The design, operation, and capabilities of a workstation-communications-simulation software system (WCS) for interactive simulation of point-to-point digital communication links is described. The system is based on Fortran-77 and is hosted on an IBM PC/AT or compatible microcomputer. At the heart of the system is a single-board floating-point array processor that provide approximately three orders of magnitude increase in computational throughput over operations performed in the AT alone. A description is given of how a unique method of interfacing to a PC host allows considerable flexibility in partitioning a simulation problem for execution on an attached processor. The WCS system is a highly graphics-oriented system using the latest advances in interactive color workstation technology.>

In this paper we describe efforts to develop a comprehensive tool for the digital simulation of a wide variety of point-to-point digital communication systems. These efforts have resulted in the interactive communications simulator (ICS); a flexible, graphics-oriented, and highly interactive hardware/software system consisting of a typical minicomputer acting as host to a fast peripheral array processor. This system is presently being employed both to evaluate existing modem performance and to explore new modulation/coding concepts appropriate for military, commercial, and space applications. A detailed functional description of the ICS is provided together with pertinent software considerations. An outline of existing ICS capabilities is presented and illustrated through typical, graphical output. A thorough discussion of channel modeling considerations is provided. The use of the ICS in the overall design of receiver structures for impulsive noise channels will be illustrated.

Algorithms for the soft-decision decoding of linear block codes are presented. These algorithms perform a reduced complexity search through a trellis derived from the parity check matrix of an(n, k)linear block code. The computational complexity of the algorithms is considerably reduced from that of a full maximum-likelihood algorithm. We demonstrate the trade-off between complexity and efficiency of the algorithms through computer simulation.