259 citations · 1.2k across the 111 of their papers we have counts for
42 papers · 1 filter
Deep-OFDM: Neural Modulation for High Mobility
S. Ashwin Hebbar, Sravan Kumar Ankireddy, Harshithanjani Athi +3
Orthogonal Frequency Division Multiplexing (OFDM) is the dominant waveform in modern wireless systems, but suffers performance degradation in high-mobility environments due to Dopp…
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning
S Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim +2
Progress in designing channel codes has been driven by human ingenuity and, fittingly, has been sporadic. Polar codes, developed on the foundation of Arikan's polarization kernel,…
Compressed Error HARQ: Feedback Communication on Noise-Asymmetric Channels
Sravan Kumar Ankireddy, S. Ashwin Hebbar, Yihan Jiang +2
In modern communication systems with feedback, there are increasingly more scenarios where the transmitter has much less power than the receiver (e.g., medical implant devices), wh…
Machine Learning-Aided Efficient Decoding of Reed-Muller Subcodes
Mohammad Vahid Jamali, Xiyang Liu, Ashok Vardhan Makkuva +3
Reed-Muller (RM) codes achieve the capacity of general binary-input memoryless symmetric channels and are conjectured to have a comparable performance to that of random codes in te…
CRISP: Curriculum based Sequential Neural Decoders for Polar Code Family
S Ashwin Hebbar, Viraj Nadkarni, Ashok Vardhan Makkuva +3
Polar codes are widely used state-of-the-art codes for reliable communication that have recently been included in the 5th generation wireless standards (5G). However, there remains…
TinyTurbo: Efficient Turbo Decoders on Edge
S Ashwin Hebbar, Rajesh K Mishra, Sravan Kumar Ankireddy +3
In this paper, we introduce a neural-augmented decoder for Turbo codes called TINYTURBO . TINYTURBO has complexity comparable to the classical max-log-MAP algorithm but has much be…