activity
20222026
most citedTinyTurbo: Efficient Turbo Decoders on Edge

16 citations · 33 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Dynamic Tokenization via Reinforcement Patching: End-to-end Training and Zero-shot Transfer

Yulun Wu, Sravan Kumar Ankireddy, Samuel Sharpe +4

Efficiently aggregating spatial or temporal horizons to acquire compact representations has become a unifying principle in modern deep learning models, yet learning data-adaptive r…

cs.AI2026

TimeSqueeze: Dynamic Patching for Efficient Time Series Forecasting

Sravan Kumar Ankireddy, Nikita Seleznev, Nam H. Nguyen +4

Transformer-based time series foundation models face a fundamental trade-off in choice of tokenization: point-wise embeddings preserve temporal fidelity but scale poorly with seque…

cs.IT2025

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…

cs.IT2025

Residual Diffusion Models for Variable-Rate Joint Source Channel Coding of MIMO CSI

Sravan Kumar Ankireddy, Heasung Kim, Joonyoung Cho +1

Despite significant advancements in deep learning based CSI compression, some key limitations remain unaddressed. Current approaches predominantly treat CSI compression as a source…

cs.CV2024★ 3 cited

Exploring Explainability in Video Action Recognition

Avinab Saha, Shashank Gupta, Sravan Kumar Ankireddy +2

Image Classification and Video Action Recognition are perhaps the two most foundational tasks in computer vision. Consequently, explaining the inner workings of trained deep neural…

cs.IT2024★ 12 cited

LightCode: Light Analytical and Neural Codes for Channels with Feedback

Sravan Kumar Ankireddy, Krishna Narayanan, Hyeji Kim

The design of reliable and efficient codes for channels with feedback remains a longstanding challenge in communication theory. While significant improvements have been achieved by…

cs.IT2024★ 2 cited

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,…

cs.IT2024

Nested Construction of Polar Codes via Transformers

Sravan Kumar Ankireddy, S Ashwin Hebbar, Heping Wan +2

Tailoring polar code construction for decoding algorithms beyond successive cancellation has remained a topic of significant interest in the field. However, despite the inherent ne…

cs.LG2023

Learning RL-Policies for Joint Beamforming Without Exploration: A Batch Constrained Off-Policy Approach

Heasung Kim, Sravan Kumar Ankireddy

In this work, we consider the problem of network parameter optimization for rate maximization. We frame this as a joint optimization problem of power control, beam forming, and int…

cs.IT2023

Task-aware Distributed Source Coding under Dynamic Bandwidth

Po-han Li, Sravan Kumar Ankireddy, Ruihan Zhao +5

Efficient compression of correlated data is essential to minimize communication overload in multi-sensor networks. In such networks, each sensor independently compresses the data a…

cs.IT2023

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…

cs.IT2022★ 16 cited

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…