PROJECT TITLE :

Energy Efficiency Maximization in Mobile Wireless Energy Harvesting Sensor Networks - 2018

ABSTRACT:

In mobile Wireless Sensor Networks (MWSNs), scavenging energy from ambient radio frequency (RF) signals could be a promising solution to prolonging the lifetime of energy-constrained relay nodes. During this Project, we apply the Simultaneous Wireless Data and Power Transfer (SWIPT) technique to a MWSN where the energy harvested by relay nodes can compensate their energy consumption on information forwarding. In such a network, how to maximize system energy potency (bits/Joule delivered to relays) bytrading off energy harvesting and data forwarding may be a important issue. To this end, we tend to style a resource allocation (ResAll) algorithm by considering different power splitting abilities of relays undertwo situations. In the primary scenario, the power received by relays is split into a continual set of power streams with arbitrary power splitting ratios. In the second situation, the received power is solely split into a discrete set of power streams with fixed power splitting ratios. For every situation above, we tend to formulate the ResAll problem in a very MWSN with SWIPT as a non-convex energy efficiency maximization downside. By exploiting fractional programming and twin decomposition, we more propose a cross-layer ResAll algorithm consisting of subalgorithms for rate control, power allocation, and power splitting to solve the matter efficiently and optimally. Simulation results reveal that the proposed ResAll algorithm converges within a tiny range of iterations, and achieves optimal system energy potency by balancing energy potency, information rate, transmit power, and power splitting ratio.