3 papers
cs.IT2026
Neural Equalisers for Highly Compressed Faster-than-Nyquist Signalling: Design, Performance, Complexity and Robustness
Shubham Paul, Sheetal Kalyani, Nambi Sheshadri +1
Faster-than-Nyquist (FTN) signalling has emerged as a compelling technique for enhancing spectral efficiency in bandwidth-constrained communication systems. By intentionally introd…
cs.IT2024
Learning Robust Representations for Communications over Interference-limited Channels
Shubham Paul, Sudharsan Senthil, Preethi Seshadri +2
In the context of cellular networks, users located at the periphery of cells are particularly vulnerable to substantial interference from neighbouring cells, which can be represent…
cs.LG2024
Learning Robust Representations for Communications over Noisy Channels
Sudharsan Senthil, Shubham Paul, Nambi Seshadri +1
We explore the use of FCNNs (Fully Connected Neural Networks) for designing end-to-end communication systems without taking any inspiration from existing classical communications m…