Sample-level error-correcting code
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.
1. A first wireless communication device for wireless communication, comprising:
one or more memories; and
one or more processors, coupled to the one or more memories, configured to cause the first wireless communication device to:
receive, from a second wireless communication device, encoded data including a set of complex samples; and
decode the encoded data to obtain complex data samples based at least in part on determining complex noise samples using a subset of complex samples, from the set of complex samples, that have a function equal to a known value, and removing the complex noise samples from the set of complex samples to obtain the complex data samples, wherein the function is a sum of exponentials of the subset of complex samples.
2. The first wireless communication device of claim 1 , wherein decoding the encoded data is based at least in part on a quantity of the complex noise samples being less than or equal to half of a quantity of the subset of complex samples.
3. The first wireless communication device of claim 1 , wherein the one or more processors, to decode the encoded data, are configured to cause the first wireless communication device to:
input the subset of complex samples and the known value into a curve fitting model.
4. The first wireless communication device of claim 3 , wherein an output of the curve fitting model is the complex noise samples.
5. The first wireless communication device of claim 3 , wherein the curve fitting model is a Prony model.
6. The first wireless communication device of claim 1 , wherein the one or more processors, to decode the encoded data, are configured to cause the first wireless communication device to:
identify the subset of complex samples from an end or a start of the set of complex samples.
7. The first wireless communication device of claim 1 , wherein the subset of complex samples are redundant samples or parity samples of the encoded data.
8. A method of wireless communication performed by a first wireless communication device, comprising:
receiving, from a second wireless communication device, encoded data including a set of complex samples; and
decoding the encoded data to obtain complex data samples based at least in part on determining complex noise samples using a subset of complex samples, from the set of complex samples, that have a function equal to a known value, and removing the complex noise samples from the set of complex samples to obtain the complex data samples, wherein the function is a sum of exponentials of the subset of complex samples.
9. The method of claim 8 , wherein decoding the encoded data is based at least in part on a quantity of the complex noise samples being less than or equal to half of a quantity of the subset of complex samples.
10. The method of claim 8 , wherein decoding the encoded data comprises:
inputting the subset of complex samples and the known value into a curve fitting model.
11. The method of claim 10 , wherein an output of the curve fitting model is the complex noise samples.
12. The method of claim 10 , wherein the curve fitting model is a Prony model.
13. The method of claim 8 , wherein decoding the encoded data comprises:
identifying the subset of complex samples from an end or a start of the set of complex samples.
14. The method of claim 8 , wherein the subset of complex samples are redundant samples or parity samples of the encoded data.
15. An apparatus for wireless communication, comprising:
means for receiving, from a second wireless communication device, encoded data including a set of complex samples; and
means for decoding the encoded data to obtain complex data samples based at least in part on determining complex noise samples using a subset of complex samples, from the set of complex samples, that have a function equal to a known value, and removing the complex noise samples from the set of complex samples to obtain the complex data samples, wherein the function is a sum of exponentials of the subset of complex samples.
16. The apparatus of claim 15 , wherein decoding the encoded data is based at least in part on a quantity of the complex noise samples being less than or equal to half of a quantity of the subset of complex samples.
17. The apparatus of claim 15 , wherein the means for decoding the encoded data comprises:
means for inputting the subset of complex samples and the known value into a curve fitting model, wherein an output of the curve fitting model is the complex noise samples.
18. The apparatus of claim 17 , wherein the curve fitting model is a Prony model.
19. The apparatus of claim 15 , wherein the means for decoding the encoded data comprises:
means for identifying the subset of complex samples from an end or a start of the set of complex samples.
20. The apparatus of claim 15 , wherein the subset of complex samples are redundant samples or parity samples of the encoded data.