Optimal Multi-User Computation Offloading Strategy for Wireless Powered Sensor Networks

Wireless sensors network (WSN) is widely used for environmental monitoring, surveillance, healthcare, and security services. One of the most critical challenges that WSN facing is the heavy computation requirements and limited energy storage. The recent development of radio frequency-based (RF) wireless power transfer (WPT) and mobile computation offloading to cloud provide a promising solution to overcome these shortcoming. In this paper, we consider a multi-user Mobile/Multi-Access edge computing (MEC) aided WSN powered by the WPT, where BSs are equipped with multiple antennas jointly service the whole sensors, the sensor node is powered by the WPT only. An optimal multi-user computation offloading strategy is proposed, where sensor nodes choose to operate in either the offloading or the local computing. In addition, perfect channel state information (CSI) and imperfect CSI are taken into account. We study the optimization of computation task offloading in MEC aided WSN under the conditions of perfect CSI and imperfect CSI. In particular, the optimal dynamic time division duplex (D-TDD) factor is investigated. Numerical results confirm the advantages of the proposed computation offloading strategy over the conventional local computation design in handing computationally heavy tasks.