scholarly journals Scatter radio relaying and applications

2020 ◽  
Author(s):  
Γεώργιος Βουγιούκας
Keyword(s):  
Low Cost ◽  
Solution Space ◽  
Unknown Origin ◽  
Doa Estimation ◽  
Low Complexity ◽  
Ultra Low Power ◽  
Single Antenna ◽  
Cost Constraints ◽  
Backscatter Communication ◽  
Fm Radio

Billions of devices are expected to be wirelessly connected in the foreseeable future. Sustaining such connectivity will require simple, elegant, engineering solutions. Based on backscatter radio principles, this dissertation offers novel, ultra-low-complexity, ultra-low-power, ultra-low-cost solutions, for connectivity in the field of narrowband wireless communications.Methods for achieving wireless communication by “recycling” radio waves, pre-existing in the environment, are offered and analysed. In contrast to generating own signals for transmission, a device (tag) adopting the suggested methods can transmit its information towards any conventional FM radio receiver, by recycling ambient signals from FM radio stations. That way, it is shown that batteryless information transmission can be achieved up to distances of 26 meters, by harvesting energy from the environment. Ultra-low cost prototypes consumed only 24 μWatt in continuous (non duty-cycled) operation.In the case of ambient signals of unknown origin and structure, digital modulation schemes are also offered, accompanied by novel coherent, partially-coherent illumination-agnostic, as well as fully noncoherent, channel-coded or uncoded detection algorithms. It is shown that under certain conditions, modulated and unknown ambient signals, can offer performance gains in the process of recovering tag's information signal, i.e., modulation of the ambient signal may be helpful. The proposed schemes do not require any cooperation with the ambient transmitter. That way, in sharp contrast to prior art, the tags adopting the proposed techniques are receiver-less; ultra-low-complexity and batteryless operation are also facilitated.Exploiting the aforementioned methods, originally intended for solving ambient backscatter communication problems, it is demonstrated for the first time that backscattering tags can also be used in an unorthodox way, for relaying signals in the frequency domain. Scatter radio relaying can be used to solve multi-antenna processing problems: a) blind (i.e., zero-feedback) beamforming, offering power gains in the order of 0.4-3.7 dB, and b) direction of arrival (DoA) estimation, offering error less than 5 degrees with 8 scattering tags. The proposed methods utilize single antenna radios without any requirement for channel feedback, multi-antenna RF front-ends or expensive controllers.The proposed techniques extend the solution space for engineers building wireless devices under power, complexity and cost constraints. Hopefully, this work will amplify the recent interest of the research community on backscatter radio and accelerate efforts towards the wide adoption of backscatter radio relaying in current and future commodity wireless systems, sensors and networks.

scholarly journals Ultra-low-power energy harvesting using power-optimized waveforms

2015 ◽  
Vol 3 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Christopher R. Valenta ◽  
Gregory D. Durgin
Keyword(s):  
Energy Harvesting ◽  
Low Power ◽  
Low Cost ◽  
Average Power ◽  
Input Power ◽  
Ultra Low Power ◽  
Backscatter Communication ◽  
Passive Sensors ◽  
Energy Harvesting Efficiency ◽  
Transfer Of Information

Power-optimized waveforms (POWs) are the enabling technology for realizing an internet-of-things (IoTs). An IoT will require billions or trillions of sensors, which must rely on passive, backscatter communication to facilitate the wireless transfer of information. Passive, backscatter sensors are uniquely suited for an IoT because of their ease of installation, low-cost, and lack of potentially toxic batteries. POW's primary benefit is that they can greatly improve the energy-harvesting efficiency of passive sensors, which increases their range and reliability. An overview of POWs is presented followed by measured results validated by a theoretical model and computer simulations. These measured results conducted at 5.8 GHz demonstrate the highest reported efficiency of a low-power, microwave energy-harvesting circuit of 26.3% at an input power of −10.2 dBm when using an excitation signal with a peak-to-average-power ratio of 12.

Low-Complexity DOA Estimation Based on Constraint Solution Space

2019 ◽  
Vol 111 (4) ◽  
pp. 2435-2447
Author(s):  
ShiBao Li ◽  
Li Sun ◽  
HaiHua Chen ◽  
JianHang Liu ◽  
TingPei Huang ◽  
...  
Keyword(s):  
Solution Space ◽  
Doa Estimation ◽  
Low Complexity

scholarly journals Recurrent Neural Network for Human Activity Recognition in Embedded Systems Using PPG and Accelerometer Data

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1715
Author(s):  
Michele Alessandrini ◽  
Giorgio Biagetti ◽  
Paolo Crippa ◽  
Laura Falaschetti ◽  
Claudio Turchetti
Keyword(s):  
Neural Network ◽  
Embedded System ◽  
Activity Recognition ◽  
Human Activity ◽  
Recurrent Neural Network ◽  
Low Cost ◽  
Low Complexity ◽  
Human Activity Recognition ◽  
Motion Artifacts ◽  
Accelerometer Data

Photoplethysmography (PPG) is a common and practical technique to detect human activity and other physiological parameters and is commonly implemented in wearable devices. However, the PPG signal is often severely corrupted by motion artifacts. The aim of this paper is to address the human activity recognition (HAR) task directly on the device, implementing a recurrent neural network (RNN) in a low cost, low power microcontroller, ensuring the required performance in terms of accuracy and low complexity. To reach this goal, (i) we first develop an RNN, which integrates PPG and tri-axial accelerometer data, where these data can be used to compensate motion artifacts in PPG in order to accurately detect human activity; (ii) then, we port the RNN to an embedded device, Cloud-JAM L4, based on an STM32 microcontroller, optimizing it to maintain an accuracy of over 95% while requiring modest computational power and memory resources. The experimental results show that such a system can be effectively implemented on a constrained-resource system, allowing the design of a fully autonomous wearable embedded system for human activity recognition and logging.

scholarly journals Vehicle Sideslip Angle Estimation Using Two Single-Antenna GPS Receivers

2010 ◽  
Author(s):  
Jong-Hwa Yoon ◽  
Huei Peng
Keyword(s):  
Low Cost ◽  
Longitudinal Velocity ◽  
Stability Control ◽  
Estimation Accuracy ◽  
Measurement Unit ◽  
Sideslip Angle ◽  
Gps Receivers ◽  
Single Antenna ◽  
Active Safety Systems ◽  
Safety Systems

Knowing vehicle sideslip angle accurately is critical for active safety systems such as Electronic Stability Control (ESC). Vehicle sideslip angle can be measured through optical speed sensors, or dual-antenna GPS. These measurement systems are costly (∼$5k to $100k), which prohibits wide adoption of such systems. This paper demonstrates that the vehicle sideslip angle can be estimated in real-time by using two low-cost single-antenna GPS receivers. Fast sampled signals from an Inertial Measurement Unit (IMU) compensate for the slow update rate of the GPS receivers through an Extended Kalman Filter (EKF). Bias errors of the IMU measurements are estimated through an EKF to improve the sideslip estimation accuracy. A key challenge of the proposed method lies in the synchronization of the two GPS receivers, which is achieved through an extrapolated update method. Analysis reveals that the estimation accuracy of the proposed method relies mainly on vehicle yaw rate and longitudinal velocity. Experimental results confirm the feasibility of the proposed method.

scholarly journals Two-Step Root-MUSIC for Direction of Arrival Estimation without EVD/SVD Computation

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Feng-Gang Yan ◽  
Shuai Liu ◽  
Jun Wang ◽  
Ming Jin
Keyword(s):  
Super Resolution ◽  
Direction Of Arrival ◽  
Doa Estimation ◽  
Low Complexity ◽  
Music Algorithm ◽  
Correlation Matrices ◽  
Noise Subspace ◽  
Using Data ◽  
Eigen Decomposition ◽  
Value Decomposition

Most popular techniques for super-resolution direction of arrival (DOA) estimation rely on an eigen-decomposition (EVD) or a singular value decomposition (SVD) computation to determine the signal/noise subspace, which is computationally expensive for real-time applications. A two-step root multiple signal classification (TS-root-MUSIC) algorithm is proposed to avoid the complex EVD/SVD computation using a uniform linear array (ULA) based on a mild assumption that the number of signals is less than half that of sensors. The ULA is divided into two subarrays, and three noise-free cross-correlation matrices are constructed using data collected by the two subarrays. A low-complexity linear operation is derived to obtain a rough noise subspace for a first-step DOA estimate. The performance is further enhanced in the second step by using the first-step result to renew the previous estimated noise subspace with a slightly increased complexity. The new technique can provide close root mean square error (RMSE) performance to root-MUSIC with reduced computational burden, which are verified by numerical simulations.

scholarly journals Low Complexity Sparse Beamspace DOA Estimation Via Single Measurement Vectors for Uniform Circular Array

2021 ◽  
Author(s):  
Di Zhao ◽  
Weijie Tan ◽  
Zhongliang Deng ◽  
Gang Li
Keyword(s):  
Optimization Problem ◽  
Signal To Noise Ratio ◽  
Estimation Method ◽  
Doa Estimation ◽  
Low Complexity ◽  
Estimation Methods ◽  
Circular Array ◽  
Single Measurement ◽  
Signal Model ◽  
Convex Optimization Problem

Abstract In this paper, we present a low complexity beamspace direction-of-arrival (DOA) estimation method for uniform circular array (UCA), which is based on the single measurement vectors (SMVs) via vectorization of sparse covariance matrix. In the proposed method, we rstly transform the signal model of UCA to that of virtual uniform linear array (ULA) in beamspace domain using the beamspace transformation (BT). Subsequently, by applying the vectorization operator on the virtual ULA-like array signal model, a new dimension-reduction array signal model consists of SMVs based on Khatri-Rao (KR) product is derived. And then, the DOA estimation is converted to the convex optimization problem. Finally, simulations are carried out to verify the eectiveness of the proposed method, the results show that without knowledge of the signal number, the proposed method not only has higher DOA resolution than subspace-based methods in low signal-to-noise ratio (SNR), but also has much lower computational complexity comparing other sparse-like DOA estimation methods.

scholarly journals A low complexity digital frequency calibration with high jitter immunity for ultra-low-power oscillators

2019 ◽  
Vol 17 ◽  
pp. 145-150
Author(s):  
Markus Scholl ◽  
Ralf Wunderlich ◽  
Stefan Heinen
Keyword(s):  
Low Power ◽  
Communication Systems ◽  
Calibration Method ◽  
Low Complexity ◽  
Frequency Stability ◽  
Wireless Communication Systems ◽  
Ultra Low Power ◽  
Wireless Transceiver ◽  
Digital Frequency ◽  
Frequency Calibration

Abstract. This paper presents a highly efficient digital frequency calibration method for ultra-low-power oscillators in wireless communication systems. This calibration method locks the ultra-low-power oscillator's output frequency to the reference clock of the wireless transceiver during its send- and receive-state to achieve frequency stability over process variation and temperature drifts. The introduced calibration scheme offers high jitter immunity and short locking periods overcoming frequency calibration errors for typical ultra-low-power oscillator's by utilizing non-linear segmented feedback levels. In measurements the proposed calibration method improves the frequency stability of an ultra-low-power 32 kHz oscillator from 53 to 10 ppm ∘C−1 over a wide temperature range for temperature drifts of less than 1 ∘C s−1 with an estimated power consumption of 185 nW while coping with relocking periods of 7 ms.

Sign in / Sign up

Export Citation Format

Share Document