Cost Minimization for Remote Health Monitoring Under Delay and Reliability Constraints

Recently, the pandemic of Coronavirus disease 2019 (COVID-19) highlights the great potential of remote health for resisting infectious diseases. The remote healthcare methodologies have achieved significant development based on reliable and low-latency transmissions of 5G. In remote health monitoring, the Internet of Things (IoT)-based physical monitoring devices need to transmit collected physical data in a real time and highly reliable manner to ensure accurate monitoring of patients. However, due to the unreliability of wireless link and the latency of data queue, it is a challenging issue to achieve high reliability communication and low delay transmission at the same time. Meanwhile, the available bandwidth is limited and the cost of renting spectrum is not negligible. Thus, it is essential for the devices to reduce communication costs while ensuring the efficient data transmission. Toward this end, our goal is to minimize the total costs of leasing bandwidth by jointly optimizing the access link and backhaul transmission, subject to the delay and reliability constraints. Considering the requirements of access link and queue together, a cost minimization problem is formulated, which is non-linear and non-convex and is hard to solve straightforwardly. Through problem equivalent transforming, a gradient descent-based algorithm is proposed to find a suboptimal solution. Simulation results validate the performance through cost, reliability, delay and those under harsh conditions.