Smart Content Delivery in 5G Networks

Smart content

 

In this project, we proposed an Audience Driven live TV Scheduling (ADTVS) framework to maximize radio resource usage when providing TV broadcasting services over LTE networks. ADTVS is a system-level scheduling framework. It considers both available radio resources and audience preferences, in order to dynamically schedule TV channels for broadcasting at various time and locations. By conducting a simulation using real-life data and scenarios, we show that ADTVS significantly outperforms the static broadcast method. The numerical results show that, in average, ADTVS enables substantial improvement of broadcast efficiency and conserves considerable amount of radio resources while scarifying less than 5% of user services compared to the benchmark system. It is worth mentioning that KAUST campus was the platform for our implementation study. 

 

Duration

2016-2020

Team Members

  • Chun Pong Lau

  • Guoqing Ma

  • Shuping Dang

  • Abdulrahman Alabbasi

Selected Publications

  • C. P. Lau, A. Alabbasi, and B. Shihada, "An Efficient Content Delivery System for 5G CRAN Employing Realistic Human Mobility", IEEE Transactions on Mobile Computing, Vol. 15, No. 4, pp. 742-756, 2019. [PDF]
  • C. P. Lau, A. Alabbasi, and B. Shihada, "An Efficient Live TV Scheduling System for 4G LTE Broadcast", IEEE Systems Journal, Vol. 11, No. 4, pp. 2737 - 2748, 2017. [PDF]