Construction of observable and MDP convolutional codes with good decodable properties by ISO representations

Key Points

• The aim is to construct observable and maximum distance profile convolutional codes that perform well with decoding algorithms.
• Utilized input/state/output representations to guide code construction.
• Exploited the invariance of properties under group actions for systematic code generation.
• Generated new convolutional codes from existing codes while maintaining key properties.
• Constructed convolutional codes showed improved decoding capabilities.
• New codes maintained desirable distance properties for reliability in decoding.

Abstract