Recognition of activities of daily living

Activities of daily living (ADL) are things we normally do in daily living, including any daily activity such as feeding ourselves, bathing, dressing, grooming, work, homemaking, and leisure. The ability or inability to perform ADLs can be used as a very practical measure of human capability in many types of disorder and disability. Oftentimes in a health care facility, with the help of observations by nurses and self-reporting by residents, professional staff manually collect ADL data and enter data into the system. Technologies in smart homes can provide some solutions to detecting and monitoring a resident’s ADL. Typically multiple sensors can be deployed, such as surveillance cameras in the smart home environment, and contacted sensors affixed to the resident’s body. Note that the traditional technologies incur costly and laborious sensor deployment, and cause uncomfortable feeling of contacted sensors with increased inconvenience. This work presents a novel system facilitated via mobile devices to collect and analyze mobile data pertaining to the human users’ ADL. By employing only one smart phone, this system, named ADL recognition system, significantly reduces set-up costs and saves manpower. It encapsulates rather sophisticated technologies under the hood, such as an agent-based information management platform integrating both the mobile end and the cloud, observer patterns and a time-series based motion analysis mechanism over sensory data. As a single-point deployment system, ADL recognition system provides further benefits that enable the replay of users’ daily ADL routines, in addition to the timely assessment of their life habits

UAV Swarm-Enabled Aerial CoMP: A Physical Layer Security Perspective

Unlike aerial base station enabled by a single unmanned aerial vehicle (UAV), aerial coordinated multiple points (CoMP) can be enabled by a UAV swarm. In this case, the management of multiple UAVs is important. This paper considers the power allocation strategy for a UAV swarm-enabled aerial network to enhance the physical layer security of the downlink transmission, where an eavesdropper moves following the trajectory of the swarm for better eavesdropping. Unlike existing works, we use only the large-scale channel state information (CSI) and maximize the secrecy throughput in a whole-trajectory-oriented manner. The overall transmission energy constraint on each UAV and the total transmission duration for all the legitimate users are considered. The non-convexity of the formulated problem is solved by using max-min optimization with iteration. Both the transmission power of desired signals and artificial noise (AN) are derived iteratively. Simulation results are presented to validate the effectiveness of our proposed power allocation algorithm and to show the advantage of aerial CoMP by using only the large-scale CSI

Joint radar-communication waveform designs using signals from multiplexed users

Joint radar-communication designs are exploited in applications where radar and communications systems share the same frequency band or when both radar sensing and information communication functions are required in the same system. Finding a waveform that is suitable for both radar and communication is challenging due to the difference between radar and communication operations. In this paper, we propose a new method of designing dual-functional waveforms for both radar and communication using signals from multiplexed communications users. Specifically, signals from different communications users multiplexed in the time, code or frequency domains across different data bits are linearly combined to generate an overall radar waveform. Three typical radar waveforms are considered. The coefficients of the linear combination are optimized to minimize the mean squared error with or without a constraint on the signal-to-noise ratio (SNR) for the communications signals. Numerical results show that the optimization without SNR constraint can almost perfectly approximate the radar waveform in all the cases considered, giving good dual-functional waveforms for both radar and communication. Also, among different multiplexing techniques, time division multiple access is the best option to approximate the radar waveform, followed by code division multiple access and orthogonal frequency division multiple access

Maritime coverage enhancement using UAVs coordinated with hybrid satellite-terrestrial networks

Due to the agile maneuverability, unmanned aerial vehicles (UAVs) have shown great promise for on-demand communications. In practice, UAV-aided aerial base stations are not separate. Instead, they rely on existing satellites/terrestrial systems for spectrum sharing and efficient backhaul. In this case, how to coordinate satellites, UAVs and terrestrial systems is still an open issue. In this paper, we deploy UAVs for coverage enhancement of a hybrid satellite-terrestrial maritime communication network. Using a typical composite channel model including both large-scale and small-scale fading, the UAV trajectory and in-flight transmit power are jointly optimized, subject to constraints on UAV kinematics, tolerable interference, backhaul, and the total energy of the UAV for communications. Different from existing studies, only the location-dependent large-scale channel state information (CSI) is assumed available, because it is difficult to obtain the small-scale CSI before takeoff in practice and the ship positions can be obtained via the dedicated maritime Automatic Identification System. The optimization problem is non-convex. We solve it by using problem decomposition, successive convex optimization and bisection searching tools. Simulation results demonstrate that the UAV fits well with existing satellite and terrestrial systems, using the proposed optimization framework

Optimal Beamforming for Hybrid Satellite Terrestrial Networks with Nonlinear PA and Imperfect CSIT

In hybrid satellite-terrestrial networks (HSTNs), spectrum sharing is crucial to alleviate the "spectrum scarcity" problem. Therein, the transmit beams should be carefully designed to mitigate the inter-satellite-terrestrial interference. Different from previous studies, this work considers the impact of both nonlinear power amplifier (PA) and large-scale channel state information at the transmitter (CSIT) on beamforming. These phenomena are usually inevitable in a practical HSTN. Based on the Saleh model of PA nonlinearity and the large-scale multi-beam satellite channel parameters, we formulate a beamforming optimization problem to maximize the achievable rate of the satellite system while ensuring that the inter-satellite-terrestrial interference is below a given threshold. The optimal amplitude and phase of desired beams are derived in a decoupled manner. Simulation results demonstrate the superiority of the proposed beamforming scheme.Comment: 5 pages, 5 figures, journa