CPC Class H04W

Provided is a method and a system for multi-channel acoustic communication and sensing. For example, there is provided a system that includes a processor and a memory. The processor, when executing instructions from the memory, can perform certain operations. The operations can include classifying a motion detected near an ultrasonic receiver based on a Doppler shift observed in a signal measured by the ultrasonic receiver. The classifying can further include detecting a side lobe in a power spectrum of the signal to indicate that the motion has been detected.

In one embodiment, a device obtains a machine learning model indicative of how to focus on particular location information from a plurality of radio frequency (RF) elements to provide an accurate location estimate of a wireless client based at least in part on angle-of-arrival information of the wireless client. When the device then obtains location information regarding the wireless client from the plurality of RF elements, it may apply the machine learning model to the location information regarding the wireless client to focus on particular location information of the location information from the plurality of RF elements. The device may then estimate a physical location of the wireless client based on focusing on the particular location information during a locationing computation.

A wireless transmit receive unit (WTRU) is configured to receive a reference signal of a first type. The first type is other than a demodulation reference signal (DM-RS). Reference signals of the first type are received in resource elements other than resource elements used for a primary synchronization signal or a secondary synchronization signal. The WTRU is configured to receive a radio resource control message indicating a subframe position in which the reference signal of the first type is transmitted and a periodicity of a transmission of the reference signal of the first type.

A method comprising: receiving a radio map of an indoor venue using survey data collected by a survey device positioned throughout the venue, the radio map including a boundary; receiving harvest data from a mobile device, wherein at least some of the harvest data are obtained by the mobile device while the mobile device is positioned at locations that are outside of the boundary; determining, based on the harvest data, a trajectory of the mobile device, wherein at least some of the trajectory resides outside of the boundary; identifying one or more locations on or proximate to the trajectory; and extending the radio map using the survey data and the one or more identified locations, wherein the extended radio map is defined at least in part by an extension of the boundary to encompass the one or more identified locations.

A method of implementing spread spectrum techniques in an automotive radar with wireless communication capabilities enables an anti-jammer radar capable of overcoming channel noise. The method is provided with a MIMO radar and at least one base station. The MIMO radar transmits the initial uplink signal and receives an ambient signal containing a reflected uplink signal and the downlink signal. The initial uplink signal is encrypted to overcome channel noise and jamming signals. The downlink signal is used to establish wireless communication between the base station and the MIMO radar. As such, the downlink signal is filtered and processed from the ambient signal. Similarly, the reflected downlink signal is also filtered from the ambient signal. Finally, the MIMO radar decrypts the reflected uplink signal to detect a plurality of targets and derive spatial positioning data for each target.