This book explains how UHF tags and readers communicate wirelessly It gives an understanding of what limits the read range of a tag, how to increase it (and why that might result in breaking the law), and the practical things that need to be addressed when designing and implementing RFID technology Avoiding heavy math but giving breadth of coverage with the right amount of detail, it is an ideal introduction to radio communications for engineers who need insight into how tags and readers work
New to this edition:
• Examples of near-metal antenna techniques
• Discussion of the wakeup challenge for battery-assisted tags, with a BAT architecture example
• Latest development of protocols: EPC Gen 120
• Update 18000-6 discussion with battery-assisted tags, sensor tags, Manchester tags and wakeup provisions


The only book to give an understanding of radio communications, the underlying technology for Radio Frequency Identification (RFID)
Praised for its readability and clarity, it balances breadth and depth of coverage
New edition includes latest developments in chip technology, antennas and protocols

The RF in RFID : UHF RFID in Practice Ed. 2

There has been a booming interest in developing WiFi localization using multi-antenna (MIMO) access points (APs). Recent advances have demonstrated promising results that break the meter-accuracy barrier using commodity APs. Yet these state-of-the-art solutions require either multiple APs that are not necessarily available in practice, or multiple-channel measurements that disrupt normal data communication. In this paper, we present SiFi, a single AP-based indoor localization system that for the first time achieves sub-meter accuracy with a single channel only. The SiFi design is based on a key observation: with MIMO, the multiple (typically three) antennas of an AP are frequency-locked; although the accurate Time-of-Arrival (ToA) estimation on commodity APs is fundamentally limited by the imperfect time and frequency synchronization between the transmitter and receiver, there should be only one value for the ToA distortion that can cause three direct-path ToAs of the antennas to intersect at a single point, i.e., the position of the target. We develop the theoretical foundations of SiFi and demonstrate its realworld implementation with off-the-shelf WiFi cards. Our implementation introduces no hardware modification and is fully compatible with concurrent data transmission. It achieves a median accuracy of 0.93 m, which significantly outperforms the best known single AP single channel solution.

SiFi: Pushing the Limit of Time-Based WiFi Localization Using a Single Commodity Access Point

We present multiscatter, a novel backscatter design that can simultaneously work with multiple excitation signals for personal IoT sensors. Specifically, we show for the first time that the backscatter tag can identify various excitation signals in an ultra-low-power way, including WiFi, Bluetooth, and ZigBee. Further, we employ a new modulation approach, overlay modulation, that can leverage those excitation signals to convey tag data on top of productive data, which makes decoding both data possible with only a single personal radio. Since 2.4 GHz signals and personal radios are everywhere, multiscatter is readily deployable in our everyday IoT applications. We prototype multiscatter using an FPGA and various commodity radios. Extensive experiments show that for mixed 802.11b&n, Bluetooth and ZigBee signals, the average identification accuracy of four protocols is more than 93%. The maximal aggregate throughput of both productive and tag data is 278.4 kbps with a single Bluetooth radio, and the maximal backscatter ranges are 28 m, 22 m, and 20 m for WiFi, Bluetooth, and ZigBee, respectively. We also demonstrate that it can leverage excitation diversity to provide uninterrupted communication and greater throughput gains, whereas the single-protocol tag being idle when target carriers are not available.

Multiprotocol backscatter for personal IoT sensors

The communication reliability of state-of-the-art Bluetooth Low Energy (BLE) backscatter systems is fundamentally limited by their modulation schemes because the Binary Frequency Shift Keying (BFSK) modulation of the tag does not exactly match commodity BLE receivers designed for Gauss Frequency Shift Keying (GFSK) modulated signals with high bandwidth efficiency. Gaussian pulse shaping is a missing piece in state-of-the-art BLE backscatter systems. Inspired by active BLE and applying calculus, we present IBLE, a BLE backscatter communication system that achieves full compatibility with commodity BLE devices. IBLE leverages the fact that phase shift is the integral of frequency over time to build a reliable physical layer for BLE backscatter. IBLE uses instantaneous phase shift (IPS) modulation, GFSK modulation, and optional FEC coding to improve the reliability of BLE backscatter communication to the commodity level. We prototype IBLE using various commodity BLE devices and a customized tag with FPGA. Empirical results demonstrate that IBLE achieves PERs of 0.04% and 0.68% when the uplink distances are 2 m and 14 m respectively, which are 280x and 70x lower than the PERs of the state-of-the-art system RBLE. On the premise of meeting the BER requirements of the BLE specification, the uplink range of IBLE is 20 m. Since BLE devices are everywhere, IBLE is readily deployable in our everyday IoT applications.

Commodity-level BLE backscatter

Backscatter communication networks receive much attention recently due to the small size and low power of backscatter nodes. As backscatter communication is often influenced by the dynamic wireless channel quality, rate adaptation becomes necessary. Most existing approaches share a common drawback: they fail to take both spatial and frequency diversity into consideration at the same time. Consequently, the transmission rate may be improperly selected, resulting in low network throughput. In this paper, we propose a channel-aware rate adaptation framework (CARA) for backscatter networks. CARA incorporates three essential modules, a lightweight channel probing scheme that differentiates collisions from packet losses, a burstiness-aware channel selection mechanism benefiting as many backscatter nodes as possible, a rate selection method choosing the optimal rate, and a mobility detection that discovers location changes. We implement CARA on commercial readers, and the experiment results show that CARA achieves up to $4 \times$ goodput gain compared with the state-of-the-art rate adaptation scheme.

Channel-Aware Rate Adaptation for Backscatter Networks

Recently backscatter communication with commodity radios has received significant attention since specialized hardware is no longer needed. The state-of-the-art BLE backscatter system, FreeRider, realizes ultra-low-power BLE backscatter communication entirely using commodity devices. It, however, suffers from several key reliability issues, including unreliable two-step modulation, productive-data dependency, and lack of interference countermeasures. To address these problems, we propose RBLE, a reliable BLE backscatter system that works with a single commodity receiver. It first introduces direct frequency shift modulation with the single tone generated by an excitation BLE device, making robust single-bit modulation possible. Then it designs dynamic channel configuration that enables channel hopping to avoid interfered channels. Moreover, it presents BLE packet regeneration that uses adaptive encoding to further enhance reliability for various channel conditions. The prototype is implemented using TI BLE radios and customized tags with FPGAs. Empirical results demonstrate that RBLE achieves more than 17x uplink goodput gains over FreeRider under indoor LoS, NLoS, and outdoor environments. We also show that RBLE can realize uplink ranges of up to 25 m for indoors and 56 m for outdoors.

Reliable Backscatter with Commodity BLE

Recently backscatter networks have received booming interest because, they offer a battery-free communication paradigm using propagation radio waves as opposed to active radios in traditional sensor networks while providing comparable sensing functionalities, ranging from light and temperature sensors to recent microphones and cameras. While sensing data on backscatter nodes has been seen on a clear path to increase in both volume and variety, backscatter communication is not well prepared and optimized for transferring such continuous and high-volume data. To bridge this gap, we propose a high-throughput rate adaptation scheme for backscatter networks by exploring the unique characteristics of backscatter links and the design space of the ISO 18000-6C (C1G2) protocol. Our key insight is that while prior work has left the downlink unattended, we observe that the quality of downlink is affected significantly by multipath fading and thus can degrade the uplink and overall throughput considerably. Therefore, we introduce a novel rate mapping algorithm that chooses the best rate for both the downlink and uplink. Also, we design an efficient channel estimation method fully compatible with the C1G2 protocol and a reliable probing trigger, substantially saving probing overhead. Our scheme is prototyped using a COTS RFID reader and tags. The results show that we achieve up to 2.5x throughput gain over state-of-the-art approaches across various mobility, channel, and network-size conditions.

Towards higher throughput rate adaptation for backscatter networks

In the past few years, various backscatter nodes have been invented for many emerging mobile applications, such as sports analytics, interactive gaming, and mobile healthcare. Backscatter networks are expected to provide a high-throughput and stable communication platform for those interconnected mobile nodes. Yet, through experiments, we find state-of-the-art rate adaptation methods for backscatter networks share a fundamental limitation of accommodating the hardware diversity of nodes because the common mapping paradigm that chooses the optimal rate based on the radio signal strength indicator (RSSI) or the like is hardly adaptable to hardware-dependent RSSIs. To address this issue, we propose MobiRate (Mobility-aware Rate adaptation) that fully exploits the mobility hints from PHY information and the characteristics of backscatter systems. The key insight is that mobility-hints, like velocity and position, can greatly benefit rate selection and channel probing. Specifically, we introduce a novel velocity-based loss rate estimation method that dynamically re-weighs packets based on time and mobility. In addition, we design a mobility-assisted probing trigger and a new selective-probing mechanism, significantly saving probing time. As MobiRate is fully compatible with the current standard, it is prototyped using a COTS RFID reader and a variety of commercial tags. Our extensive experiments demonstrate that MobiRate achieves up to 3.8x throughput gain over the state-of-the-art methods across a wide range of mobility, channel conditions, and tag types.

MobiRate: Mobility-Aware Rate Adaptation Using PHY Information for Backscatter Networks

This paper presents RapidRider, the first WiFi backscatter system that takes uncontrolled OFDM WiFi signals, e.g., 802.11a/g/n, as excitations and efficiently embeds tag data at the single-symbol rate. Such design brings us closer to the dream of pervasive backscatter communication since uncontrolled WiFi signals are everywhere. Specifically, we show that RapidRider can demodulate tag data for each OFDM symbol while previous systems rely on multi-symbol demodulation. Further, we design deinterleaving-twins decoding that enables RapidRider to use any uncontrolled WiFi signals as carriers. We prototype RapidRider using FPGAs, commodity radios, and USRPs. Comprehensive evaluations show that RapidRider’s maximum throughput is 3.92x and 1.97x better than FreeRider and MOXcatter. To accommodate cases where there is only one receiver available, we design RapidRider+ that can take productive data and tag data on the same packet. Results demonstrate that it can achieve an aggregated goodput of productive and tag data around 1 Mbps on average.

RapidRider: Efficient WiFi Backscatter with Uncontrolled Ambient Signals

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