Bit Interleaving for Autoencoder Communications
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Solution Overview
Problem
Current wireless communication systems face challenges in optimizing bit interleaving for bitwise autoencoder based communications, particularly in adapting to varying channel conditions and ensuring reliable data transmission due to unequal error protection levels across bit positions in modulation constellations learned by bitwise autoencoders.
Innovation Solution
A wireless communication device trains a bitwise autoencoder neural network to obtain a constellation mapping and determines a bit position ordering based on error protection levels, performing bit interleaving to prioritize more important bits in higher error protection positions, thereby ensuring reliable data transmission and adapting to changing channel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bit interleaving is performed without considering error protection levels, then the complexity of the communication system is reduced, but the reliability of data transmission deteriorates due to unequal error protection across bit positions
Solution Approach 1:
The system performs preliminary analysis of error protection levels for each bit position in the modulation constellation before executing bit interleaving. The transmitter determines the error protection level of each bit position based on the learned constellation mapping, then uses this information to guide the interleaving process. This preliminary assessment ensures that important bits are mapped to positions with higher error protection before transmission begins.
Solution Approach 2:
The system dynamically adjusts the bit interleaving pattern based on the error protection levels derived from the constellation mapping. By changing the mapping parameters according to the specific error protection characteristics of each bit position, the system optimizes transmission reliability without requiring a completely complex new architecture. The interleaving pattern adapts to the parameters revealed by the autoencoder's learned constellation.
2Adaptability or versatility
If a fixed constellation mapping is used, then the device complexity is reduced, but the adaptability to varying channel conditions deteriorates
Solution Approach 1:
The system employs a bitwise autoencoder neural network that dynamically learns and adapts the constellation mapping based on current channel conditions. Rather than using a static, fixed constellation, the autoencoder continuously optimizes the mapping between coded bits and modulated symbols to match the prevailing channel characteristics. This dynamic adaptation allows the system to respond to varying channel conditions while maintaining manageable complexity through the use of neural network-based learning.
Data Source
AI summary
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a wireless communication device (WCD) may train a bitwise autoencoder neural network to obtain a constellation mapping. The WCD may determine a bit position ordering for bit positions of modulated symbols associated with the constellation mapping based at least in part on error protection levels of bit positions associated with the constellation mapping. The WCD may perform bit interleaving for one or more coded bits of a communication, based at least in part on the bit position ordering of the constellation mapping, to obtain one or more interleaved bits. The WCD may generate one or more modulated symbols for the communication by mapping the one or more interleaved bits using the constellation mapping. The WCD may transmit, to a receiver device, the one or more modulated symbols for the communication. Numerous other aspects are described.