The present disclosure relates to a mobile terminal, a base station and respective operation methods. The mobile terminal comprises circuitry, which in operation assumes that a base station is configured to use one of a plurality of transmission beams, receives a downlink control channel candidate and a corresponding demodulation reference signal using one of a plurality of reception beams corresponding to the assumed one of the plurality of transmission beams, performs channel estimation based on the received demodulation reference signal, and, depending on the quality, demodulates the downlink control channel candidate using the channel estimation. The channel estimation is performed using a demodulation reference signal sequence which is generated observing an association which is associating the generated sequence with the assumed one of the plurality of transmission beams such that at least two of the plurality of transmission beams are associated with different demodulation reference signal sequences.

A device for performing wireless communication at least one processor configured to generate a condition signal based on at least one parameter associated with the device or the wireless communication, and select at least one of a plurality of signal processing algorithms for performing at least one of a plurality of signal processing functions based on the condition signal, each of the plurality of signal processing functions being associated with the wireless communication.

Disclosed are a method and system for acquiring massive MIMO beam domain statistical channel information. A refined beam domain channel model involved in the disclosed method is based on a refined sampling steering vector matrix. Compared with a traditional DFT matrix-based beam domain channel model, when antenna size is limited, said model is closer to a physical channel model, and provides a model basis for solving the problem of the universality of massive MIMO for various typical mobile scenarios under a constraint on antenna size. The present invention provides a method for acquiring massive MIMO refined beam domain a priori statistical channel information and a posteriori statistical channel information, the a posteriori statistical channel information comprising mean and variance information of the a posteriori channel. The method of the present invention has low complexity, can be applied to an actual massive MIMO system, provides support for a robust precoding transmission method, and has large application value.

The present disclosure relates to a mobile terminal, a base station and respective operation methods. The mobile terminal comprises circuitry, which in operation assumes that a base station is configured to use one of a plurality of transmission beams, receives a downlink control channel candidate and a corresponding demodulation reference signal using one of a plurality of reception beams corresponding to the assumed one of the plurality of transmission beams, performs channel estimation based on the received demodulation reference signal, and, depending on the quality, demodulates the downlink control channel candidate using the channel estimation. The channel estimation is performed using a demodulation reference signal sequence which is generated observing an association which is associating the generated sequence with the assumed one of the plurality of transmission beams such that at least two of the plurality of transmission beams are associated with different demodulation reference signal sequences.

Provided are a downlink channel state information estimation method and apparatus, a device, and a storage medium. The downlink channel state information estimation method includes sending a downlink radio frame carrying channel sounding information; receiving an uplink radio frame carrying a first downlink channel state information data set; acquiring an uplink channel state information data set; and determining a second downlink channel state information data set.

The present invention relates to a frequency offset estimation method for average consensus-based clock synchronization, and belongs to the technical field of wireless sensor networks. According to the method, in combination with distributed one-way broadcast characteristics, solving of maximum likelihood estimation is converted into a linear optimization problem, and a relative frequency offset estimation value is obtained by adopting an iterative method. By applying the estimation value to the compensation of logic clock parameter between nodes, an effect of keeping logic clocks of network nodes consistent can be achieved. According to the present invention, distribution characteristics of communication time delay are fully considered, accurate relative frequency offset estimation can be implemented, so the synchronization precision of average consensus-based clock synchronization is effectively improved, the maximum likelihood estimation solving is performed by adopting the iterative method, an estimation algorithm is simplified, and storage overhead is reduced.

Various embodiments provide apparatuses, systems, and methods to determine a figure of merit (FOM) of a communication link (e.g., a serial communication link, also referred to herein as a channel) between a transmitter and a receiver. The FOM may be used to, for example, determine a health of the communication link during mission mode (normal operating mode), determine a modulation scheme to use for the communication link, determine a configuration to use for the receiver and/or transmitter, and/or another suitable use case. Other embodiments may be described and claimed.

The present disclosure relates to a method (10) for characterizing a wideband RF device-under-test (DUT) by means of a narrowband RF source or a narrowband RF receiver, the method (10) comprising: selecting (11) a bandwidth of the wideband RF DUT to be analyzed; dividing (12) the selected bandwidth into at least two overlapping sub-bands, the respective sub-bands having a frequency range that corresponds to a bandwidth of the narrowband RF source or the narrowband RF receiver; acquiring (13) a response of the wideband RF DUT for each of the at least two overlapping sub-bands by means of at least two narrowband measurements using the narrowband RF source or the narrowband RF receiver; and calculating (14) a continuous amplitude response and a continuous phase response of the wideband RF DUT in a frequency range that corresponds to the combined bandwidth of the at least two overlapping sub-bands, said calculation making use of the overlap of the sub-bands.

According to the present document, a method by which a terminal receives data in a wireless communication system comprises: receiving a channel signal and a reference signal (RS) from a base station; generating a sequence by performing an operation of equalizing the RS to a channel RS; and decoding the received channel signal on the basis of the generated sequence, wherein the operation of equalizing the RS to the channel RS is based on a parameter determined according to a machine learning process.

Systems, methods, and devices to reduce the channel estimation overhead by collecting data from many UEs and building a location-based mathematical model are disclosed. During building of the model, a reference signal is used to collect location- and signal-related data from connected UEs. Once the model is successfully built, it is then transmitted and/or downloaded to each new UE that connects to the base station. The UEs and/or the base stations then use this model to determine their own transmission parameter values. The UEs also report their location to the base stations, which use the model to estimate channel conditions and adapt transmission parameters for themselves.