14 research outputs found
Efficient Ambient LoRa Backscatter with On-Off Keying Modulation
Backscatter communication holds potential for ubiquitous and low-cost
connectivity among low-power IoT devices. To avoid interference between the
carrier signal and the backscatter signal, recent works propose a
frequency-shifting technique to separate these two signals in the frequency
domain. Such proposals, however, have to occupy the precious wireless spectrum
that is already overcrowded, and increase the power, cost, and complexity of
the backscatter tag. In this paper, we revisit the classic ON-OFF Keying (OOK)
modulation and propose Aloba, a backscatter system that takes the ambient LoRa
transmissions as the excitation and piggybacks the in-band OOK modulated
signals over the LoRa transmissions. Our design enables the backsactter signal
to work in the same frequency band of the carrier signal, meanwhile achieving
flexible data rate at different transmission range. The key contributions of
Aloba include: (1) the design of a low-power backscatter tag that can pick up
the ambient LoRa signals from other signals. (2) a novel decoding algorithm to
demodulate both the carrier signal and the backscatter signal from their
superposition. We further adopt link coding mechanism and interleave operation
to enhance the reliability of backscatter signal decoding. We implement Aloba
and conduct head-to-head comparison with the state-of-the-art LoRa backscatter
system PLoRa in various settings. The experiment results show Aloba can achieve
199.4 Kbps data rate at various distances, 52.4 times higher than PLoRa
XRLoc: Accurate UWB Localization for XR Systems
Understanding the location of ultra-wideband (UWB) tag-attached objects and
people in the real world is vital to enabling a smooth cyber-physical
transition. However, most UWB localization systems today require multiple
anchors in the environment, which can be very cumbersome to set up. In this
work, we develop XRLoc, providing an accuracy of a few centimeters in many
real-world scenarios. This paper will delineate the key ideas which allow us to
overcome the fundamental restrictions that plague a single anchor point from
localization of a device to within an error of a few centimeters. We deploy a
VR chess game using everyday objects as a demo and find that our system
achieves cm median accuracy and cm percentile
accuracy in dynamic scenarios, performing at least better than
state-of-art localization systems. Additionally, we implement a MAC protocol to
furnish these locations for over tags at update rates of Hz, with a
localization latency of ms