Among other things, aspects, features, and implementations of wireless mesh networks and wireless mesh network devices are described.

Methods for determining variability in a state of a medium, include monitoring the medium and determining the variability in the state of the medium based on the processing of the response over time based on the response detected at the at least one receive element over time. Monitoring the medium can include generating a transmit signal, transmitting it into the medium using a transmit element, and receiving a signal from the medium at a receive element. The transmit and receive elements can be decoupled from one another. The transmit and receive elements can have differing geometry. The determined variability in the state of the medium can be used to provide notifications and/or take automated actions.

The present disclosure relates to methods and devices for mitigating inter-cluster interference in clusters where one or more network nodes are transmitting in coordination using several transceiver antennas. In particular the disclosure relates to improved precoder algorithms to be used for coordinated multipoint transmission applications. The disclosure also relates to corresponding computer programs. The disclosure proposes a method, performed in a communication system, of mitigating inter-cluster interference, wherein the communication system is configured to coordinate transmissions of one or more wireless devices within two or more wireless device categories and one or more network nodes, wherein the one or more network nodes are transmitting in coordination to the wireless devices in the cluster using several transceiver antennas.

For example, a first wireless communication device may be configured to cluster a plurality of channel estimation measurements into a plurality of clusters based on a clustering criterion, the plurality of channel estimation measurements corresponding to a respective plurality of Physical Protocol Data Units (PPDUs) received from a second wireless communication device over a wireless communication channel; and, based on clustering of the plurality of channel estimation measurements into the plurality of clusters, selectively provide a clustered channel estimation measurement to be processed for detection of changes in an environment of the wireless communication channel, by providing the clustered channel estimation measurement together with one or more other clustered channel estimation measurements of a same cluster of the clustered channel estimation measurement to be processed for the detection of the changes in the environment.

Embodiments of a user equipment (UE) and method for resource allocation and device-to-device (D2D) discovery hopping are generally described herein. In some embodiments, the UE may receive signaling from an enhanced node B (eNB) indicating discovery resources to transmit discovery signals on within an LTE operation zone. The discovery resources may include a discovery zone which may comprise a plurality of physical resource blocks (PRBs) and a plurality of subframes. The UE may transmit a discovery signal for receipt by one or more other UEs for D2D discovery within some of the PRBs of the discovery zone. The PRBs for the transmission of the discovery signal may be determined in accordance with a hopping mode to provide increased frequency diversity within a bandwidth of the discovery zone. The hopping mode may comprise intra-subframe hopping, inter-subframe hopping or joint intra/inter-subframe hopping.

Aspects of the present disclosure describe receiving, from an access point, an indication of at least one of a beamforming method for beamforming a RS or a normalization method for normalizing power for beamforming the RS. A channel covariance matrix corresponding to interference over a plurality of antenna ports can be generated, as well as a RS beamforming matrix based at least in part on modifying the channel covariance matrix and on the normalization method. The RS can be generated based on the RS beamforming matrix and the beamforming method. The RS can be transmitted to the access point based on the RS beamforming matrix.

A semi-blind channel estimation method and apparatus are provided. The semi-blind channel estimation method includes: step S1: obtaining data that includes a first training sequence and that is received by a receive end; step S2: performing minimum mean square error channel estimation based on the data and the prestored first training sequence, to obtain a channel parameter matrix; step S3: detecting the first training sequence by using a least square detection algorithm, to obtain estimated data; and step S4: using the estimated data as a second training sequence, replacing the first training sequence in step S2 with the second training sequence, and cyclically performing step S2 and step S3 on the second training sequence, until a channel parameter matrix obtained last time is the same as a channel parameter matrix obtained this time, and then stopping circulation, to estimate a final channel parameter matrix.

According to an embodiment, a system can comprise a processor and a memory that can store executable instructions that, when executed by the processor, facilitate performance of operations. The operations can include generating a first signal in an initial domain and transforming the first signal into a first portion of a time-frequency grid of a time-frequency domain, resulting in a transformed first signal. The operations further include combining the transformed first signal with a second signal of a second portion of the time-frequency grid, resulting in a combined signal, and transmitting the combined signal to a user equipment device for a further transformation. The operations further include receiving a response signal from the user equipment device that was configured, based on the further transformed first signal.

Complex transfer functions indicating characteristics of propagation between transmission antenna elements and N reception antenna elements are calculated from reception signals received by the N reception antenna elements during a predetermined period. Components affected by vital activity are extracted from the calculated complex transfer functions. A correlation matrix is calculated from changed components affected by vital activity. A steering vector for regions divided from a target region is calculated. A living-body signal intensity vector is estimated by performing compressed sensing for an unknown value that is the living-body signal intensity vector using a correlation matrix vector and an extended steering vector. The number of components constituting the living-body signal intensity vector and having a value of at least a predetermined threshold is estimated to be the number of living bodies, and positions of regions corresponding to the components are estimated to be estimated positions of the living bodies.

According to an embodiment, a system can comprise a processor and a memory that can store executable instructions that, when executed by the processor, facilitate performance of operations. The operations can include generating a first signal in an initial domain and transforming the first signal into a first portion of a time-frequency grid of a time-frequency domain, resulting in a transformed first signal. The operations further include combining the transformed first signal with a second signal of a second portion of the time-frequency grid, resulting in a combined signal, and transmitting the combined signal to a user equipment device for a further transformation. The operations further include receiving a response signal from the user equipment device that was configured, based on the further transformed first signal.