Graph-Based Detection and LDPC Decoding over 2D Intersymbol Interference Channels

In this paper, we propose a fully graph-based iterative detection and decoding scheme for Low-Density Parity-Check (LDPC) coded generalized two-dimensional (2D) intersymbol interference (ISI) channels. The 2D detector consists of a downtrack detector based on the symbol-level sum-product algorithm (SPA) and a bit-level SPA-based crosstrack detector. A LDPC decoder based on simplified check node operations is also proposed to provide soft information for the 2D channel detector. Numerical results show that the proposed receiver achieves better performance as compared with the trellis-based BCJR detector over 2×2 2D channels while at a significantly lower computational complexity.

Application of Diversity Combining with RLS Adaptive Filtering in Data Transmission in a Hydroacoustic Channel

When transmitting data in a hydroacoustic channel under difficult propagation conditions, one of the problems is intersymbol interference (ISI) caused mainly by the effect of multipath propagation. This phenomenon leads to a decrease in transmission parameters, and sometimes completely prevents it. Therefore, we have made an attempt to use diversity combining with Recursive Least Squares (RLS) adaptive filtering to improve the quality of data transmission in a hydroacoustic channel with strong reflections. The method was tested in simulation and during measurements in a real environment. The influence of the method on data transmission in the hydroacoustic channel was examined in detail. The obtained results allow us to draw conclusions regarding the purposefulness of use of diversity combining and RLS adaptive filtering in order to improve the quality of data transmission by reducing the effect of ISI.