AT&T Intellectual Property I, LP

At&t Mobility II LLC

Paul Maxwell

Ernest Tsui

Weihua Ye

Young Suh

Brian Gavin

Michael Taylor

James Hollister

Guanying Ru

Vibhav Arun Kapnadak

Peter Richard Wong

Embodiments for port reconfiguration for passive intermodulation interference mitigation are presented herein. A base station device comprises a signal processing component comprising a passive intermodulation interference component and an antenna configuration component. The passive intermodulation interference component determines passive intermodulation interference corresponding to uplink signals that have been received, via a configurable cellular antenna array of the base station device, from respective wireless devices of a group of wireless devices that have been communicatively coupled to the base station device. The antenna configuration component selects a defined configuration of a group of cellular antenna ports of the configurable cellular antenna array to facilitate a reduction of the passive intermodulation interference corresponding to the uplink signals.

Port reconfiguration for passive intermodulation interference mitigation

A system includes a base band unit pooling component that determines, via a base band unit pool of base station devices, respective uplink channel estimates of an uplink channel wirelessly coupling, using frequency division duplexing via respective modular antenna elements, a user equipment to the base band unit pool. A downlink channel estimation component of the system derives, based on the respective uplink channel estimates, a downlink channel estimate of a downlink channel wirelessly coupling, using the frequency division duplexing via a portion of the respective modular antenna elements corresponding to a base station device of the base band unit pool, the base station device to the user equipment. In turn, the system generates, using the downlink channel estimate, a group of downlink sector beams to be transmitted to the user equipment using the downlink channel via the portion of the respective modular antenna elements.

Generating downlink sector beams based on uplink channel estimates utilizing a base band unit pool for modular massive multiple-input multiple-output arrays

Aspects of the subject disclosure may include, for example, causing a reference antenna element of a first set of antenna elements of a first antenna array to transmit a first signal, determining for each antenna element of a second set of antenna elements of a second antenna array, a receive-related offset, relative to the reference element, based on inter-element propagation delays between the first and second sets of elements, causing each antenna element of the second set of elements to transmit a respective second signal, based on the reference antenna element receiving the respective second signals, calculating a respective transmit-related offset for each antenna element of the second set of antenna elements relative to the reference antenna element based on the inter-element propagation delays, and performing calibration between the first antenna array and the second antenna array based on the respective receive-related and transmit-related offsets. Other embodiments are disclosed.

Method and system for calibrating modular antenna arrays

Aspects of the subject disclosure may include, for example, obtaining, over an uplink (UL) using an aggregation of modular antenna arrays, a modulated signal that includes feedback transmitted by a user equipment (UE), wherein the aggregation of modular antenna arrays comprises multiple groups of antenna elements, after the obtaining the modulated signal, performing a demodulation of the modulated signal, determining demodulator constellation errors from the demodulation of the modulated signal, performing an error gradient weight adaptation responsive to the determining the demodulator constellation errors to derive revised weights for various antenna elements of the multiple groups of antenna elements, and applying the revised weights to the various antenna elements of the multiple groups of antenna elements to adjust signals received over the UL. Other embodiments are disclosed.

Method and system for uplink beam optimization and calibration

Aspects of the subject disclosure may include, for example, receiving a plurality of orthogonal sounding reference signals (SRS) from a plurality of user equipment (UEs), wherein each SRS of the plurality of orthogonal SRS is provided by a respective UE of the plurality of UEs, determining a downlink (DL) channel, in frequency division duplex (FDD), using spatial correlations relating to the plurality of UEs, wherein the spatial correlations are based on the plurality of orthogonal SRS, calculating a plurality of DL precoding weights for a plurality of coherent modular antenna panels responsive to the determining the DL channel, and applying the plurality of DL precoding weights to the plurality of coherent modular antenna panels to enable multi-user (Mu)-multiple-input-multiple-output (MIMO) for the plurality of UEs. Other embodiments are disclosed.

Method and system for predicting a downlink channel

Aspects of the subject disclosure may include, for example, receiving sounding reference signal (SRS) symbols from antenna elements of each of multiple modular antenna arrays, wherein the multiple modular antenna arrays are operatively combined to form a coherent antenna system, performing an uplink (UL) channel estimation and a downlink (DL) channel estimation, across a plurality of physical resource blocks (PRBs), based on the SRS symbols, calculating, for the antenna elements, a plurality of uplink (UL) combining weights based on the UL channel estimation and a plurality of downlink (DL) precoder weights based on the DL channel estimation, and causing the plurality of UL combining weights and the plurality of DL precoder weights to be applied to the antenna elements, thereby adjusting beamforming of the coherent antenna system. Other embodiments are disclosed.

Method and system for determining uplink and downlink weights for antenna elements of modular antenna arrays

A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. A passive intermodulation cancelation system can generate an equivalent signal to a received interference signal and use the equivalent signal to generate an error signal. The error signal can then be used to reinforce a learning system and converge on a steady state of the interference signal to cancel other interference signals.

Facilitation of passive intermodulation cancelation via machine learning

A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. The passive intermodulation detection system can generate a test signal in a first band that is transmitted by an antenna. Another antenna can receive a signal in another band, and the passive intermodulation detection system can analysis the received signal to determine whether an intermodulation product due to a non-linearity is present. Based on the type of intermodulation product, period, order, frequency, and etc., the type and location of the non-linearity can be identified.

Remote diagnosis and cancellation of passive intermodulation

A passive intermodulation detection system is provided to remotely identify passive intermodulation at a base station site and diagnose the type of intermodulation and location of the non-linearity that is the source of the passive intermodulation. The passive intermodulation detection system can generate a test signal in a first band that is transmitted by an antenna. Another antenna can receive a signal in another band, and the passive intermodulation detection system can analyze the received signal to determine whether an intermodulation product due to a non-linearity is present. Based on the type of intermodulation product, period, order, frequency, and etc, the type and location of the non-linearity can be identified and canceled via a passive intermodulation canceling mechanism.

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Piedmont, CA, United States of America

Paul Maxwell