View source for 18701449. Determination of Autoregressive Model Order for a Channel Prediction Filter simplified abstract (Telefonaktiebolaget LM Ericsson (publ))

=Determination of Autoregressive Model Order for a Channel Prediction Filter=


==Organization Name==

[[:Category:Telefonaktiebolaget LM Ericsson (publ)|Telefonaktiebolaget LM Ericsson (publ)]]


[[Category:Telefonaktiebolaget LM Ericsson (publ)]]

==Inventor(s)==

[[:Category:Zhao Wang of TÄBY (SE)|Zhao Wang of TÄBY (SE)]][[Category:Zhao Wang of TÄBY (SE)]]

[[:Category:Xueying Hou of LUND (SE)|Xueying Hou of LUND (SE)]][[Category:Xueying Hou of LUND (SE)]]

[[:Category:Wei Zhou of STAFFANSTORP (SE)|Wei Zhou of STAFFANSTORP (SE)]][[Category:Wei Zhou of STAFFANSTORP (SE)]]

[[:Category:Rikke Apelfr�jd of KNIVSTA (SE)|Rikke Apelfr�jd of KNIVSTA (SE)]][[Category:Rikke Apelfr�jd of KNIVSTA (SE)]]

==Determination of Autoregressive Model Order for a Channel Prediction Filter - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18701449 titled 'Determination of Autoregressive Model Order for a Channel Prediction Filter

**Simplified Explanation:**
The patent application describes a method for determining the order of an autoregressive (AR) model for channel prediction in a radio environment based on the quality of Channel State Information (CSI).

**Key Features and Innovation:**
* Mechanisms for CSI quality triggered determination of AR model order for channel prediction.
* Method involves obtaining an indication of declining CSI quality, estimating current channel conditions, and determining AR model order accordingly.
* Channel prediction filter defined by the AR model with the determined order.

**Potential Applications:**
This technology can be applied in wireless communication systems, IoT devices, and network optimization for improved channel prediction accuracy.

**Problems Solved:**
The technology addresses the challenge of adapting the AR model order for channel prediction in response to changing channel conditions and declining CSI quality.

**Benefits:**
* Enhanced channel prediction accuracy.
* Improved performance in dynamic radio environments.
* Efficient resource allocation in wireless networks.

**Commercial Applications:**
* Wireless communication systems.
* IoT devices for smart homes and cities.
* Network optimization solutions for telecom companies.

**Prior Art:**
Readers can explore prior research on AR model order determination for channel prediction in wireless communication systems and signal processing literature.

**Frequently Updated Research:**
Stay updated on the latest advancements in AR model order determination for channel prediction in dynamic radio environments for cutting-edge applications.

**Questions about AR Model Order Determination for Channel Prediction:**
1. What are the key factors influencing the determination of the AR model order for channel prediction?
2. How does the quality of Channel State Information impact the accuracy of channel prediction in wireless communication systems?


==Original Abstract Submitted==

There is provided mechanisms for CSI quality triggered determination of AR model order for a channel prediction filter. A method is performed by a network node. The method comprises obtaining an indication of declining CSI quality in a radio environment. The method comprises, in response thereto, obtaining an estimation of current channel conditions in the radio environment. The method comprises determining the AR model order based on the estimation of current channel conditions. The method comprises performing channel prediction of the radio environment using the channel prediction filter. The channel prediction filter is defined by an AR model having the determined AR model order.



[[Category:H04B17/391]]
[[Category:H04B7/06]]
[[Category:CPC_H04B17/3913]]