View source for 18575419. A Radio Receiver with an Iterative Neural Network, and Related Methods and Computer Programs simplified abstract (Nokia Solutions and Networks Oy)

=A Radio Receiver with an Iterative Neural Network, and Related Methods and Computer Programs=


==Organization Name==

[[:Category:Nokia Solutions and Networks Oy|Nokia Solutions and Networks Oy]]


[[Category:Nokia Solutions and Networks Oy]]

==Inventor(s)==

[[:Category:Mikko Johannes Honkala of Espoo (FI)|Mikko Johannes Honkala of Espoo (FI)]][[Category:Mikko Johannes Honkala of Espoo (FI)]]

[[:Category:Dani Johannes Korpi of Helsinki (FI)|Dani Johannes Korpi of Helsinki (FI)]][[Category:Dani Johannes Korpi of Helsinki (FI)]]

[[:Category:Janne Matti Juhani Huttunen of Espoo (FI)|Janne Matti Juhani Huttunen of Espoo (FI)]][[Category:Janne Matti Juhani Huttunen of Espoo (FI)]]

==A Radio Receiver with an Iterative Neural Network, and Related Methods and Computer Programs - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18575419 titled 'A Radio Receiver with an Iterative Neural Network, and Related Methods and Computer Programs

==Simplified Explanation==
The patent application describes a radio receiver device that uses an iterative neural network to determine log-likelihood ratios of information bits in a received radio signal.

==Key Features and Innovation==
* Radio receiver device receives a radio signal with information bits.
* Determines log-likelihood ratios (LLRs) of the information bits.
* Uses an iterative neural network (NN) to process the frequency domain representation of the signal.
* Iterative NN includes a single processing block that iteratively processes the signal.
* Outputs estimates of LLRs based on the processing results of the single processing block.

==Potential Applications==
This technology can be applied in:
* Wireless communication systems
* Signal processing applications
* Radio frequency engineering

==Problems Solved==
* Efficient determination of log-likelihood ratios in radio signals
* Improved signal processing accuracy
* Enhanced performance of radio receiver devices

==Benefits==
* Increased accuracy in decoding information bits
* Enhanced reliability of radio communication systems
* Improved overall performance of radio receiver devices

==Commercial Applications==
* This technology can be utilized in the development of advanced radio receiver devices for various industries such as telecommunications, broadcasting, and military communications.

==Prior Art==
Readers interested in prior art related to this technology can explore research papers, patents, and publications in the field of wireless communication systems, signal processing, and neural networks.

==Frequently Updated Research==
Stay updated on the latest advancements in neural network applications in radio signal processing and wireless communication systems to understand the evolving landscape of this technology.

==Questions about Radio Signal Processing==
===How does the iterative neural network improve the accuracy of log-likelihood ratio determination in radio signals?===
The iterative neural network processes the frequency domain representation of the signal iteratively, enhancing the accuracy of log-likelihood ratio estimation through multiple processing steps.

===What are the potential challenges in implementing this technology in real-world radio receiver devices?===
Implementing this technology in real-world devices may face challenges related to computational complexity, power consumption, and integration with existing radio signal processing systems.


==Original Abstract Submitted==

Radio receiver devices and related methods and computer programs are disclosed. A radio signal including information bits is received at a radio receiver device. The radio receiver device determines log-likelihood ratios, LLRs, of the information bits. The determining of the LLRs is performed by applying an iterative neural network, NN, to a frequency domain representation of the received radio signal over a transmission time interval, TTI. The iterative NN includes a single processing block iteratively executable to process the frequency domain representation of the received radio signal. The iterative NN is configured to output estimates of the LLRs based on the processing results of the single processing block.



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