6 papers
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…
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…
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…
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…
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…
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…