"This dissertation proposes three new algorithms for underwater acoustic wireless communications. One is a new tail-biting circular MAP decoder for full tail-biting convolution (FTBC) codes for very short data blocks intended for Internet of Underwater Things (IoUT). The proposed algorithm was evaluated by ocean experiments and computer simulations on both Physical (PHY) and Media access control (MAC) layers. The ocean experimental results show that without channel equalization, the full tail-biting convolution (FTBC) codes with short packet lengths not only can perform similarly to zero-tailing convolution (ZTC) codes in terms of bit error rate (BER) in the PHY layer. Computer simulation results show that the FTBC codes outperform the ZTC codes in terms of MAC layer metrics, such as collision rate and bandwidth utilization, in a massive network of battery powered IoUT devices.
Second, this dissertation also proposes a new approach to utilizing the underwater acoustic (UWA) wireless communication signals acquired in a real-world experiment as a tool for evaluating new coding and modulation schemes in realistic doubly spread UWA channels. This new approach, called passband data reuse, provides detailed procedures for testing the signals under test (SUT) that change or add error correction coding, change bit to symbol mapping (baseband modulation) schemes from a set of original experimental data"--Abstract, page iv.
Beetner, Daryl G.
Zheng, Y. Rosa
Kosbar, Kurt Louis
Moss, Randy Hays, 1953-
Electrical and Computer Engineering
Ph. D. in Electrical Engineering
Missouri University of Science and Technology
Journal article titles appearing in thesis/dissertation
- Tail-biting convolutional codes for underwater acoustic communications with short packets
- Passband data reuse of field experimental data in underwater acoustic communications
xi, 62 pages
© 2019 Mohammadhossein Behgam, All rights reserved.
Dissertation - Open Access
Electronic OCLC #
Behgam, Mohammadhossein, "Underwater acoustic communications and adaptive signal processing" (2019). Doctoral Dissertations. 2802.