Abstract: A wireless network system includes a base station (BS) having a number of array antennas and a controller. The network system also includes a number of mobile stations (MS) each having its own antenna array. The base station modulates a transmit signal directed to a MS with a transmit beamformer as specified by the controller. The MS equalizes a received signal with a receive beamformer. The controller is configured to calculate an outage probability of the MS based on statistical channel state information at the BS, for a given set of a transmit beamformer wk, a receive beamformer vk, and a predetermined threshold of a signal-to-noise-interference-plus-noise ratio (SINR) at the MS. The controller is also configured to obtain a solution set comprising a transmit beamformer wk and a receive beamformer vk. The controller is further configured to specify, based on the obtained solution set, the beamformers to be adopted.

Abstract: A fractional order Linear Active Disturbance Rejection Control (FOLADRC) system and a method thereof is disclosed. The FOLADRC system includes a fractional order state extended observer (FESO) controller circuit having a FESO controller. The FESO controller receives a process variable and plant output signal, estimates an input disturbance and an output disturbance and outputs disturbance cancelling feedback signals. The disturbance cancelling feedback signals are transmitted to multipliers present in a forward path of the FESO controller circuit. Further, the FESO controller has an observer gain vector and a cross over frequency bandwidth. The FESO controller incrementally changes the observer gain vector and the FESO controller bandwidth until a closed loop transfer function of the FESO controller converges, thus exhibiting an iso-damping property.

Abstract: A method, apparatus, and system of optimizing transmission of data in a power domain non-orthogonal multiple access system is described. The method includes generating a first encoded data stream associated with a first user device, and generating a second encoded data stream associated with a second user device. The method also includes generating a superimposed signal using the first encoded data stream and the second encoded data stream. In addition, the method includes determining a first minimum beam power associated with a first beam vector, and determining a second minimum beam power associated with a second beam vector. The method also includes transmitting the superimposed signal to the first user device at the first minimum beam power, and transmitting the superimposed signal to the second user device at the second minimum beam power.

Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.