Abstract: Wireless networks with plural nodes having a respective transceiver and a processor configured to, and methods to, obtain current state data, calculate a reward, store such state data and rewards in a collected parameters database, provide such current state data and data from such collected parameters database to a reinforced neural network, select an action using the reinforced neural network, and output the action to the respective transceiver so as to selective modify its transmit power level.

Abstract: A network control and rate optimization solution for multiuser multiple input multiple output (MU-MIMO) communications in wireless networks. This solution is decentralized and includes scheduling and routing of the MU-MIMO communication links that adapt to dynamic channel, interference, and traffic conditions. The ergodic sum rates of MIMO multiple access channel (MAC) and interference channel (IC) configurations are analyzed by considering the error, and overhead effects due to channel estimation (training) and quantization (feedback). By taking practical considerations such as channel estimation, quantization error and in-network interference into account, the rate gain is shown with an increasing number of antennas compared with single-input single-output (SISO) systems. A distributed channel access protocol to select and activate MU-MIMO configurations is presented with the maximum achievable sum rates using local information on channel, interference, and traffic conditions.

Abstract: Computer and mobile device-based systems and computer-implemented methods are described for automated medication adherence improvement for patients in medication-assisted treatments. The computer and mobile device-based systems includes modules and components to help patients in identifying prescribed medications, logging medication events, and to provide patients with personalized and targeted adherence enhancing interventions consisting of short questions, tips, advices, suggestions, strategies etc. by applying data mining and statistical analysis techniques on the individual and population-level data collected primarily from the same system.