Collaborative research by Georgia State University, Stony Brook University, and Rutgers University
This work has been supported by the National Science Foundation (NSF) under the grant of CNS Core: Medium: Collaborative: Reality Aware Networks (CNS-1901355, 1910170, 1910133)Abstract:
This project seeks to improve the robustness of wireless sensing and networking technologies through a reality-aware wireless architecture that blends networking and sensing. Robust perception and high-bandwidth networking benefit innovations across a diverse spectrum of high-impact areas including mixed-reality, robotics, and automated vehicles. For example, the use of such techniques to enhance driver assistance systems or automated vehicles has the potential to save numerous lives. In addition to disseminating results through scholarly publication, the project will engage the wireless and automotive industry to facilitate the technology transfer. The project also includes a set of integrated education and broadening participation activities to engage and retain students from underrepresented groups through internship programs, educational and outreach activities at each participating institution.
Design and study a network architecture that can blend visual perception and wireless communication to increase overall wireless system performance;
Design low-energy, visual signaling strategies, hardware markers or ‘tags’ and communication protocols to improve wireless device lifetime;
Develop improved Simultaneous Localization and Mapping (SLAM) algorithms that blend conventional computer vision strategies with tag recognition and decoding;
Implement a reality-aware network architecture prototype that integrates the results from objectives 1-3 and lets applications address and communicate with perceived nodes;
Experimentally evaluate the reality-aware network architecture through controlled lab setups and integration with the NSF PAWR COSMOS testbed.
See the details of the project
Abstract: To achieve high-speed reception, this project combines the fast sampling nature of photodiodes and the noise isolation property of imaging array structures into a unified structure that emulates a high-speed image sensing receiver. This project designs a novel VLC receiver architecture integrating a photodiode and an LCD array that acts as a pixelated shutter. Through this unified design, the receiver selects the exact area over which the transmitted signal is detected on the array, thus isolating actual light signal from ambient noise reaching the photodiode, resulting in a dramatic increase in the Signal to Noise Ratio (SNR). The signal isolation and SNR enhancement is enabled by the spatio-temporal mechanisms for selective signal reception and tracking on the LCD array. To achieve a larger field-of-view for reception, the receiver is fit with an 180-degree panoramic lens. This project develops a model to understand the relationship between spatial mobility and the light signal's location on the array and its strength and sets a baseline for designing signal tracking mechanisms to address mobility in high-speed VLC systems.
LCD-Photodiode Receiver Design
In this work, we aim to develop a novel architecture of hybrid VLC receiver based on the unified design of integrating a photodiode and an LCD array that acts as a pixelated shutter. To identify and separate noise and interference from the desired signals, we present an automated shutter controlling algorithm (fast spatial tracking mechanism) in the receiver. In our preliminary research efforts, we have demonstrated the feasibility of our VLC receiver architecture by conducting measurements study of noise and interference identification and separation using our proposed shutter controlling algorithm. [COMSNETS’19], [PerCom’20]
Spatial Multiplexing using LCD-Photodiode Receiver
In this work, we propose, design and evaluate a novel architecture for VLC that can enable multiple-access reception using a photoreceptor receiver that uses only a single photodiode. The novel design includes a liquid-crystal-display (LCD) based shutter system that can be automated to control and enable selective reception of light beams from multiple transmitters. We evaluate the feasibility of multiple access on a single photodiode from two light emitting diode (LED) transmitters and the performance of the communication link using bit-error-rate (BER) and packet-error-rate (PER) metrics. Our experiment and trace based evaluation through proof-of-concept implementation reveals the feasibility of multiple LED reception on a single photodiode. [MDPI Journal’20]
Mobility Analysis and Open Sourcing the VLC kit
We have designed and developed a VLC kit by integrating LED transmitter on the top of a 3-wheel RaspberryPi controlled robot. This kit is open sourced and can be used as the evaluation of our prototype system (pixelated shutter controlling algorithm) across mobile environments. The complete tutorial for developing the similar kind VLC hardware Kit can be found in here.
MDPI 21 "An Empirical Study of Deep Learning Models for LED Signal Demodulation in Optical Camera Communication" Ahmed A, Trichy S, MD Rashed Rahman, Ashok A. MDPI Journal of Network. 2021; 1(3): 261-278. https://doi.org/10.3390/network1030016
IEEE TVT 21 "See-through a Vehicle: Augmenting Road Safety Information using Visual Perception and Camera Communication in Vehicles," K. Ashraf, Vignesh V, R. Walden, MD Rashed Rahman, Ashwin Ashok, in IEEE Transactions on Vehicular Technology, doi: 10.1109/TVT.2021.3066409, March 2021.
MDPI 20"Enabling Multiple Access in Visible Light Communication Using Liquid Crystal Displays: A Proof-of-Concept Study", MD Rashed Rahman, Adedara K; Ashwin Ashok, MDPI Journal of Electronics, 2020, 9, 826.
PerCom 20 “High Throughput Mobile Visible Light Communication”, MD Rashed Rahman, Ashwin Ashok, 18th Annual IEEE International Conference on Pervasive Computing and Communications PhD Forum, March 23-27, Austin, Texas, USA.
COMSNETS 19 "A Novel Architecture for Ultra-High Signal-to-Interference-Noise-Ratio in Visible Light Communication", MD Rashed Rahman, SM Towhidul Islam, Ashwin Ashok, 11th International Conference on Communications, Systems and Networks(COMSNETS), 2019.
MD Rashed Rahman: “High Throughput Mobile Visible Light Communication”, 18th Annual IEEE International Conference on Pervasive Computing and Communications PhD Forum, March 23-27, Austin, Texas, USA (Virtual Talk)
MD Rashed Rahman: "A Novel Receiver Architecture for Ultra-High Speed Visible Light Communication", Rising Stars Forum ACM MobiSys'2019, Seoul, South Korea, June 2019
MD Rashed Rahman: "A Novel Spatial Multiplexing Approach for Noise Separation in Multi-VLC System", Research Poster, CS Student Poster/Demo Day, Atlanta, USA, Apr 2019.
MD Rashed Rahman: "A Novel Architecture for High Speed VLC System", Research Poster, CS Student Poster/Demo Day, Atlanta, USA, Nov 2018. (Best Graduate Student Poster Award)
Programming Languages: MATLAB, Simulink, PSpice, GNU Radio, Python, C, OpenCV
Software Packages: Linux (Ubuntu), Latex, AutoCAD, Solid Works, Visual Studio, LabView, Minitab
Hardware Devices: USRP, Raspberry Pi, Arduino, Oscilloscope, Multimeter, Spectrum Analyzer, Function & Waveform Generator, 3D printer
Specialization areas: Optical Communication, Hardware Systems prototyping, IoT Devices, Electro-Optic Systems, Optical test-bed, Optical & Wireless Networks, MIMO, CDM, OFDM, cellular communication systems