Multi-Source WPT Enabled IoNT: Joint Resource Allocation for Fairness-Aware Reliability Maximization in the FBL Regime

In this paper, we study a multi-source wireless power transfer (MS-WPT) enabled Internet of Nano Things (IoNT) supporting multi-hop ultra-reliable low-latency communications (URLLC), i.e., nanosensors wirelessly transmit short packets to the same destination in a multi-hop collecting-then-relaying manner. For such MS-WPT enabled nanoscale relaying network, we for the first time characterize the fairness-aware reliability and propose a joint blocklength and dynamic MS-WPT power allocation design for maximum transmission error probability minimization. However, the mutual effects between multi-source, the infinite MS-WPT schemes, the nonlinear EH model, and the complex finite blocklength (FBL) reliability model make the problem nonconvex and intractable. To tackle these difficulties, we first characterize the optimal frame structure for MS-WPT and prove that an equivalent optimal performance can be achieved by limited WPT decisions corresponding to a finite number of sub-slots. Following that, an optimization problem with finite number of variables is formulated, nevertheless, remaining nonconvex. To cope with it, variable substitution, nonconvex relationship decoupling, relax variable introduction as well as successive convex approximation (SCA) are utilized to further reformulate the problem into local convex ones. A sub-optimal solution is finally achieved by the proposed iteration-based algorithm. Via numerical simulation, it is validated that a significant performance improvement is achieved by our proposed design.