In this paper, we propose a wirelessly powered Internet of Things (IoT) system based on the cell-free massive MIMO technology. In such a system, during the downlink phase, the sensors harvest radio-frequency (RF) energy emitted by the distributed access points (APs). During the uplink phase, sensors transmit data to the APs using the harvested energy. Collocated massive MIMO and small-cell IoT can be treated as special cases of cell-free IoT. We derive the tight closed-form lower bound on the amount of harvested energy, and the closed-form expression of SINR as the metrics of power transfer and data transmission, respectively. To improve the energy efficiency, we jointly optimize the uplink and downlink power control coefficients to minimize the total transmit energy consumption while meeting the target SINRs. Extended simulation results show that cell-free IoT outperforms collocated massive MIMO and small-cell IoT both in terms of the per user throughput for uplink, and the amount of energy harvested for downlink. Moreover, significant gains can be achieved by the proposed joint power control in terms of both per user throughput and energy consumption.
We investigate the long-term scheduling and power control scheme for a wirelessly powered cell-free Internet of Things (IoT) network which consists of distributed access points (APs) and large number of sensors. In each time slot, a subset of sensors are scheduled for uplink data transmission or downlink power transfer. Through asymptotic analysis, we obtain closedform expressions for the harvested energy and the achievable rates that are independent of random pilots. Then, using these expressions, we formulate a long-term scheduling and power control problem to maximize the minimum time avera…
In this paper, we introduce a backscatter assisted wirelessly powered mobile edge computing (MEC) network, where each edge user (EU) can offload task bits to the MEC server via hybrid harvest-then-transmit (HTT) and backscatter communications. In particular, considering a practical non-linear energy harvesting (EH) model and a partial offloading scheme at each EU, we propose a scheme to maximize the weighted sum computation bits of all the EUs by jointly optimizing the backscatter reflection coefficient and time, active transmission power and time, local computing frequency and execution time …
Due to the sustainable power supply and environment-friendly features, self-powered IoT devices have been increasingly employed in various fields such as providing observation data in remote areas, especially in rural areas or post-disaster scenarios. Generally, through multi-hop relay, the sensed data of those self-powered IoT devices are collected by the sink node which connects to the IoT backbones. However, due to the remoteness, the sink needs to be located at the border of the monitoring area where both the backbone of IoT and electrical infrastructures are accessible. Under such deploym…
Federated edge learning (FEEL) is a widely adopted framework for training an artificial intelligence (AI) model distributively at edge devices to leverage their data while preserving their data privacy. The execution of a power-hungry learning task at energy-constrained devices is a key challenge confronting the implementation of FEEL. To tackle the challenge, we propose the solution of powering devices using wireless power transfer (WPT). To derive guidelines on deploying the resultant wirelessly powered FEEL (WP-FEEL) system, this work aims at the derivation of the tradeoff between the model…
We investigate a wireless power transfer (WPT)-based backscatter-mobile edge computing (MEC) network with a {reconfigurable intelligent surface (RIS)}.In this network, wireless devices (WDs) offload task bits and harvest energy, and they can switch between backscatter communication (BC) and active transmission (AT) modes. We exploit the RIS to maximize energy efficiency (EE). To this end, we optimize the time/power allocations, local computing frequencies, execution times, backscattering coefficients, and RIS phase shifts.} This goal results in a multi-objective optimization problem (MOOP) wit…
Towards realizing an intelligent networked society, enabling low-cost low-energy connectivity for things, also known as Internet of Things (IoT), is of crucial importance. While the existing wireless access networks require centralized signaling for managing network resources, this approach is of less interest for future generations of wireless networks due to the energy consumption in such signaling and the expected increase in the number of IoT devices. Then, in this work we investigate leveraging machine learning for distributed control of IoT communications. Towards this end, first we inve…
Power supply for Internet of Things (IoT) devices is one of the bottlenecks in IoT development. To provide perpetual power supply to IoT devices, resonant beam charging (RBC) is a promising safe, long-range and high-power wireless power transfer solution. How long distance can RBC reach and how much power can RBC transfer? In this paper, we analyze the RBC's consistent and steady operational conditions, which determine the maximum power transmission distance. Moreover, we study the power transmission efficiency within the operational distance, which determines the deliverable power through the…
NarrowBand-Internet of Things (NB-IoT) is a new 3GPP radio access technology designed to provide better coverage for a massive number of low-throughput low-cost devices in delay-tolerant applications with low power consumption. To provide reliable connections with extended coverage, a repetition transmission scheme is introduced to NB-IoT during both Random Access CHannel (RACH) procedure and data transmission procedure. To avoid the difficulty in replacing the battery for IoT devices, the energy harvesting is considered as a promising solution to support energy sustainability in the NB-IoT ne…
The combination of non-orthogonal multiple access (NOMA) using power-domain with backscatter sensor communication (BSC) is expected to connect a large-scale Internet of things (IoT) devices in future sixth-generation (6G) era. In this paper, we introduce a BSC in multi-cell IoT network, where a source in each cell transmits superimposed signal to its associated IoT devices using NOMA. The backscatter sensor tag (BST) also transmit data towards IoT devices by reflecting and modulating the superimposed signal of the source. A new optimization framework is provided that simultaneously optimizes t…
Internet of things (IoT) is a revolutionizing technology which aims to create an ecosystem of connected objects and embedded devices and provide ubiquitous connectivity between trillions of not only smart devices but also simple sensors and actuators. Although recent advancements in miniaturization of devices with higher computational capabilities and ultra-low power communication technologies have enabled the vast deployment of sensors and actuators everywhere, such an evolution calls for fundamental changes in hardware design, software, network architecture, data analytic, data storage and p…
Battery-powered wireless IoT devices are now widely seen in many critical applications. Given the limited battery capacity and inaccessibility to external power recharge, optimizing energy efficiency (EE) plays a vital role in prolonging the lifetime of these IoT devices. However, a sheer amount of existing works only focus on the EE design at the infrastructure level such as base stations (BSs) but with little attention to the EE design at the device level. In this paper, we propose a novel idea that aims to shift energy consumption to a grid-powered cognitive radio mesh network thus preservi…
Device-free localization (DFL) is an emerging technology for estimating the position of a human or object that is not equipped with any electronic tag, nor participate actively in the localization process. Similar to device-based localization, the initial phase in DFL is to build the fingerprint database which is usually done manually using site surveying. This process is tedious, time-consuming, and vulnerable to environmental dynamics. Motivated by the recent advances in the Internet of Things (IoT), this paper introduces RadioGrapher; a system that automates the process of device-free finge…
Wireless powered backscatter communications (WPBC) is capable of implementing ultra-low-power communication, thus promising in the Internet of Things (IoT) networks. In practice, however, it is challenging to apply WPBC in large-scale IoT networks because of its short communication range. To address this challenge, this paper exploits an unmanned ground vehicle (UGV) to assist WPBC in large-scale IoT networks. In particular, we investigate the joint design of network planning and dynamic resource allocation of the access point (AP), tag reader, and UGV to minimize the total energy consumption.…
Billions of everyday objects could become part of the Internet of Things (IoT) by augmentation with low-cost, long-range, maintenance-free wireless sensors. Radio Frequency Identification (RFID) is a low-cost wireless technology that could enable this vision, but it is constrained by short communication range and lack of sufficient energy available to power auxiliary electronics and sensors. Here, we explore the use of flexible perovskite photovoltaic cells to provide external power to semi-passive RFID tags to increase range and energy availability for external electronics such as microcontro…
Photovoltaic (PV) cells have the potential to serve as on-board power sources for low-power IoT devices. Here, we explore the use of perovskite solar cells to power Radio Frequency (RF) backscatter-based IoT devices with a few μW power demand. Perovskites are suitable for low-cost, high-performance, low-temperature processing, and flexible light energy harvesting that hold the possibility to significantly extend the range and lifetime of current backscatter techniques such as Radio Frequency Identification (RFID). For these reasons, perovskite solar cells are prominent candidates for future lo…
The Internet of Things (IoT) has important applications in our daily lives including health and fitness tracking, environmental monitoring and transportation. However, sensor nodes in IoT suffer from the limited lifetime of batteries resulting from their finite energy availability. A promising solution is to harvest energy from environmental sources, such as solar, kinetic, thermal and radio frequency, for perpetual and continuous operation of IoT sensor nodes. In addition to energy generation, recently energy harvesters have been used for context detection, eliminating the need for additional…
This paper investigates a full-duplex orthogonal-frequency-division multiple access (OFDMA) based multiple unmanned aerial vehicles (UAVs)-enabled wireless-powered Internet-of-Things (IoT) networks. In this paper, a swarm of UAVs is first deployed in three dimensions (3D) to simultaneously charge all devices, i.e., a downlink (DL) charging period, and then flies to new locations within this area to collect information from scheduled devices in several epochs via OFDMA due to potential limited number of channels available in Narrow Band IoT, i.e., an uplink (UL) communication period. To maximiz…
Wireless energy transfer (WET) is emerging as an enabling green technology for Internet of Things (IoT) networks. WET allows the IoT devices to wirelessly recharge their batteries with energy from external sources such as dedicated radio frequency transmitters called power beacons (PBs). In this paper, we investigate the optimal deployment of PBs that guarantees a network-wide energy outage constraint. Optimal positions for the PBs are determined by maximizing the average incident power for the worst location in the service area since no information about the sensor deployment is provided. Suc…
Future IoT networks consist of heterogeneous types of IoT devices (with various communication types and energy constraints) which are assumed to belong to an IoT service provider (ISP). To power backscattering-based and wireless-powered devices, the ISP has to contract with an energy service provider (ESP). This article studies the strategic interactions between the ISP and its ESP and their implications on the joint optimal time scheduling and energy trading for heterogeneous devices. To that end, we propose an economic framework using the Stackelberg game to maximize the network throughput a…
Long range wireless connectivity opens the door for new IoT applications. Low energy consumption is essential to enable long autonomy of devices powered by batteries or even relying on harvested energy. This paper introduces technologies for long-distance interaction with energy-constraint embedded devices. It proposes sleepy strategies for power management for the platform and the transmission. Adequate signal processing on the remote modules is demonstrated to play a crucial role to sustain the autonomy of these systems. The presented open-source development platform invites the signal proce…
Over the recent years, the proliferation of smart devices and their applications has led to a rapid evolution of the concept of the Internet of Things (IoT), advancing large scale machine type networks which are characterized by sporadic transmissions of short packets. In contrast to typical communication models and in order to capture a realistic IoT environment, we study an asynchronous channel access performed by a primary ad hoc network underlaid with a cognitive secondary wireless-powered ad hoc network. Specifically, we consider that the primary transmitters are connected to the power gr…
In this paper, we develop a new framework called blockchain-based Radio Frequency (RF)-powered backscatter cognitive radio network. In the framework, IoT devices as secondary transmitters transmit their sensing data to a secondary gateway by using the RF-powered backscatter cognitive radio technology. The data collected at the gateway is then sent to a blockchain network for further verification, storage and processing. As such, the framework enables the IoT system to simultaneously optimize the spectrum usage and maximize the energy efficiency. Moreover, the framework ensures that the data co…
Generative AI-Powered Plugin for Robust Federated Learning in Heterogeneous IoT Networks
Institute of Information & Communications Technology Planning & Evaluation (IITP)-ITRC (Information Technology Research Center)（信息与通信技术规划与评估院（IITP）-ITRC（信息技术研究中心））
The semantic communication system enables wireless devices to communicate effectively with the semantic meaning of the data. Wireless powered Internet of Things (IoT) that adopts the semantic communication system relies on harvested energy to transmit semantic information. However, the issue of energy constraint in the semantic communication system is not well studied. In this paper, we propose a semantic-based energy valuation and take an economic approach to solve the energy allocation problem as an incentive mechanism design. In our model, IoT devices (bidders) place their bids for the ener…
In this paper, we investigate and analyze energy recycling for a reconfigurable intelligent surface (RIS)-aided wireless-powered communication network. As opposed to the existing works where the energy harvested by Internet of things (IoT) devices only come from the power station, IoT devices are also allowed to recycle energy from other IoT devices. In particular, we propose group switching- and user switching-based protocols with time-division multiple access to evaluate the impact of energy recycling on system performance. Two different optimization problems are respectively formulated for …
Reconfigurable Intelligent Sensing Surface enables Wireless Powered Communication Networks: Interference Suppression and Massive Wireless Energy Transfer
This letter considers a multi-pair decode-and-forward relay network where a power-splitting (PS) protocol is adopted at the energy-constrained relay to provide simultaneous wireless information and energy harvesting (EH). To achieve higher efficiency of EH, we propose a new PS-based EH architecture at the relay by incorporating an alternating current (AC) computing logic, which is employed to directly use the wirelessly harvested AC energy for computational blocks. Under a nonlinear EH circuit, our goal is to maximize the fairness of end-to-end rate among user pairs subject to power constraint…
This paper studies an unmanned aerial vehicle (UAV)-enabled two-user interference channel for wireless powered communication networks (WPCNs), in which two UAVs wirelessly charge two low-power Internet-of-things (IoT)-devices on the ground and collect information from them. We consider two scenarios when both UAVs cooperate in energy transmission and/or information reception via interference coordination and coordinated multi-point (CoMP), respectively. For both scenarios, the UAVs' controllable mobility is exploited via trajectory design to not only enhance the wireless power transfer (WPT) e…
Illinois Institute of Technology（伊利诺伊理工学院）；Argonne National Laboratory（阿贡国家实验室）
In this paper, we apply the Non-Orthogonal Multiple Access (NOMA) technique to improve the massive channel access of a wireless IoT network where solar-powered Unmanned Aerial Vehicles (UAVs) relay data from IoT devices to remote servers. Specifically, IoT devices contend for accessing the shared wireless channel using an adaptive $p$-persistent slotted Aloha protocol; and the solar-powered UAVs adopt Successive Interference Cancellation (SIC) to decode multiple received data from IoT devices to improve access efficiency. To enable an energy-sustainable capacity-optimal network, we study the j…
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this problem, energy harvesting offers a viable alternative to autonomously power IoT devices, resulting in a number of battery-less energy harvesting IoTs (or EH-IoTs) appearing in the market in recent years. Standards activities are also underway, which involve wireless protocol design suitable for EH-IoTs as well as testing procedures for various energy harvesting…
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, in which a multi-antenna hybrid access point (AP) wirelessly charges multiple users, and each user relies on the harvested energy to execute computation tasks. We jointly optimize the energy beamforming and remote task execution at the AP, as well as the local computing and task offloading, aiming to minimize the total system energy consumption over a finite time horizon, subject to causality constraints for both energy harvesting and task arrival at the users. In particular, we consider a practical scenario …
This paper studies a wireless powered mobile edge computing (MEC) system with device-to-device (D2D)-enabled task offloading. In this system, a set of distributed multi-antenna energy transmitters (ETs) use collaborative energy beamforming to wirelessly charge multiple users. By using the harvested energy, the actively computing user nodes can offload their computation tasks to nearby idle users (as helper nodes) via D2D communication links for self-sustainable remote computing. We consider the frequency division multiple access (FDMA) protocol, such that the D2D communications of different us…
Consider a large-scale cellular network in which base stations (BSs) serve massive Internet-of-Things (IoT) devices. Since IoT devices are powered by a capacity-limited battery, how to prolong their working lifetime is a paramount problem for the success of cellular IoT systems. This paper proposes how to use BSs to manage the active and dormant operating modes of the IoT devices via downlink signaling in an energy-efficient fashion and how the IoT devices perform energy-efficient uplink power control to improve their uplink coverage. We first investigate the fundamental statistical properties…
