TY  - JOUR
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
IS  - 12
VL  - 17
SP  - 37
JF  - China Communications
A1  - Chen, W
A1  - Deligiannis, N
A1  - Andreopoulos, Y
A1  - Wassell, IJ
UR  - https://doi.org/10.23919/JCC.2020.12.003
TI  - On the Energy Self-Sustainability of IoT via Distributed Compressed Sensing
EP  - 51
AV  - public
Y1  - 2020/12//
KW  - Distributed compressed sensing
KW  -  energy harvesting
KW  -  internet of things
KW  -  energy self-sustainability.
ID  - discovery10120991
N2  - This paper advocates the use of the distributed compressed sensing (DCS) paradigm to deploy energy harvesting (EH) Internet of Thing (IoT) devices for energy self-sustainability. We consider networks with signal/energy models that capture the fact that both the collected signals and the harvested energy of different devices can exhibit correlation. We provide theoretical analysis on the performance of both the classical compressive sensing (CS) approach and the proposed distributed CS (DCS)-based approach to data acquisition for EH IoT. Moreover, we perform an in-depth comparison of the proposed DCS- based approach against the distributed source coding (DSC) system. These performance characterizations and comparisons embody the effect of various system phenomena and parameters including signal correlation, EH correlation, network size, and energy availability level. Our results unveil that, the proposed approach offers significant increase in data gathering capability with respect to the CS-based approach, and offers a substantial reduction of the mean-squared error distortion with respect to the DSC system.
PB  - CHINA INST COMMUNICATIONS
ER  -