By Super User
Towards cross-layer security for underwater acoustic networks. Pelekanakis, Konstantinos; Petroccia, Roberto; Cassarà, Pietro; Alves, João. CMRE-FR-2018-008. June 2020.
This work deals with adaptive Underwater Acoustic communications where the modem must operate at very low Signal-to-Noise Ratios (SNRs) to protect the link from a potential eavesdropping attack. The proposed modem is equipped with seven Direct Sequence Spread Spectrum signals of various coding rates and modulation orders. A multi-band Channel estimate-based Decision Feedback Equalizer is used at the receiver. We address the challenge of achieving high spectral efficiency subject to a combination of Bit- Error Rate (BER) and SNR constraints. To this end, adaptive selection of signals is achieved based on their BER prediction via boosted trees. This ensemble of trees learns directly from the received data and relates the BER with signal characteristics and channel metrics. The efficiency of the boosted trees is validated by post-processing thousands of acoustic signals recorded in the Gulf of La Spezia, Italy. More than ten times faster communications as compared to a modem with a fixed rate transmission is achieved. In addition, Mixed Integer Linear Programming and Cross-Entropy centralised algorithms are explored to optimise the selection of the modulation scheme and transmission power to use when considering metrics such as throughput, energy consumption, reduction of SNR at the receiver (or transmission power at the transmitter) for covert communications. Our analysis show that each transmitting node should adapt the modulation scheme and transmission power according to the selected optimisation metrics, posing the base for distributed and secure adaptive strategies.