18617740. Nonlinear Neural Network with Phase Normalization for Base-Band Modelling of Radio-Frequency Non-Linearities simplified abstract (Nokia Solutions and Networks Oy)

Nonlinear Neural Network with Phase Normalization for Base-Band Modelling of Radio-Frequency Non-Linearities

Organization Name

Nokia Solutions and Networks Oy

Inventor(s)

Arne Fischer-buhner of Leuven (BE)

Nonlinear Neural Network with Phase Normalization for Base-Band Modelling of Radio-Frequency Non-Linearities - A simplified explanation of the abstract

This abstract first appeared for US patent application 18617740 titled 'Nonlinear Neural Network with Phase Normalization for Base-Band Modelling of Radio-Frequency Non-Linearities

Simplified Explanation: The patent application discusses a method to mitigate non-linearity in a data communication chain by using a neural network.

• **Key Features and Innovation:**

   - Obtaining a data communication signal with complex-valued input samples.
   - Capturing a current sample and a set of delayed samples from the input.
   - Generating a phase-normalized input signal by normalizing the phase of the samples.
   - Providing the phase-normalized signal to a neural network to mitigate non-linearity.
   - Denormalizing the output sample to restore the phase of the data communication signal.

• **Potential Applications:**

   - Improving the performance and efficiency of data communication systems.
   - Enhancing signal processing in telecommunications and networking technologies.

• **Problems Solved:**

   - Addressing non-linearity issues in data communication chains.
   - Improving the accuracy and reliability of data transmission.

• **Benefits:**

   - Enhanced signal quality and reduced distortion.
   - Increased data transmission speeds and efficiency.

• **Commercial Applications:**

   - Telecom companies can use this technology to optimize their data communication networks.
   - Manufacturers of networking equipment can integrate this innovation to enhance their products.

• **Prior Art:**

   - Researchers and engineers in the field of signal processing and telecommunications may have explored similar methods to mitigate non-linearity in data communication chains.

• **Frequently Updated Research:**

   - Stay updated on advancements in neural network applications in signal processing and data communication technologies.

Questions about Mitigation of Non-Linearity in Data Communication Chain: 1. How does the normalization of phase help in mitigating non-linearity in data communication chains? 2. What are the potential challenges in implementing neural networks for non-linearity mitigation in data communication systems?

Original Abstract Submitted

Various example embodiments relate to mitigation of a non-linearity in a data communication chain. A method may include: obtaining a data communication signal including a plurality of complex-valued input samples; capturing, from the plurality of complex-valued input samples, a current sample and a set of delayed samples; generating a phase-normalized input signal based on normalizing phase of the current sample and the set of delayed samples by a normalization term, wherein the normalization term is common for the current sample and the set of delayed samples; providing the phase-normalized input signal to a neural network configured to mitigate non-linearity of a data communication chain and to output a complex-valued output sample for each of the plurality of complex-valued input samples; and denormalizing phase of the complex-valued output sample by a denormalization term configured to restore phase of the data communication signal.