Survey of Indoor Localization Based on Deep Learning

This study comprehensively examines the current state of deep learning (DL) usage in indoor positioning.It emphasizes the significance and efficiency of convolutional neural networks (CNNs) and recurrent neuralnetworks (RNNs). Unlike prior studies focused on single sensor modalities like Wi-Fi or Bluetooth, this researchexplores the integration of multiple sensor modalities (e.g.,Wi-Fi, Bluetooth, Ultra-Wideband, ZigBee) to expandindoor localization methods, particularly in obstructed environments. It addresses the challenge of precise objectlocalization, introducing a novel hybrid DL approach using received signal information (RSI), Received SignalStrength (RSS), and Channel State Information (CSI) data to enhance accuracy and stability. Moreover, thestudy introduces a device-free indoor localization algorithm, offering a significant advancement with potentialobject or individual tracking applications. It recognizes the increasing importance of indoor positioning forlocation-based services. It anticipates future developments while acknowledging challenges such as multipathinterference, noise, data standardization, and scarcity of labeled data. This research contributes significantly toindoor localization technology, offering adaptability, device independence, and multifaceted DL-based solutionsfor real-world challenges and future advancements. Thus, the proposed work addresses challenges in objectlocalization precision and introduces a novel hybrid deep learning approach, contributing to advancing locationcentricservices.While deep learning-based indoor localization techniques have improved accuracy, challenges likedata noise, standardization, and availability of training data persist. However, ongoing developments are expectedto enhance indoor positioning systems to meet real-world demands.

A Compact Dual-Port Multi-Band Rectifier Circuit for RF Energy Harvesting

This paper presents a compact multi-band rectifier with an improved impedance matching bandwidth.It uses a combination of–matching network(MN)at Port-1,with a parallel connection of three cell branch MN at Port-2.The proposed impedance matching network(IMN)is adopted to reduce circuit complexity,to improve circuit performance,and power conversion efficiency(PCE)of the rectifier at low input power.The fabricated rectifier prototype operates at 0.92,1.82,2.1,2.46 and 2.65 GHz covering GSM/900,GSM/1800,UMTS2100,and Wi-Fi/2.45–LTE2600.The size of the compact rectifier on the PCB board is 0.13λ_(g)×0.1λ_(g).The fabricated rectifier achieved an RF-to DC(radio frequency direct current)PCE of 31.8%,24%,22.7%,and 15%,and 14.1%for−20 dBm at the five respective measured operating frequencies.The circuit attains a peak RF-to-DC PCE of 82.3%for an input power of 3 dBm at 0.92 GHz.The proposed rectifier realizes an ambient output dc voltage of 454 mV for multi-tone input signals from the two ports.The rectifier drives a bq25504-674 power management module(PMM)to achieve 1.21 V from the two-port connection.The rectifier has the ability to exploit both frequency domain through the multi-band operation with good impedance bandwidth and a spatial domain using dual-port configuration.Hence,it is a potential candidate for various applications in radio frequency energy harvesting(RFEH)system.

Design of a Five-Band Dual-Port Rectenna for RF Energy Harvesting

This paper proposed the design of a dual-port rectifier with multifrequency operations.The RF rectifier is achieved using a combination of L-section inductive impedance matching network(IMN)at Port-1 with a multiple stubs impedance transformer at Port-2.The fabricated prototype can harvest RF signal from GSM/900,GSM/1800,UMTS/2100,Wi-Fi/2.45 and LTE/2600 frequency bands at(0.94,1.80,2.10,2.46,and 2.63 GHz),respectively.The rectifier occupies a small portion of a PCB board at 0.20λg×0.15λg.The proposed circuit realized a measured peak RF-to-dc(radio frequency direct current)power conversion efficiency(PCE)of(21%,22.76%,25.33%,21.57%,and 22.14%)for an input power of−20 dBm.The RF harvester attains a measured peak RF-to-dc PCE of 72.70%and an output dc voltage of 154 mV for an input power of 3 dBm at 2.46 GHz.Measurement of the proposed rectifier in the ambiance gives a peak dc output voltage of 376.1 mV from the five signal tones.Similarly,a low-powered bq25504-674 evaluation module(EVM)is integrated with the rectifier.The module boost and drive the rectifier output dc voltage to 945 mV.The performance of the proposed rectifier in the ambiance environment makes it a suitable module for low-powered RF applications.