Summary:
UCLA researchers have developed a parallel list decoding algorithm to rapidly improve wireless communication data processing.
Reference:
Dual List Decoding (Case No. 2024-172)
Background:
Convolutional codes (CCs) are used extensively in wireless communication systems to improve data transmission reliability over noisy signals. During transmission, data is combined using generator polynomials to produce an encoded output sequence, including redundant segments to assist with error detection at the receiver. The Viterbi Algorithm is commonly used to decode these received CCs into understandable and interpretable data. However, the Viterbi Algorithm's complexity increases exponentially with the length of the redundant segments, making it challenging to balance error detection and high-speed signal processing. Therefore, new decoding algorithms are needed to enhance both error detection and processing speed.
Innovation:
Researchers in the Department of Electrical and Computer Engineering have developed a novel decoding algorithm that significantly reduces complexity compared to the standard Viterbi Algorithm. This innovation involves decomposing the CC into two shorter component codes by factoring the original polynomial. By decoding these two lists in parallel, rather than sequentially, the researchers have achieved a tenfold reduction in complexity. This novel approach not only enhances wireless communication efficiency but also has numerous potential applications.
Potential Applications:
• Mobile and cellular networking
• Satellite communications
• High-speed financial trading systems
• Autonomous vehicles
• Healthcare/telemedicine
• Consumer electronics and IoT
• Defense, military and emergency services
Advantages:
• Increased signal decoding throughput
• Reduced latency
• Improved error correction
Development-To-Date:
Researchers have validated the algorithm with a 10x improvement in data processing speed.
Lead Inventor:
Professor Richard Wesel, PhD, Department of Electrical and Computer Engineering