Performance of Systematic RRNS Based Space-Time Block Codes with Probability-Aware Adaptive Demapping

In this paper, we propose a novel design of concatenated Space-Time Block Codes (STBCs) using Systematic Redundant Residue Number System (RRNS) codes. The link between residues and complex signal constellations is optimized by incorporating the "Direct Mapping", "Prior probability based Distance Aware Mapping" and "Indirect Mapping" schemes. We analytically quantify the upper bounds on the codeword and bit error probabilities of Systematic RRNS-STBC and characterize the achievable coding and diversity gains assuming maximum likelihood decoding (MLD). We propose an Adaptive M-ary Demapping scheme for ML decoding, which exploits the RRNS code structure to decrease complexity and provide further performance improvement over the Distance Aware Mapping scheme. It is shown that Indirect Mapping, when used for RRNS coding schemes can offer more efficient transmission and performance than naive M-ary mapping. It is also seen that Systematic RRNS-STBC codes provide superior performance compared to Non-systematic RRNS-STBC, for the same code parameters, owing to more efficient binary to residue mapping.