9 citations · 12 across the 5 of their papers we have counts for
6 papers
Reinforcement Learning Based Goodput Maximization with Quantized Feedback in URLLC
Hasan Basri Celebi, Mikael Skoglund
This paper presents a comprehensive system model for goodput maximization with quantized feedback in Ultra-Reliable Low-Latency Communication (URLLC), focusing on dynamic channel c…
Goodput Maximization with Quantized Feedback in the Finite Blocklength Regime for Quasi-Static Channels
Hasan Basri Celebi, Mikael Skoglund
In this paper, we study a quantized feedback scheme to maximize the goodput of a finite blocklength communication scenario over a quasi-static fading channel. It is assumed that th…
A Learning-Based Approach to Address Complexity-Reliability Tradeoff in OS Decoders
Baptiste Cavarec, Hasan Basri Celebi, Mats Bengtsson +1
In this paper, we study the tradeoffs between complexity and reliability for decoding large linear block codes. We show that using artificial neural networks to predict the require…
A Multi-Objective Optimization Framework for URLLC with Decoding Complexity Constraints
Hasan Basri Celebi, Antonios Pitarokoilis, Mikael Skoglund
Stringent constraints on both reliability and latency must be guaranteed in ultra-reliable low-latency communication (URLLC). To fulfill these constraints with computationally cons…
Latency and Reliability Trade-off with Computational Complexity Constraints: OS Decoders and Generalizations
Hasan Basri Celebi, Antonios Pitarokoilis, Mikael Skoglund
In this paper, we study the problem of latency and reliability trade-off in ultra-reliable low-latency communication (URLLC) in the presence of decoding complexity constraints. We…
Low-Latency Communication with Computational Complexity Constraints
Hasan Basri Celebi, Antonios Pitarokoilis, Mikael Skoglund
Low-latency communication is one of the most important application scenarios in next-generation wireless networks. Often in communication-theoretic studies latency is defined as th…