Physical layer key generation provides privacy protection technique suitable for devices with limited computational ability. A key generation algorithm is based on OFDM waveforms. By exploiting the holistic CSI, key generation rate (KGR) is improved significantly. A cross-layer encryption protocol is based on the key generation algorithm and the AES. The secrecy of the encryption is enhanced compared to traditional encryption schemes with one pre-shared key (e.g., WPA2-PSK), even when some generated keys are leaked to the eavesdropper. The results lead to practical and robust applications of physical layer key generation.

An apparatus, method and computing program is described including: receiving one or more received symbols and one or more received bits, wherein the received symbols are received at a receiver of a transmission system including a transmitter, a channel, and the receiver; converting one or more of the received bits that are deemed to be correct into one or more estimated transmission symbols; generating an estimated channel transfer function based on one or more of the estimated transmission symbols and corresponding received symbols; and providing training data pairs, each training data pair including a first element based on the estimated channel transfer function and a second element based on the corresponding received symbols.

A receiving circuit (100) includes: a channel estimation unit (20) configured to estimate a channel response vector based on a reception signal received via a plurality of antennas (10); a covariance matrix estimation unit (30) configured to estimate a covariance matrix based on the reception signal and the channel response vector; a covariance matrix correction unit (40) configured to correct the covariance matrix by adding, to the covariance matrix, an offset value with a value in components including off-diagonal elements of the matrix; and a weight multiplication unit (50) configured to estimate a transmission signal by multiplying a weight based on the channel response vector and the corrected covariance matrix by the reception signal.

Example embodiments of the present disclosure relate to machine learning-based channel estimation. According to an example embodiment, a first device determines a signal quality that is expected in transmission of a reference signal from a second device to the first device and receives the reference signal from the second device. The first device selects, based on the expected signal quality, a channel estimation model from a plurality of channel estimation models that have been trained for a plurality of candidate signal qualities for the reference signal. The first device determines, using the selected channel estimation model and based on the received reference signal, channel state information of a communication channel from the first device to the second device. According to this solution, a channel estimation model is dynamically selected for use, depending on a real-time signal quality expected to be gained in transmission of a certain RS.

An apparatus, method, and non-transitory computer readable medium performing estimating spatial overlap of beams associated with one or more combinations of at least two user devices of a plurality of user devices of a mobile communications system based, at least in part, on angular direction of radiated power of the user devices, wherein the user devices include candidate user devices to be scheduled on a network resource for multi user channel transmission; and determining scheduling metrics associated with the one or more combinations of the at least two user devices of the plurality of user devices based on the estimated spatial overlap.

An electronic device is provided. The electronic device includes a communication circuit and a processor. The processor may be configured to obtain information on the number of predicted abnormal terminals, allocate different resources respectively to a plurality of terminal groups, wherein the number of the plurality of terminal groups is greater than the number of predicted abnormal terminals, obtain learning data of each of the plurality of terminal groups, and identify a final terminal group among the plurality of terminal groups, based on the learning data.

Embodiments provide efficient channel access utilizing a channel assessment mode and include determining that a predetermined condition exists on a radio bandwidth (e.g., unlicensed band); and, in response to determining that the predetermined condition exists on the radio bandwidth, initiating the channel assessment mode on the mobile device, where the channel assessment mode is configured to implement a channel assessment scheme configured for efficiently accessing a channel on the radio bandwidth. Some embodiments monitor the radio bandwidth for one or more triggering events indicative of interference; and detect at least one of the one or more triggering events indicative of interference on the radio bandwidth in order to determine the predetermined condition exists. These triggering events may include determining a current/historic packet collision probability is above a threshold, detecting signals that identify another radio access system, detecting a channel utilization ratio above a threshold, and determining a current/historic data throughput.

In response to an instruction received from a base station, a signal forwarding device applies a signal forwarding scheme selected from a plurality of signaling forwarding schemes by a scheduler. The signal forwarding scheme may be applied by the signal forwarding device to forward signals from the base station to a user equipment (UE) device and/or from the UE device to the base station. The scheduler selects the signal forwarding scheme based on channel characteristics of the channel between the signal forwarding device and the UE device and/or the channel between the signal forwarding device and the base station. Although at least some of the channel characteristics are determined by the base station, at least some of the channel characteristics can be determined by the signal forwarding device in some situations.

Some demonstrative embodiments include apparatuses, devices, systems and methods of communicating an Enhanced Directional Multi-Gigabit (DMG) (EDMG) Physical Layer Protocol Data Unit (PPDU). For example, an EDMG wireless communication station (STA) may be configured to communicate an EDMG PPDU including a Channel Estimation Field (CEF) and/or a pilot sequence, which may be configured for an OFDM mode.

Provided by the present disclosure are a method used for signal transmission, and corresponding user terminals and base stations. The method performed by a user terminal includes: receiving indication information for a spatial-domain reception parameter transmitted by a base station; determining a first spatial-domain reception parameter according to the indication information for a spatial-domain reception parameter, so that the user terminal receives downlink data signals through the first spatial domain reception parameter. The method performed by a base station includes: generating indication information for a spatial-domain reception parameter; and transmitting the indication information for a spatial-domain reception parameter to a user terminal, so that the user terminal determines a first spatial-domain reception parameter according to the indication information for a spatial-domain reception parameter.