A novel traffic load balancing approach for scheduling of optical transparent antennas (OTAs) on mobile terminals

Optical transparent antennas (OTAs) are a relatively new technology that allows for high-speed wireless communication using a transparent antenna placed on the surface of a mobile device. However, scheduling OTA transmissions can be challenging due to several factors that must be considered. One critical consideration when developing a scheduling plan for OTAs is bandwidth. OTA-based mobile terminals require a significant amount of bandwidth to transmit and receive data, which means it's essential to ensure that enough bandwidth is available for OTA transmissions. This can be achieved by monitoring network traffic patterns and allocating sufficient bandwidth for OTA transmissions. Another important factor to consider is the signal strength of OTA transmissions. The strength of these signals can be affected by factors such as weather conditions, interference from other sources, and the location of the mobile terminal. Scheduling of OTAs can be planned successfully when the signal strength is optimal to ensure that transmissions can take place without any hurdles. Developing a scheduling plan for OTAs in mobile terminals is a complicated process, requiring consideration of several factors. These include ensuring sufficient bandwidth for OTA transmissions due to their high bandwidth requirements, signal strength should be optimal and OTA usage should be minimal when battery levels are low to conserve power. Additionally, network congestion and user preferences should also be considered when scheduling the OTAs. The smart scheduling mechanisms are required to handle the mobile applications while handling OTAs on mobile terminals. This study is proposing a modified traffic load clustering (MTLC) scheduling mechanism for scheduling OTAs on mobile terminals. The proposed MTLC method offers better spectrum efficiency above 90%, time-slot utilization between 88 and 95%, and channel utilization between 80 and 90% during scheduling of optical antennas. It also optimizes the latency time, throughput, and outperforms other algorithms.