Battery-free backscatter communication (BT-BackCom) is a promising technology for practical Internet of Things (IoT) due to its environmentally friendly operation and low maintenance cost. As it matures, BT-BackCom transforms applications such as logistics, mobile payments, healthcare, environmental sensing, and emergency communication. While energy harvesting techniques typically provide 10 μW to 1 mW of power, sustaining real-time transmission at the lower bound remains challenging. In this work, we investigate the minimum power budget required for real-time BT-BackCom burst transmissions. We identify a fundamental limitation in state-of-the-art low dropout (LDO) regulator-based designs caused by their hysteresis control, which limits reduction of the intermittent charging period. To address this, we propose a compact hysteresis-switch architecture that enables fine-grained control of the transmission cycle and minimizes energy waste between charging periods. The design exhibits near-zero quiescent current. Using low-cost commercial components, we prototype a monostatic BT-BackCom system that integrates analog backscatter, frequency-shift keying (FSK), a software-defined radio (SDR) interrogator, and self-interference cancellation. Our system achieves near real-time backscatter operation with a power budget as low as 11.36 μW and demonstrates zero bit error rate (BER) in FSK decoding at 18 dB signal-to-noise ratio (SNR), even under ambient light conditions as low as 30 lux.

The paper outlines the design, prototyping, and simulation processes involved in creating a compact radio frequency (RF) backscatter communication system, powered by Organic Photovoltaic (OPV) cells. This system is integral to a mine rescue operation, particularly useful in scenarios where miners are trapped due to accidents. In such situations, a rescue drone, equipped with a searchlight and the discussed communication system, takes the lead in the assisted escape mission for miners. The drone establishes duplex communication with the miners through a battery-free, wearable transponder device. Initial experiments employing a RF backscatter testbed - which utilizes both software-defined radios and OPV cells - were conducted. These preliminary tests were crucial for assessing the conditions necessary for successful backscatter communication, as well as for evaluating the energy-harvesting performance of the system. Findings from these experiments indicate that the device can operate battery-free, powered solely by OPV cells, even under low illuminance levels of less than 75 lux. In the pursuit of crafting the device in a compact form, a co-design initiative was launched. This effort focused on developing a meander dipole antenna in tandem with the OPV cells, targeting a resonant frequency of 912 MHz. Simulation results, obtained from ANSYS HFSS, revealed significant changes in antenna impedance and S parameters yet minimal impact on the radiation pattern of the antenna with the integration of the layered OPV structure.

In the event of a mine emergency, the inherently unstable environment poses significant risks and challenges to rescue efforts. The use of intelligent systems employing robots to aid in mine rescues has emerged as a promising approach. However, the communication infrastructure within mines is often compromised or insufficient to handle the network traffic demands of these systems following an incident. Consequently, there is a need for a temporary, deployable communication network capable of supporting both time-sensitive environmental monitoring (e.g., toxic or flammable gases) and high-throughput data transmission, such as video or 3D mapping. In this paper, we propose a wireless mesh network (WMN) featuring droppable nodes as a solution to address this challenge. We assess the signal-to-noise ratio required for a stable and continuous stream of 3D LiDAR mapping data and evaluate its feasibility in a mine setting using collected data from a mine tunnel. Furthermore, we employ the OMNeT++ network simulator in conjunction with the experimental data to investigate the potential of a larger network to fulfill the requirements for LiDAR streaming. Our findings indicate that a WMN within a mine environment has the potential to support high-volume data transmission, such as video and LiDAR streams, thus enhancing the effectiveness of intelligent mine rescue systems.

Retroreflective visible light communication and positioning (R-VLCP) is a novel ultralow-power Internet of Things (IoT) technology leveraging indoor light infrastructures. Compared to traditional VLCP, R-VLCP offers several additional favorable features, including self-alignment, low-size, weight, and power (SWaP), glaring-free, and sniff-proof. In analogy to RFID, R-VLCP employs a microwatt optical modulator (e.g., LCD shutter) to manipulate the intensity of the reflected light from a corner-cube retroreflector (CCR) to the photodiodes (PDs) mounted on a light source. In our previous works, we derived a closed-form expression for the retroreflection channel model, assuming that the PD is much smaller than the CCR in geometric analysis. In this article, we generalize the channel model to arbitrary size of PD and CCR. The received optical power is fully characterized relative to the sizes of PD and CCR, and the 3-D location of CCR. We also develop a custom and open-source ray tracing simulator—RetroRay, and use it to validate the channel model. Performance evaluation of area spectral efficiency and horizontal location error is carried out based on the channel model validated by RetroRay. The results reveal that increasing the size of PD and the density of CCRs improves communication and positioning performance with diminishing returns.

In urban environments, tall buildings or structures can pose limits on the direct channel link between a base station (BS) and an Internet of Thing device (IoTD) for wireless communication. Unmanned aerial vehicles (UAVs) with a mounted reconfigurable intelligent surface (RIS), denoted as UAV-RIS, have been introduced in recent works to enhance the system throughput capacity by acting as a relay node between the BS and the IoTDs in wireless access networks. Uncoordinated UAVs or RIS phase shift elements will make unnecessary adjustments that can significantly impact the signal transmission to IoTDs in the area. The concept of Age of Information (AoI) is proposed in wireless network research to categorize the freshness of the received update message. To minimize the Average Sum of AoI (ASoA) in the network, two model-free deep reinforcement learning (DRL) approaches—Off-Policy deepQ-network (DQN) and On-Policy proximal policy optimization (PPO)—are developed to solve the problem by jointly optimizing the RIS phase shift, the location of the UAV-RIS, and the IoTD transmission scheduling for large-scale Internet of Things wireless networks. Analysis of loss functions and extensive simulations is performed to compare the stability and convergence performance of the two algorithms. The results reveal the superiority of the On-Policy approach, PPO, over the Off-Policy approach, DQN, in terms of stability, convergence speed, and under diverse environment settings.

In this paper, we investigate the performance of a practical aggregated LiFi-WiFi system with the discrete constellation inputs from a practical view. We derive the achievable rate expressions of the aggregated LiFi-WiFi system for the first time. Then, we study the rate maximization problem via optimizing the constellation distribution and power allocation jointly. Specifically, a multilevel mercy-filling power allocation scheme is proposed by exploiting the relationship between the mutual information and minimum mean-squared error (MMSE) of discrete inputs. Meanwhile, an inexact gradient descent method is proposed for obtaining the optimal probability distributions. To strike a balance between the computational complexity and the transmission performance, we further develop a framework that maximizes the lower bound of the achievable rate where the optimal power allocation can be obtained in closed forms and the constellation distributions problem can be solved efficiently by Frank-Wolfe method. Extensive numerical results show that the optimized strategies are able to provide significant gains over the state-of-the-art schemes in terms of the achievable rate.

Visible light communication (VLC)-based indoor localization approaches enjoy many advantages, such as utilizing ubiquitous lighting infrastructure, high location accuracy, and no interruption to RF-based devices. However, existing VLC-based localization methods lack a real-time backward channel from the device to landmarks and necessitate computation at the device, which make them unsuitable for real-time tracking of small IoT devices. In this paper, we propose and prototype RETRO, that establishes an almost zero-delay backward channel by retroreflection. RETRO localizes passive IoT devices without requiring computation and heavy sensing (e.g., camera) at the devices. Multiple photodiodes (i.e., landmarks) are mounted on any single unmodified light source to sense the retroreflected optical signal (i.e., location signature). We derive a closed-form expression, which is validated by experiments and ray tracing simulations, for the reflected optical power relative to the location and the orientation of the retroreflector. The expression is applied to a received signal strength indicator and trilateration based localization algorithm. Extensive experiments demonstrate centimeter-level location accuracy and single-digit angular error. For practicality concern, to mitigate the thickness problem of a single retroreflector, the capabilities of different retroreflector arrays are studied. The range of the localization system is theoretically evaluated for different light emission patterns.

Identifying the accurate location of small objects is a key element of Internet of Things (IoT). This paper investigates the feasibility of tracking the real-time location of a completely passive retroreflector using visible light for IoT applications. Existing ultra-low power visible light retroreflector systems modulate light with a liquid crystal display (LCD) shutter, which is powered by a solar cell. However, the solar cell costs additional space exclusively for energy harvesting, and it may not be able to supply enough power to the advanced power-hungry LCD shutter and its driver circuit. To eliminate the power supply, we design, implement and evaluate PassiveRETRO, an enhanced retroreflector-based visible light localization system. The PassiveRETRO system completely eliminates the necessity of any electronic component on the IoT devices. Polarization-based modulation and bandpass optical filters are adopted to identify the retroreflected optical signal and create multiple channels. Each IoT device operates on a specific range of the visible light spectrum. Optical rotatory dispersion is further applied to mitigate the mutual interference among different channels. Experimental results from our prototyped system show that PassiveRETRO is robust to environmental reflection and can still achieve centimeter-level location accuracy when multiple IoT devices are deployed.

Indoor localization is very important to enable Internet-of-things (IoT) applications. Visible light communication (VLC)-based indoor localization approaches enjoy many advantages, such as utilization of existing ubiquitous lighting infrastructure, high location and orientation accuracy, and no interruption to RF -based devices. However, existing VLC-based localization methods lack a real-time backward channel from the device to landmarks and necessitate computation at the device, which make them unsuitable for real-time tracking of small IoT devices. In this paper, we propose and prototype a retroreflector-based visible light localization system (RETRO), that establishes an almost zero-delay backward channel using a retroreflector to reflect light back to its source. RETRO localizes passive IoT devices without requiring computation and heavy sensing (e.g., camera) at the devices. Multiple photodiodes (i.e., landmarks) are mounted on any single unmodified light source to sense the retroreflected optical signal (i.e., location signature). We theoretically derive a closed-form expression for the reflected optical power related to the location and orientation of the retroreflector, and validate the theory by experiments. The characterization of received optical power is applied to a received signal strength indicator and trilateration based localization algorithm. Extensive experiments demonstrate centimeter-level location accuracy and single-digit angular error.

Visible light communication (VLC) has the potential to add significant capacity to short range wireless access technology by piggybacking data on light from overhead luminaires. However, an uplink is required to complete such a network, which introduces new issues. In this paper, we propose and implement a practical hybrid WiFi-VLC system that does not require a separate VLC uplink but rather aggregates WiFi and VLC downlinks and shares the WiFi uplink. Aggregated downlink bandwidth of the hybrid system is achieved by using a Linux bonding driver and media access control (MAC) address redirection. The throughput of the system is tested and compared with WiFi-only (one WiFi downlink) and asymmetric (one VLC downlink) systems under a congested WiFi environment. The evaluation results show that our system achieves aggregated downlink bandwidth that is approximately the summation of the downlink capacities of the WiFi-only and asymmetric systems. The study of the round-trip time (RTT) demonstrates the tradeoff between bandwidth utilization and latency that can be used in the design of load-balancing algorithms. Finally, the deployed system demonstrates feasibility in typical indoor space room dimensions.

The coexistence of omnidirectional small cells (OSCs), such as RF small cells, and directional small cells (DSCs), such as visible-light communication cells, is investigated. The delay of two cases of such heterogeneous networks is evaluated. In the first case, resource allocated OSCs, such as RF femtocells, are considered. In the second case, contention-based OSCs, such as WiFi access point, are studied. For each case, two configurations are evaluated. In the first configuration, the non-aggregated scenario, any request is either allocated to OSC or DSC. While in the second configuration, the aggregated scenario, each request is split into two pieces, one is forwarded to OSC and the other is forwarded to DSC. For the first case, under Poisson request arrival process and exponential distribution of request size, the optimal traffic allocation ratio is derived for the non-aggregated scenario and it is mathematically proved that the aggregated scenario provides lower minimum average system delay than that of the non-aggregated scenario. For the second case, the average system delay is derived for both non-aggregated and aggregated scenarios, and extensive simulation results imply that, under certain conditions, the non-aggregated scenario outperforms the aggregated scenario due to the overhead caused by contention.

Visible light communications (VLC) is emerging as a new alternative to the use of the existing and increasingly crowded radio frequency (RF) spectrum. VLC is unlicensed, has wide bandwidth, supports new levels of security due to the opacity of walls, and can be combined to provide both lighting and data communications for little net increase in energy cost. As part of a lighting system, VLC is ideal as a downlink technology in which data are delivered from overhead luminaries to receivers in the lighting field. However, realizing a symmetric optical channel is problematic because most receivers, such as mobile devices, are ill-suited for an optical uplink due to glare, device orientation, energy constraints. In this paper we propose and implement a hybrid solution in which the uplink challenge is resolved by the use of an asymmetric RF-VLC combination. VLC is used as a downlink, RF is used as an uplink, and the hybrid solution realizes full duplex communication without performance glare or throughput degradation expected in an all-VLC-based approach. Our proposed approach utilizes a software defined VLC platform (SDVLC) to implement the unidirectional optical wireless channel and a WiFi link as the back-channel. Experiments with the implemented prototype reveal that the integrated system outperforms conventional WiFi for crowded (congested) multiuser environments in term of throughput, and demonstrate functional access to full-duplex interactive applications such as web browsing with HTTP.