75 citations · 150 across the 8 of their papers we have counts for
9 papers
A Universal Systematic Method to Generate Error Patterns on Memoryless Channels
Marwan Jalaleddine, Jiajie Li, Syed Mohsin Abbas +1
The high computational cost of approaching the performance of Maximum-likelihood (ML) decoding has limited its practical use for decades. Because the complexity grows exponentially…
Enabling Fast Polar SC Decoding with IR-HARQ
Marwan Jalaleddine, Mohamad Ali Jarkas, Jiajie Li +1
To extend the applications of polar codes within next-generation wireless communication systems, it is essential to incorporate support for Incremental Redundancy (IR) Hybrid Autom…
Hardware-friendly IR-HARQ for Polar SCL Decoders
Marwan Jalaleddine, Jiajie Li, Warren J. Gross
To extend the applications of polar codes within next-generation wireless communication systems, it is essential to incorporate support for Incremental Redundancy (IR) Hybrid Autom…
Step-GRAND: A Low Latency Universal Soft-input Decoder
Syed Mohsin Abbas, Marwan Jalaleddine, Chi-Ying Tsui +1
GRAND features both soft-input and hard-input variants that are well suited to efficient hardware implementations that can be characterized with achievable average and worst-case d…
GRAND for Rayleigh Fading Channels
Syed Mohsin Abbas, Marwan Jalaleddine, Warren J. Gross
Guessing Random Additive Noise Decoding (GRAND) is a code-agnostic decoding technique for short-length and high-rate channel codes. GRAND tries to guess the channel noise by genera…
High-Throughput and Energy-Efficient VLSI Architecture for Ordered Reliability Bits GRAND
Syed Mohsin Abbas, Thibaud Tonnellier, Furkan Ercan +2
Ultra-reliable low-latency communication (URLLC), a major 5G New-Radio use case, is the key enabler for applications with strict reliability and latency requirements. These applica…
List-GRAND: A practical way to achieve Maximum Likelihood Decoding
Syed Mohsin Abbas, Marwan Jalaleddine, Warren J. Gross
Guessing Random Additive Noise Decoding (GRAND) is a recently proposed universal Maximum Likelihood (ML) decoder for short-length and high-rate linear block-codes. Soft-GRAND (SGRA…
High-Throughput VLSI Architecture for GRAND Markov Order
Syed Mohsin Abbas, Marwan Jalaleddine, Warren J. Gross
Guessing Random Additive Noise Decoding (GRAND) is a recently proposed Maximum Likelihood (ML) decoding technique. Irrespective of the structure of the error correcting code, GRAND…
High-Throughput VLSI architecture for Soft-Decision decoding with ORBGRAND
Syed Mohsin Abbas, Thibaud Tonnellier, Furkan Ercan +2
Guessing Random Additive Noise Decoding (GRAND) is a recently proposed approximate Maximum Likelihood (ML) decoding technique that can decode any linear error-correcting block code…