Energy-Efficient Resource Allocation for Dynamic Priority-Based Vehicular Mobile-Health Communications

Abstract

Owing to the developments of wireless communication technologies, mobile health (M-Health) has been postulated as a promising means to improve healthcare quality and save lives in emergencies. However, using wireless communications in M-Health faces the following challenges. First, the wireless transmission may generate electromagnetic interference (EMI) and trigger critical malfunctions to the medical devices. Second, different types of M-Health applications and time-varying patient conditions require dynamic quality of service (QoS). Third, energy efficiency (EE) should be optimized to guarantee the reliability of M-Health services, considering the limitations of the existing battery technologies. To address these challenges, this paper investigates the joint channel and power resource allocation problem for vehicular M-Health communications. The problem is formulated as a mixed-integer nonlinear program (MINLP) to maximize the system EE with the consideration of EMI constraints on medical equipment and dynamic QoS requirements of medical users. To find possible solutions, we reformulate the MINLP problem by relaxing the integer variables and transforming the objective to convex forms. Based on the dual-decomposition method, we first obtain the optimal power allocation and then recover the channel allocation variables to integers. To satisfy the QoS requirements, we develop two channel allocation strategies, i.e., the QoS fulfillment strategy and the QoS compensation strategy. The swap-blocking allocation concept is introduced to guarantee the optimality of the obtained solutions. Simulation results show that the proposed resource allocation scheme improves the system EE and service satisfaction degree.