Efficient Multicarrier Communication for Highly Spread Underwater Acoustic Channels

Abstract

Abstract-In this paper we propose a novel method for communication over underwater acoustic channels that exhibit simultaneously large delay spread and Doppler spread, such as those found in the surf zone. In particular, we propose a coded pulse-shaped multicarrier scheme that converts the doubly dispersive channel into an inter-carrier interference (ICI) channel with small ICI spread. The resulting ICI is mitigated using a soft noncoherent equalizer that leverages sparsity in the delay-power profile to generate near-optimal bit estimates with low complexity. The noncoherent equalizer uses a delay-power-profile estimate (rather than a channel estimate) which is obtained from pilots. Numerical simulations with surf-zone-like channels demonstrate performance close to genie-aided bounds.

Realization of Ofdm Based Underwater Acoustic Communication

“…In OFDM,also known as multicarrier modulation, uses multiple carriers sending some bits on each channel. InOFDM [8,17],all of the subchannels are dedicated to a data source.Multicarrier modulation especially OFDM is suitable for multipath environment as its carriers are orthogonal. As symbol period increases, the error rate is small compared with single carrier.…”

Equalization of Time-Varying Channels

“…Cui and Tellambura [CT07] applied the complex exponential (CE)-BEM, made several approximations to the noncoherent MLSD metric in (6.69) to reduce it to a simple quadratic form a H Ra (with a-independent R), and then used tree-search to find the optimal a ∈ A K , all under the assumption that A was constant modulus. Hwang and Schniter took a more direct approach, leveraging the CE-BEM to design PSP-based and channel EMB-based noncoherent MAP bit equalization algorithms in [HS08] and [HS09], respectively, whose complexities scale as O K(2D + 1) 2 I 2 . The key to these low complexities is the use of a fast metric update.…”

EM-based soft noncoherent equalization of doubly selective channels using tree search and basis expansion

“…Groups of Ns information symbols are then combined with pilot and guard symbols to form symbol blocks of length N ≥ Ns. (For brevity, we omit the details of the pilot pattern; see [17,18] …”

“…Compared to previously described literature, our approach differs principally in two regards: 1) in place of trellis techniques, we use soft tree search, and 2) in place of the Gauss-Markov model, we use a generic basis expansion model [13,14]. Our use of soft tree-search builds on recent ideas from the multiple-input multiple-output (MIMO) literature (e.g., [15,16]), yielding a flexible and efficient tradeoff between performance and complexity, and our generic BE model allows accurate modeling of many channel classes, including time-domain, frequency-domain, and sparse channels (see, e.g., [17]). Our combination of soft tree-search and BE channel modeling yields a soft noncoherent equalizer whose complexity is linear in the block length and quadratic in the number of BE coefficients.…”