submitted to PO: Adapting Underwater Acoustic Communication Networks to Changing Oceanic Conditions Using Opportunistic Signaling Schemes and Morphological Signal Processing
Abstract
The over-arching technical objective of this project is to develop signal processing techniques and communication and node placement protocols for shallow water acoustic communication networks that are cognizant of changing oceanic conditions. Shallow water acoustics, particularly under moderate to rough sea conditions, poses very different interference models (and related challenges) than encountered in electromagnetic wireless medium such as in radio-frequency (RF), optical or millimeter wave communications. In this project we meet the grand challenge of mitigating unpredictable, rapidly shifting, persistent and prolonged delay spread due to acoustic scattering phenomena by developing a suite of physics-cognizant computational techniques that track and leverage oceanic phenomena opportunistically. We also develop adaptive node placement techniques based on graph-clustering methods that are multipath-aware in real time and therefore, implicitly account for the non-R2 propagation loss in underwater acoustics. Technical objectives: (i) Track channel sparsity and multipath activity in real-time using a suite of mixed norm optimization and morphological signal processing techniques; (ii) Develop opportunistic signaling schemes that exploit channel multipath locally to bolster reliable communication between nodes; (iii) Combine physical layer detection at the node-level with graph clustering techniques at the multinode level to achieve optimum node placement. The proposed project will advance the current knowledge of underwater acoustic communications across the physical and network layers in three major ways: (i) We will connect physics-cognizant raytracing acoustic propagation models (e.g. Bellhop) with ray-agnostic multi-scale statistical models of the underwater acoustic channel impulse response. We will achieve this by mapping individual ray clusters onto multipath bands along the channel support using sparse recovery and morphological signal processing methods; (ii) We will enhance cross-layer signaling architecture of shallow water acoustic communication networks by leveraging natural channel gains due to oceanic phenomena such as caustics and surface wave focusing events. We will achieve this by designing adaptive and opportunistic fullduplex signaling schemes that will seek to maximize local throughput and by induction, overall network capacity; (iii) We will enable adaptive and cooperative node placement techniques based on graphclustering methods that are multipath-aware in real time and therefore, implicitly account for the non-R2 propagation loss in underwater acoustics. In synopsis, the proposed effort will build upon the existing foundations of shallow water acoustics, communication networks and signal processing to create novel cross-layer computational techniques that will enhance the current state of the art in underwater acoustic communications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jul 20, 2020
- Source ID
- N000142012626
Entities
People
- Ananya Sen Gupta
Organizations
- Office of Naval Research
- United States Navy
- University of Iowa