Fall Detection using Wi-Fi Signals and Threshold-Based Activity Segmentation

Low latency communications is one of the key design targets in future wireless networks. We propose a queue aware algorithm to optimize resources guaranteeing low latency in multiple-input single-output (MISO) networks. Proposed system model is based on dynamic network architecture (DNA), where some terminals can be configured as temporary access points (APs) on demand when connected to the Internet. Therein, we jointly optimize the user-AP association and queue weighted sum rate of the network, subject to limitations of total transmit power of the APs and minimum delay requirements of the users. The user-AP association is viewed as finding a sparsity constrained solution to the problem of minimizing ℓ q -norm of the difference between queue and service rate of users. Finally, the efficacy of the proposed algorithm in terms of network latency and its fast convergence are demonstrated using numerical experiments. Simulation results show that the proposed algorithm yields up to two-fold latency reductions compared to the state-of-the-art techniques.