Concurrent Backscatter Streaming from Batteryless and Wireless Sensor Tags with Multiple Subcarrier Multiple Access

This paper proposes a novel multiple access method that enables concurrent sensor data streaming from multiple batteryless, wireless sensor tags. The access method is a pseudo-FDMA scheme based on the subcarrier backscatter communication principle, which is widely employed in passive RFID and radar systems. Concurrency is realized by assigning a dedicated subcarrier to each sensor tag and letting all sensor tags backscatter simultaneously. Because of the nature of the subcarrier, which is produced by constant rate switching of antenna impedance without any channel filter in the sensor tag, the tag-to-reader link always exhibits harmonics. Thus, it is important to reject harmonics when concurrent data streaming is required. This paper proposes a harmonics rejecting receiver to allow simultaneous multiple subcarrier usage. This paper particularly focuses on analog sensor data streaming which minimizes the functional requirements on the sensor tag and frequency bandwidth. The harmonics rejection receiver is realized by carefully handling group delay and phase delay of the subcarrier envelope and the carrier signal to accurately produce replica of the harmonics by introducing Hilbert and inverse Hilbert transformations. A numerical simulator with Simulink and a hardware implementation with USRP and LabVIEW have been developed. Simulations and experiments reveal that even if the CIR before harmonics rejection is 0dB, the proposed receiver recovers the original sensor data with over 0.98 cross-correlation

Leveraging Backscatter for Ultra-low Power Wireless Sensing Systems

The past few years have seen a dramatic growth in wireless sensing systems, with millions of wirelessly connected sensors becoming first-class citizens of the Internet. The number of wireless sensing devices is expected to surpass 6.75 billion by 2017, more than the world\u27s population as well as the combined market of smartphones, tablets, and PCs. However, its growth faces two pressing challenges: battery energy density and wireless radio power consumption. Battery energy density looms as a fundamental limiting factor due to slow improvements over the past several decades (3x over 22 years). Wireless radio power consumption is another key challenge because high-speed wireless communication is often far more expensive energy-wise than computation, storage and sensing. To make matters worse, wireless sensing devices are generating an increasing amount of data. These challenges raise a fundamental question --- how should we power and communicate with wireless sensing devices. More specifically, instead of using batteries, can we leverage other energy sources to reduce, if not eliminate, the dependence on batteries? Similarly, instead of optimizing existing wireless radios, can we fundamentally change how radios transmit wireless signals to achieve lower power consumption? A promising technique to address these questions is backscatter --- a primitive that enables RF energy harvesting and ultra-low-power wireless communication. Backscatter has the potential to reduce dependence on batteries because it can obtain energy by rectifying the wireless signals transmitted by a backscatter reader. Backscatter can also work by reflecting existing wireless signals (WiFi, BLE) when these are available nearby. Because signal reflection only consumes uWs of power, backscatter can enable ultra-low-power wireless communication. However, the use of backscatter for communicating with wireless sensing devices presents several challenges. First, decreasing RF power across distance limits the operational range of micro-powered backscatter devices. This raises the question of how to maintain a communication link with a backscatter device despite tiny amount of harvested power. Second, even though the backscatter RF front-end is extremely power-efficient, the computational and sensing overhead on backscatter sensors limit its ability to operate with a few micro-Watts of power. Such overhead is a negligible factor of overall power consumption for platforms where radio power consumption is high (e.g. WiFi or Bluetooth based devices). However, it becomes the bottleneck for backscatter based platforms. Third, backscatter readers are not currently deployed in existing indoor environments to provide a continuous carrier for carrying backscattered information. As a result, backscatter deployment is not yet widespread. This thesis addresses these challenges by making the following contributions. First, we design a network stack that enables continuous operation despite decreasing harvested power across distance by employing an OS abstraction --- task fragmentation. We show that such a network stack enables packet transfer even when the whole system is powered by a 3cmx3cm solar panel under natural indoor light condition. Second, we design a hardware architecture that minimizes the computational overhead of backscatter to enable over 1Mbps backscatter transmission while consuming less than 100uWs of power, a two order of magnitude improvement over the state-of-the-art. Finally, we design a system that can leverage both ambient WiFi and BLE signals for backscatter. Our empirical evaluation shows that we can backscatter 500bps data on top of a WiFi stream and 50kbps data on top of a Bluetooth stream when the backscatter device is 3m away from the commercial WiFi and Bluetooth receivers

Towards battery-free machine learning and inference in underwater environments

This paper is motivated by a simple question: Can we design and build battery-free devices capable of machine learning and inference in underwater environments? An affirmative answer to this question would have significant implications for a new generation of underwater sensing and monitoring applications for environmental monitoring, scientific exploration, and climate/weather prediction. To answer this question, we explore the feasibility of bridging advances from the past decade in two fields: battery-free networking and low-power machine learning. Our exploration demonstrates that it is indeed possible to enable battery-free inference in underwater environments. We designed a device that can harvest energy from underwater sound, power up an ultra-low-power microcontroller and on-board sensor, perform local inference on sensed measurements using a lightweight Deep Neural Network, and communicate the inference result via backscatter to a receiver. We tested our prototype in an emulated marine bioacoustics application, demonstrating the potential to recognize underwater animal sounds without batteries. Through this exploration, we highlight the challenges and opportunities for making underwater battery-free inference and machine learning ubiquitous

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. Particularly, this paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a profound study of the 6G vision and outlining five of its disruptive technologies, i.e., terahertz communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss their requirements, key challenges, and open research problems

A prospective look: key enabling technologies, applications and open research topics in 6G networks

The fifth generation (5G) mobile networks are envisaged to enable a plethora of breakthrough advancements in wireless technologies, providing support of a diverse set of services over a single platform. While the deployment of 5G systems is scaling up globally, it is time to look ahead for beyond 5G systems. This is mainly driven by the emerging societal trends, calling for fully automated systems and intelligent services supported by extended reality and haptics communications. To accommodate the stringent requirements of their prospective applications, which are data-driven and defined by extremely low-latency, ultra-reliable, fast and seamless wireless connectivity, research initiatives are currently focusing on a progressive roadmap towards the sixth generation (6G) networks, which are expected to bring transformative changes to this premise. In this article, we shed light on some of the major enabling technologies for 6G, which are expected to revolutionize the fundamental architectures of cellular networks and provide multiple homogeneous artificial intelligence-empowered services, including distributed communications, control, computing, sensing, and energy, from its core to its end nodes. In particular, the present paper aims to answer several 6G framework related questions: What are the driving forces for the development of 6G? How will the enabling technologies of 6G differ from those in 5G? What kind of applications and interactions will they support which would not be supported by 5G? We address these questions by presenting a comprehensive study of the 6G vision and outlining seven of its disruptive technologies, i.e., mmWave communications, terahertz communications, optical wireless communications, programmable metasurfaces, drone-based communications, backscatter communications and tactile internet, as well as their potential applications. Then, by leveraging the state-of-the-art literature surveyed for each technology, we discuss the associated requirements, key challenges, and open research problems. These discussions are thereafter used to open up the horizon for future research directions