Advisory Committee Chair
Mohammad R Haider
Advisory Committee Members
Leon Jololian
Karthikeyan Lingasubramanian
Aleksandar Milenkovic
A Abdollah Mirbozorgi
Nasim Uddin
Document Type
Dissertation
Date of Award
2022
Degree Name by School
Doctor of Philosophy (PhD) School of Engineering
Abstract
Spectrum-efficient data telemetry is critically important in high-density wireless sensor networks. The rapid expansion of the sensor network has generated a large volume of data on the limited bandwidth and brought new challenges, including transmission bottlenecks, latency, and congestion. The existing wireless technologies cannot support the proliferation of sensor devices for the limitations of spectrum and resources, including computational power, memory, and feature size that hinder the deployment of sophisticated signal processing. To overcome these limitations, orthogonal pulse-based telemetry provides an excellent alternative with reduced complexity, data compression, and efficient transmission. However, the number of data channels also limits the single pulse system to support high-density IoT networks. This dissertation work proposes two innovative encoding schemes to address the above challenges. The first scheme encodes multi-bit data using index randomization, where a single-order pulse carries multi-bit data. The second scheme encodes individual data channels by a distinct pulse-sequence (PS) instead of a single pulse, where the permutation of a group of higher-order pulses in adjacent time slots creates a series of PSs. The superposition of the PSs creates a unified composite sequence and a compressed data representation of the encoded channels. At the receiver end, a cyclic pulse elimination algorithm decodes individual pulses from the combined signal. This dissertation also presents orthogonal PS generation to simplify the pulse decoding iv scheme for finding the missing channel. Finally, a prototype test platform is configured to validate the proposed scheme's performance, feasibility, and compatibility using the channel effect investigations, existing bandwidth, communication architecture, and network protocol. Simulation results show that index randomization increases the data compression ratio, improves processing time, and adds an extra level of physical layer security. Test results show that the BER satisfies the lower bound for wireless telemetry and increases data transmission speed by supporting large number of channels. The proposed scheme is also different than the IFFT-based Walsh-Hadamard orthogonal code generation for wireless communication. In addition, the orthogonal pulse-based compression is free from sophisticated signal processing. The simplicity and efficacy show enormous potentials to meet the demand for next-generation high-density IoT networks using existing bandwidth and communication architecture.
Recommended Citation
Hossain, Md. Kamal, "Spectrum-Efficient High-Density Data Communication for Wireless Sensor Networks" (2022). All ETDs from UAB. 196.
https://digitalcommons.library.uab.edu/etd-collection/196