Joint Offloading and Computing Optimization in Wireless Powered Mobile-Edge Computing Systems

Speaker:Dr. Feng Wang (Guangdong University of Technology)

Time and Date: 10:30-12:00, Oct. 19, 2016

Place: Room B415, Building of Computing Centre, Handan Campus

 

 

Abstract

Integrating mobile-edge computing (MEC) and wireless power transfer (WPT) is a promising technique in the Internet of Things (IoT) era. It can provide massive low-power mobile devices with enhanced computation capability and sustainable energy supply. In this paper, we consider a wireless powered multiuser MEC system, where a multi-antenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute latency-sensitive computation tasks. With MEC, each user can execute these tasks locally by itself or offload all or part of them to the AP following a time division multiple access (TDMA) protocol. Under this setup, we pursue an energy-efficient wireless powered MEC system design by jointly optimizing the transmit energy beamformer at the AP, the central processing unit (CPU) frequency and the offloaded bits at each user, as well as the time allocation among the users. In particular, we minimize the energy consumption at the AP over a particular time block subject to the computation latency and energy harvesting constraints per user. By formulating this problem into a convex framework and employing the Lagrange duality method, we obtain its optimal solution in a semi-closed form. Numerical results demonstrate the benefit of the proposed joint design over alternative benchmark schemes in terms of energy efficiency.

 

 

Biography

Feng Wang received the B.E. and Ph.D. degrees from the Nanjing University of Posts and Telecommunications and Fudan University in 2009 and 2016, respectively. From 2012 to 2013, he was a research fellow with Sharp Laboratories of China. Since 2016, he joined the School of Information Engineering, Guangdong University of Technology as a lecturer. His current research interests include energy efficiency and energy harvesting in wireless communications, multiuser MIMO beamforming, and signal processing for communications.