Managing massive mimo antennas in a wireless network
AssigneeCellwize Wireless Technologies Ltd.
InventorsDan WEIL, Yaniv VAKNIN, Daniel YELLIN
Life of this patent
Estimating the term…
Abstract
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a network entity may calculate, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna. The network entity may provide the one or more predicted KPIs. Numerous other aspects are described.
Claims30
An apparatus, comprising:
- a memory;
- and
- one or more processors, coupled to the memory, configured to:
- calculate, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna;
- and
- provide the one or more predicted KPIs.
A method of managing an antenna configuration in a wireless network, comprising:
- calculating, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna;
- and
- providing the one or more predicted KPIs.
A non-transitory computer-readable medium storing a set of instructions for wireless communication, the set of instructions comprising:
- one or more instructions that, when executed by one or more processors of an apparatus, cause the apparatus to:
- calculate, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna;
- and
- provide the one or more predicted KPIs.
An apparatus for wireless communication, comprising:
- means for calculating, using a machine learning (ML) model trained to estimate an impact of a reconfiguration of an antenna on a set of key performance indicators (KPIs) of a given cell and one or more neighbors of the given cell, one or more predicted KPIs using data characterizing a reconfiguration of a massive multiple-input multiple-output (M-MIMO) antenna;
- and
- means for providing the one or more predicted KPIs.
Dependencies are inferred from the claim text.