and load factor values. The proposed model obtained 98.58% CSI, 95.86% MCC, 96.35% delta-P, 97.96% FMI, 99.83% BMI, 21.52% enhanced spectrum efficiency, 16.38% enhanced scalability, 18.79% enhanced signal quality, 18.64% enhanced power control and 18.89% enhanced energy efficiency.