Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, in a control channel, a first grant identifying a first set of resources of a first data channel on which the UE is to monitor for one or more second grants, the first data channel being downlink. The UE may monitor the first set of resources in the first data channel for the one or more second grants, the one or more second grants identifying a second set of resources of a second data channel on which the UE is to perform data communications. The UE may transmit, based at least in part on the monitoring the first set of resources, a feedback message associated with receipt of the one or more second grants.

Methods, systems, and devices for wireless communications are described. A user equipment (UE) may receive, in a control channel, a first grant identifying a first set of resources of a first data channel on which the UE is to monitor for one or more second grants, the first data channel being downlink. The UE may monitor the first set of resources in the first data channel for the one or more second grants, the one or more second grants identifying a second set of resources of a second data channel on which the UE is to perform data communications. The UE may transmit, based at least in part on the monitoring the first set of resources, a feedback message associated with receipt of the one or more second grants.

Example aspects include a method, apparatus, and computer-readable medium for wireless communication at user equipment (UE) of a mobile network, comprising monitoring an uplink metric of an uplink transmission channel. The aspects further include calculating an uplink transmit power based at least on a tolerance threshold. Additionally, the aspects include transmitting, via the uplink transmission channel according to the uplink transmit power, an uplink transmission. Additionally, the aspects include detecting a change in the uplink metric. Additionally, the aspects include comparing the change in the uplink metric with performance improvement criteria. Additionally, the aspects include determining whether to adjust the uplink transmit power. Additionally, the aspects include iterating adjustments to the uplink transmit power. Additionally, the aspects include stopping the adjustments to the uplink transmit power in response to determining that the uplink metric meets a performance threshold or in response to determining that the tolerance threshold has been met.

Example aspects include a method, apparatus, and computer-readable medium for wireless communication at user equipment (UE) of a mobile network, comprising monitoring an uplink metric of an uplink transmission channel. The aspects further include calculating an uplink transmit power based at least on a tolerance threshold. Additionally, the aspects include transmitting, via the uplink transmission channel according to the uplink transmit power, an uplink transmission. Additionally, the aspects include detecting a change in the uplink metric. Additionally, the aspects include comparing the change in the uplink metric with performance improvement criteria. Additionally, the aspects include determining whether to adjust the uplink transmit power. Additionally, the aspects include iterating adjustments to the uplink transmit power. Additionally, the aspects include stopping the adjustments to the uplink transmit power in response to determining that the uplink metric meets a performance threshold or in response to determining that the tolerance threshold has been met.

Various systems and methods for scheduling data transmissions from a base station to user equipment (UE) are presented. Channel quality indicator values that correspond to multiple UE may be determined for multiple carrier components of a cellular network's carrier aggregation. A scheduling matrix may be created that includes instantaneous data transfer rates for the UE. Elements within the scheduling matrix may be normalized by modifying instantaneous data transmission rates using average data transmission rates. Scheduling decisions for data transfers may be made for the UE based on the normalized scheduling matrix.

Various systems and methods for scheduling data transmissions from a base station to user equipment (UE) are presented. Channel quality indicator values that correspond to multiple UE may be determined for multiple carrier components of a cellular network's carrier aggregation. A scheduling matrix may be created that includes instantaneous data transfer rates for the UE. Elements within the scheduling matrix may be normalized by modifying instantaneous data transmission rates using average data transmission rates. Scheduling decisions for data transfers may be made for the UE based on the normalized scheduling matrix.

One example method of operation may include transmitting a data stream from a first device to a second device via one or more channels, determining the data stream experienced a potential network communication error, and retransmitting at least a portion of the data stream over a mirrored channel transmission comprising at least two streams which both retransmit in parallel at least a same portion of the retransmitted portion of the data stream.

One example method of operation may include transmitting a data stream from a first device to a second device via one or more channels, determining the data stream experienced a potential network communication error, and retransmitting at least a portion of the data stream over a mirrored channel transmission comprising at least two streams which both retransmit in parallel at least a same portion of the retransmitted portion of the data stream.

Provided is a method and system for optimizing utilization and performance of a Wi-Fi network for one or more subscriber client devices through a Wi-Fi console application by monitoring an RF environment of the Wi-Fi network to detect interference to a subscriber client device from one or more neighboring client devices that include non-subscriber client devices and other subscriber client devices and allocating a spectrum/channel for the subscriber client device to access the Wi-Fi network using an AI model based on the interference detected, throughput requirements of applications running on the subscriber client device and importance/priority of an activity on the subscriber client device. The AI model constructs a relational aggregated graph and decompose the relational aggregated graph into dynamic clusters. A heuristic deep-learning method is applied to analyze the dynamic clusters to reduce a computation time for recommendation of a suitable spectrum/channel for accessing the Wi-Fi network.

Provided is a method and system for optimizing utilization and performance of a Wi-Fi network for one or more subscriber client devices through a Wi-Fi console application by monitoring an RF environment of the Wi-Fi network to detect interference to a subscriber client device from one or more neighboring client devices that include non-subscriber client devices and other subscriber client devices and allocating a spectrum/channel for the subscriber client device to access the Wi-Fi network using an AI model based on the interference detected, throughput requirements of applications running on the subscriber client device and importance/priority of an activity on the subscriber client device. The AI model constructs a relational aggregated graph and decompose the relational aggregated graph into dynamic clusters. A heuristic deep-learning method is applied to analyze the dynamic clusters to reduce a computation time for recommendation of a suitable spectrum/channel for accessing the Wi-Fi network.