Real-time multiuser scheduling based on end-user requirement using big data analytics

摘要

With the rapid growth in wireless data networks and increasing demand for multimedia applications, the next generation of wireless networks should be able to provide services for heterogeneous traffic with diverse quality of service (QoS) requirements. Multiuser diversity refers to a type of diversity present across different users in a fading environment. This diversity can be exploited by scheduling transmissions so that users transmit when their channel conditions are favorable. Hence, scheduling algorithms that support QoS and maintain a required throughput to ensure users' satisfaction are crucial to the development of these wireless networks. In this paper, different scheduling techniques have been evaluated using OFDM with different scenarios. The goal is to analyze the properties of networks such as throughput, fairness, and delay. Experimental results indicate that the PFS approach outperforms the other techniques in terms of fairness, throughput, and delay.