Related papers: Rich-ARQ: From 1-bit Acknowledgment to Rich Neural…
In this paper, we address the discrete-time average consensus problem in strongly connected directed graphs, where nodes exchange information over unreliable error-prone communication links. We enhance the Robustified Ratio Consensus…
Deep learning methods have recently been used to construct non-linear codes for the additive white Gaussian noise (AWGN) channel with feedback. However, there is limited understanding of how these black-box-like codes with many learned…
We consider the $N$-user broadcast erasure channel with $N$ unicast sessions (one for each user) where receiver feedback is regularly sent to the transmitter in the form of ACK/NACK messages. We first provide a generic outer bound to the…
In this work, we investigate proactive Hybrid Automatic Repeat reQuest (HARQ) using link-level simulations for multiple packet sizes, modulation orders, BLock Error Rate (BLER) targets and two delay budgets of 1 ms and 2 ms, in the context…
A new random linear network coding scheme for reliable communications for time division duplexing channels is proposed. The setup assumes a packet erasure channel and that nodes cannot transmit and receive information simultaneously. The…
In Collaborative Intelligence (CI), the Artificial Intelligence (AI) model is divided between the edge and the cloud, with intermediate features being sent from the edge to the cloud for inference. Several deep learning-based Semantic…
Hybrid Automatic Repeat Request (HARQ) schemes typically allocate all available resources to retransmit failed packets to ensure reliability. However, under stringent delay constraints, these schemes often exhibit low spectral efficiency…
In this paper, we consider a class of wireless powered communication devices using hybrid automatic repeat request (HARQ) protocol to ensure reliable communications. In particular, we analyze the trade-off between accumulating mutual…
A status updating system is considered in which a variable length code is used to transmit messages to a receiver over a noisy channel. The goal is to optimize the codewords lengths such that successfully-decoded messages are timely. That…
Large Language Models (LLMs) are scaling rapidly, creating significant challenges for collaborative server client distributed training, particularly in terms of communication efficiency and computational overheads. To address these…
Deep learning has enabled significant advances in feedback-based channel coding, yet existing learned schemes remain fundamentally limited: they employ fixed block lengths, suffer degraded performance at high rates, and cannot fully exploit…
Exploiting fine-grained correspondence and visual-semantic alignments has shown great potential in image-text matching. Generally, recent approaches first employ a cross-modal attention unit to capture latent region-word interactions, and…
This paper studies the wireless spectrum sharing between a pair of distributed primary radio (PR) and cognitive radio (CR) links. Assuming that the PR link adapts its transmit power and/or rate upon receiving an interference signal from the…
In this paper, the effective capacity of cooperative communication (CC) systems with hybrid Automatic repeat request (HARQ) is derived. The derived expressions are valid for any channel distribution and with any arbitrary number of…
This paper discusses a new channel model and code design for the reader-to-tag channel in near-field passive radio frequency identification (RFID) systems using inductive coupling as a power transfer mechanism. If the receiver…
This paper presents a unified modeling, estimation, and feedback framework for reconfigurable intelligent surface RIS-assisted optical wireless links. The key modeling element is a long-exposure pixel gain that extends the classical…
A random access code (RAC) is a communication task in which the sender encodes a random message into a shorter one to be decoded by the receiver so that a randomly chosen character of the original message is recovered with some probability.…
The design of codes for feedback-enabled communications has been a long-standing open problem. Recent research on non-linear, deep learning-based coding schemes have demonstrated significant improvements in communication reliability over…
Neural audio codec (NAC) is essential for reconstructing high-quality speech signals and generating discrete representations for downstream speech language models. However, ensuring accurate semantic modeling while maintaining high-fidelity…
This paper proposes a reinforcement learning (RL)-aided cognitive framework for massive MIMO-based integrated sensing and communication (ISAC) systems employing a uniform planar array (UPA). The focus is on enhancing radar sensing…