A backscatter tag-to-tag network enables battery-less communication by harvesting energy and reflecting wireless signals between tags, making it ideal for energy-efficient IoT applications such as asset tracking, structural health monitoring, and environmental sensing. Accurate localization is crucial for these applications. While RSSI-based (Received Signal Strength Indicator) localization is the most common method for RF localization—estimating distance based on the received signal strength—it is often dependent on the position and power of the excitation source. We present a novel distance estimation method based on the estimation of the channel path loss and phase between tags, which is independent of the excitation source’s position and power. The experimental results demonstrate millimeter-level accuracy in 67% of cases and 99% accuracy within 17 cm for tag-to-tag distances up to 2.4 meters at 915 MHz.

Large scale networks of intelligent sensors that can function without any batteries will have enormous implications in applications that range from smart spaces to structural and environmental monitoring. RF tags present an amenable platform for sensor integration as the backscatter communication offers low energy cost of communication. Current RF tags either use extremely low-power sensors or perform tasks of tag localization and identification based on the strength of the backscatter signal. We present a technique for estimation of amplitude and phase of the tag-to-tag channel that can be performed with very limited computational and energy resources. This enables monitoring of the interactions between tagged objects and activities around tags, as well as assessment of a variety of engineering structures. Experimental results demonstrate high resolution in the amplitude and phase channel measurement at a distances ranging from 22 cm to 1.34 m.

Backscattering tags transmit passively without an on-board active radio transmitter. Almost all present-day backscatter systems, however, rely on active radio receivers. This presents a significant scalability, power and cost challenge for backscatter systems. To overcome this barrier, recent research has empowered these passive tags with the ability to reliably receive backscatter signals from other tags. This forms the building block of passive networks wherein tags talk to each other without an active radio on either the transmit or receive side. For wider functionality, accurate localization of such tags is critical. All known backscatter tag localization techniques rely on active receivers for measuring and characterizing the received signal. As a result, they cannot be directly applied to passive tag-to-tag networks. This paper overcomes the gap by developing a localization technique for such passive networks based on a novel method for phase-based ranging in passive receivers. This method allows pairs of passive tags to collaboratively determine the inter-tag channel phase while effectively minimizing the effects of multipath and noise in the surrounding environment. Building on this, we develop a localization technique that benefits from large link diversity uniquely available in a passive tag-to-tag network. We evaluate the performance of our techniques with extensive micro-benchmarking experiments in an indoor environment using fabricated prototypes of tag hardware. We show that our phase-based ranging performs similar to active receivers, providing median 1D ranging error <1 cm and median localization error also <1 cm. Benefiting from the large-scale link diversity our localization technique outperforms several state-of-the-art techniques that use active receivers.

Mobile devices have become the primary mode for Internet access in developing countries. Yet typical data plans and SMS costs can be overwhelming for low income users in these countries. In this paper, we explore the design and usability of a free but extremely low bit rate communication channel to address this challenge. We propose, a data communication channel that uses to transmit messages between phones, thereby sacrificing performance in exchange for low cost. While the data rate of is extremely low (<1 bps), our prototype implementation and small scale user studies explore the feasibility of this idea for different types of messaging scenarios. Our results show that could be a viable option for messaging scenarios that require short, pre-determined responses (e.g., survey questions) while for traditional SMS-style messaging, a suitable user interface and other customizations are likely required to make it a viable option for users.

In this paper, we present a technique whereby passive tags can track each other in a backscattering tag-to-tag network (BTTN). In such a network, passive tags without any on-board radio transceivers communicate directly with each other by backscattering an external excitation signal. First, we explain how the tags determine their distances to other communicating tags in their proximity and then how they can track nearby tags. Our technique is based on multiphase backscattering, more specifically, on the ability of backscattering tags to systematically change the phase offset of the signal that is being backscattered. A passive receiving tag with an envelope detector can then examine the received signal amplitude over the multiple backscattering phases and can draw inferences about the inter-tag distance. We demonstrate our method and show its accuracy on tags that we have built in our lab. Experiments show that our passive tags can measure Doppler shifts with approximately the same accuracy as that achieved by active conventional RFID readers. Our median tracking error based on data from two tags is only about 2.5 cm.

We propose, design, and prototype (using software defined radios) a layered hybrid decode-estimate- and-forward relaying strategy. The scheme relies on splitting the source message into two layers with unequal error protection (UEP). Considering half-duplex relay operation, cooperation takes place over two time-slots. The relay attempts to decode both layers during the first time-slot; with the probability of successfully decoding one of the layers being higher than the other due to UEP between the two layers. During the second time-slot, the relay transmits the jointly encoded message containing the successfully decoded layer(s) with the (imperfect) decoding estimates of the unrecoverable layer(s). In order to recover the source information, we design a decoding strategy at the destination that jointly operates on the signals received from the source and the relay. The proposed scheme is implemented using off-the-shelf systematic low-density parity-check codes, with joint decoding achieved through iterative message-passing. Simulations over narrowband Gaussian links indicate a performance gain of up to 3 dB compared to the unlayered operation at the source. We also present prototype results with over-the-air transmissions using National Instruments (NI) USRPs 2921s with all baseband processing implemented in NI LabView. These experimental results indicate significant performance gains over a conventional unlayered relaying approach.