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"Optimizing Sample Delivery in RF-Charging Multi-Hop IoT Networks" by Muchen Jiang and Kwan Wu Chin

This paper studies sample delivery in a multi-hop network where a power beacon charges devices via radio frequency (RF) signals. Devices forward samples with a deadline from a source to a sink. The goal is to minimize the power beacon’s transmit power and guarantee that samples arrive at the sink with probability (1-) by their deadline, where is a given probability of failure. A key challenge is that the power beacon does not have instantaneous channel gains information to devices and also between devices; i.e., it does not know the energy level of devices. To this end, we formulate a chance-constrained stochastic program for the problem at hand, and employ the sample-average approximation (SAA) method to compute a solution. We also outline two novel approximation methods: Sampling based Probabilistic Optimal Power Allocation (S-POPA) and Bayesian Optimization based Probabilistic Optimal Power Allocation (BO-POPA). Briefly, S-POPA generates a set of candidate solutions and iterativel ....

Probabilistic Optimal Power Allocation , Bayesian Optimization , Array Signal Processing , Energy Transfer , Imperfect Knowledge , Nternet Of Things , Monte Carlo , Robabilistic Logic , Radio Frequency , Resource Management , Stochastic Optimization ,

"Maximizing Packets Collection in Wireless Powered IoT Networks with Ch" by Xiaoyu Song and Kwan Wu Chin

This paper studies data collection in a wireless powered Internet of things (IoT) network with a hybrid access point (HAP). A fundamental problem at the HAP is to determine the number of time slots over a given planning horizon that is used to charge and collect data from devices. To this end, we outline a mixed integer linear program (MILP) to determine (i) the mode (charge or data) of each slot, (ii) the HAP’s transmit power allocation, and (iii) transmitting devices in data slots. Further, we propose a receding horizon approach whereby the HAP solves the said MILP over a time window using channel estimates from a Gaussian mixture model (GMM). We also outline a data-driven approach. In its offline stage, an IoT network operator first solves the said MILP over an exhaustive collection of channel power gains. The MILP solution for each channel power gain realization is then stored in neural networks. In the online stage, the HAP accesses the trained neural network of each time slot t ....

Array Signal Processing , Data Collection , Data Communication , Model Predictive Control , Neural Network , Radio Frequency , Plinks Transmissions , Wireless Communication , Ireless Or Rf Charging ,

"A Novel Distributed Resource Allocation Scheme for Wireless Powered Co" by Tengjiao He, Kwan Wu Chin et al.

Abstract
This paper considers a novel Internet of Things (IoT) network comprising of sensor devices and Power Beacons (PBs); both types of nodes are equipped with a Cognitive Radio (CR). In addition, these sensor devices are powered by Radio Frequency (RF) signals from PBs. Our aim is to maximize the minimum rate of devices acting as sources. We outline the first Mixed Integer Linear Program (MILP) that jointly optimizes the channel assignment of PBs and devices, beamforming vector of PBs, data routing over multiple hops and link activation schedule of devices. We also design a distributed protocol called Distributed Max-min Rate with Cognitive Radio (D-MRCR) for use by devices and PBs. Devices set their operation mode using local information and use a game theory based approach to iteratively adjust their transmit power. On the other hand, each PB employs a Linear Program (LP) to determine its beamforming vector. Our results show that the max-min rate of D-MRCR is within 51.8 ....

Integer Linear Program , Linear Program , Power Beacons , Cognitive Radio , Radio Frequency , Mixed Integer Linear Program , Distributed Max Min Rate , Array Signal Processing , Channel Access , Cognitive Radio , Istributed Protocols , Nternet Of Things , Wireless Charging , Wireless Sensor Networks , முழு நேரியல் ப்ரோக்ர்யாம் , நேரியல் ப்ரோக்ர்யாம் , அறிவாற்றல் வானொலி , வானொலி அதிர்வெண் , கலப்பு முழு நேரியல் ப்ரோக்ர்யாம் ,