Truncated Convolutional Codes as a New Approach of Unequal Error Protection

In a wireless networked control system (WNCS), physical processes are periodically observed and corresponding single analog measurements are digitized by scalar quantizers. Subsequently, these data are transmitted via a digital wireless communication system. A new source/channel coding scheme is presented that achieves a very low mean square error (MSE) of the analog physical values when they are transmitted over a noisy channel. The use of a quantizer with natural binary code (NBC) labeling is proposed and it is shown that a certain class of linear unequal error protection (LUEP) block codes which are obtained from convolutional codes by direct truncation (DT) termination, matches the source characteristics of this kind of quantizer and leads to a low MSE. The LUEP capabilities of such codes are examined and simulation results are presented that show that such codes outperform standard block codes as well as Ma´s generalized tail-biting (GTB) codes. Additionally, we provide examples where convolutional encoded quantizer outputs also show superior performance compared to redundant index assignments which are obtained from spread s snake-in-the-box (SIB) codes. Furthermore, by means of a special class of time-varying convolutional codes, we develop a method for the bitwise adjustment of the protection levels of an LUEP block code, which may be used to adapt the code to the channel.