Sample-Level Error-Correcting Code Using Known Complex Samples
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Solution Overview
Problem
Existing wireless communication systems face challenges in accurately transmitting and receiving complex data samples due to noise and errors introduced during transmission, which can lead to reduced communication performance and reliability.
Innovation Solution
A method for encoding complex data samples by adding time domain complex samples with a known function, such as a sum of exponentials, to the original data samples, and decoding these samples by identifying and removing noise samples based on a subset of complex samples with a known function.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If complex data samples are transmitted over wireless channels, then communication coverage and reach are improved, but noise and errors are introduced during transmission
Solution Approach 1:
The patent applies preliminary action by adding time domain complex samples with a known function (sum of exponentials) to the original data samples before transmission. This pre-processing step embeds error correction capability into the transmitted signal, enabling the receiver to identify and correct noise-induced errors without requiring retransmission, thus maintaining transmission reliability while extending communication coverage.
2Reliability
If error correction techniques are applied to complex data samples, then transmission reliability is improved, but processing complexity increases
Solution Approach 1:
The patent changes the parameter domain by working directly with time domain complex samples rather than transforming to frequency domain. The error correction is achieved by evaluating the known function (sum of exponentials) at specific time points and comparing with received samples. This parameter change simplifies the processing complexity while maintaining high transmission reliability, as it avoids complex transformations and directly operates on the transmitted signal parameters.
3Manufacturing precision
If noise samples are identified and removed from complex data samples, then manufacturing precision of the signal is improved, but measurement precision requirements increase
Solution Approach 1:
The patent implements feedback by using the known function (sum of exponentials) to generate expected values at specific time points and comparing these with the actually received samples. The difference between expected and actual values provides feedback about the presence and magnitude of noise samples. This feedback mechanism enables precise noise identification and removal while maintaining manageable measurement precision requirements, as the known function provides a reference for comparison.
Data Source
AI summary
A first wireless communication device configured to encode real samples of data to obtain encoded data based at least in part on adding one or more time domain complex samples to the real samples of the data, wherein a function of the one or more time domain complex samples is a known value, and wherein the function is a sum of exponentials of the one or more time domain complex samples. The first wireless communication device is configured to transmit, to a second wireless communication device, the encoded data.