Summary:
UCLA researchers in the department of Electrical and Computer Engineering have developed a probabilistic approach to decoding short-blocklength transmissions between devices, which is ideal for the noisy short-blocklength communication frequently used in Internet of Things (IoT) applications.
Background:
In telecommunication, error detection and correction (EDAC) enable the reliable delivery of digital data over unreliable communication channels. Many communication channels are subject to channel noise, and thus errors may be introduced during transmission from the source to a receiver. An example of a higher noise application that is subject to transmission errors is Internet of Things (IoT) networks, which generally rely on lower-latency, shorter communications. Different approaches to EDAC generate corresponding tradeoffs in accuracy, latency, and throughput depending on the requirements of an application. There is an ongoing need for EDAC techniques with better performance for a given application.
Innovation:
Researchers at UCLA led by Professor Rick Wesel have developed a probabilistic approach to decode short messages which is highly accurate despite the noisy nature of these communications. When compared to current approaches, this technology results in fewer mistakes when reading short, noisy messages. This proposed method could be invaluable for improving the rate and quality of communication sent on higher noise networks, such as IoT.
Potential Applications:
• Short Block Length Communication
• Information Communication
• Internet of Things
• 5G
Advantages:
• Lower Error Rate
• Highly Efficient
• Works with Short Messages
Development to Date: A simulation of the technology has been successfully demonstrated.
Reference: UCLA Case No. 2022-237
Lead Inventor: Richard Wesel