6 papers
An Information-Theoretic Efficient Capacity Region for Multi-User Interference Channel
Sagnik Bhattacharya, Abhiram Rao Gorle, Muhammad Ali Mohsin +1
We investigate the capacity region of multi-user interference channels (IC), where each user encodes multiple sub-user components. By unifying chain-rule decomposition with the Ent…
Task and Perception-aware Distributed Source Coding for Correlated Speech under Bandwidth-constrained Channels
Sagnik Bhattacharya, Muhammad Ahmed Mohsin, Ahsan Bilal +1
Emerging wireless AR/VR applications require real-time transmission of correlated high-fidelity speech from multiple resource-constrained devices over unreliable, bandwidth-limited…
Optimum Power Allocation for Low Rank Wi-Fi Channels: A Comparison with Deep RL Framework
Muhammad Ahmed Mohsin, Sagnik Bhattacharya, Kamyar Rajabalifardi +2
Upcoming Augmented Reality (AR) and Virtual Reality (VR) systems require high data rates ( 500 Mbps) and low power consumption for seamless experience. With an increasing num…
Optimum Power-Subcarrier Allocation and Time-Sharing in Multicarrier NOMA Uplink
Sagnik Bhattacharya, Kamyar Rajabalifardi, Muhammad Ahmed Mohsin +1
Currently used resource allocation methods for uplink multicarrier non-orthogonal multiple access (MC-NOMA) systems have multiple shortcomings. Current approaches either allocate t…
Successive Interference Cancellation-aided Diffusion Models for Joint Channel Estimation and Data Detection in Low Rank Channel Scenarios
Sagnik Bhattacharya, Muhammad Ahmed Mohsin, Kamyar Rajabalifardi +1
This paper proposes a novel joint channel-estimation and source-detection algorithm using successive interference cancellation (SIC)-aided generative score-based diffusion models.…
Hierarchical Deep Reinforcement Learning for Adaptive Resource Management in Integrated Terrestrial and Non-Terrestrial Networks
Muhammad Ahmed Mohsin, Hassan Rizwan, Muhammad Umer +3
Efficient spectrum allocation has become crucial as the surge in wireless-connected devices demands seamless support for more users and applications, a trend expected to grow with…