Jasper Brüggmann | Searcharxiv

arXiv2026

Mixed Block Markov Superposition Transmission Codes

Block Markov superposition transmission (BMST) codes provide a flexible framework for constructing codes with near-capacity performance and low-complexity sliding-window decoding. However, existing BMST variants show contrasting performance limitations: recursive BMST (rBMST) codes suffer from error propagation but avoid high error floors, whereas non-recursive BMST codes exhibit the opposite behavior. Motivated by these complementary characteristics, we combine recursive and non-recursive components through parallel and serial concatenation, yielding mixed BMST (mBMST) codes. The proposed framework subsumes existing BMST variants and enables new BMST structures. Simulations show that these structures improve FER and BER performance with lower memory requirements than rBMST.

cs.IT↗

arXiv2024

Turbo Equalization with Coarse Quantization using the Information Bottleneck Method

This paper proposes a turbo equalizer for intersymbol interference channels (ISI) that uses coarsely quantized messages across all receiver components. Lookup tables (LUTs) carry out compression operations designed with the information bottleneck method aiming to maximize relevant mutual information. The turbo setup consists of an equalizer and a decoder that provide extrinsic information to each other over multiple turbo iterations. We develop simplified LUT structures to incorporate the decoder feedback in the equalizer with significantly reduced complexity. The proposed receiver is optimized for selected ISI channels. A conceptual hardware implementation is developed to compare the area efficiency and error correction performance. A thorough analysis reveals that LUT-based configurations with very coarse quantization can achieve higher area efficiency than conventional equalizers. Moreover, the proposed turbo setups can outperform the respective non-turbo setups regarding area efficiency and error correction capability.

cs.IT↗