Multichannel Equalization by Decision-Directed Passive Phase Conjugation: Experimental Results

Acoustic Communication Using Time-Reversal Signal Processing: Spatial and Frequency Diversity

“…Our approach is to use the results from broadband experiments to predict performance at reduced bandwidths. The mathematical details [17] are beyond the scope of the present short communication; here, we merely sketch how these data-driven simulations are performed and present numerical results.…”

Passive Time Reversal Acoustic Communications Through Shallow-Water Internal Waves

“…To deal with the channel fluctuation in the presence of internal waves, we propose to update the channel estimates regularly within a data packet at time intervals of . Note that time reversal combining alone with frequent channel updates has been discussed for high frequencies [25]. Joint time reversal combining and multichannel equalization have been considered for moving platforms [26].…”

Joint Passive Time Reversal and Multichannel Equalization for Underwater Communications

“…If done properly, this has the added benefit of reducing the additive noise component in the probe estimate h m (t), which generates undesirable convolutional noise during focusing according to (2). A similar idea was taken one step further in [7] and termed decision-directed passive phase conjugation (DDPPC). In DDPPC the channel is tracked throughout the data packet, using as reference either a known preamble (training sequence) or previous symbol decisions (decision-directed mode).…”

“…While [7] argues in favor of iterative block least-squares estimation, in this work we adopt the exponentially-windowed RLS algorithm for channel tracking, which has been extensively used as a tool in underwater channel equalization and identification.…”

“…Surprisingly, there is no clear dependency between output MSE and Doppler shift in the original data. c) Multichannel Combining: Table II provides MSE values for joint time reversal using estimated probes and the simplified MC algorithms of Section III, as well as the DDPPC approach of [7] with impulse response snapshots taken every 10 symbol intervals. All PLL loop filters used the same feedback gain K = 0.05.…”