Convolutional Coding for PPM-BPSK Dibit Distance Optimization
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Solution Overview
Problem
Conventional convolutional codes designed for BPSK mapping exhibit worse performance when used with combined PPM and BPSK schemes, as the distance properties of dibits change, leading to reduced error correction capabilities.
Innovation Solution
Searching for new generator pairs that optimize the dibit distance properties for combined PPM and BPSK systems, resulting in systematic codes that maintain performance comparable to optimal BPSK codes, with one generator determining the signal position and the other the sign, allowing non-coherent receivers to decode directly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional convolutional codes designed for BPSK mapping are used with combined PPM and BPSK schemes, then the system can support both non-coherent and coherent receivers, but the error correction performance deteriorates due to changed dibit distance properties
Solution Approach 1:
The patent changes the generator parameters of the convolutional code to optimize dibit distance properties for combined PPM/BPSK modulation. Specifically, new generator pairs are selected that maximize the minimum distance between valid dibit sequences, thereby improving error correction performance while maintaining compatibility with both non-coherent and coherent receivers.
Solution Approach 2:
The patent performs preliminary optimization of the convolutional code generators before transmission, specifically designing the code structure to account for the combined PPM/BPSK modulation scheme's distance properties. This preliminary design ensures that the code is pre-adapted to the modulation characteristics, preventing performance degradation.
2Reliability
If new generator pairs are designed to optimize dibit distance for combined PPM/BPSK, then error correction performance improves, but code complexity increases
Solution Approach 1:
The patent optimizes specific parameters of the convolutional code generators (the tap positions and connections in the shift register) to achieve better dibit distance properties. By carefully selecting which stages of the shift register are XORed together to produce each output bit, the code achieves improved error correction while maintaining a practical implementation structure.
Data Source
AI summary
A method and apparatus for transmitting and receiving convolutionally coded data in a communication system employing a combination of Pulse Position Modulation (PPM) and Binary Phase Shift Keying (BPSK), wherein the code is selected to have error rate performance that is as good as the best convolutional code used with systems employing only BPSK.