Cross-Layer Optimization-Based Asymmetric Medical Video Transmission in IoT Systems

Abstract

At present, Internet of Things (IoT) networks are attracting much attention since they provide emerging opportunities and applications. In IoT networks, the asymmetric and symmetric studies on medical and biomedical video transmissions have become an interesting topic in both academic and industrial communities. Especially, the transmission process shows the characteristics of asymmetry: the symmetric video-encoding and -decoding processes become asymmetric (affected by modulation and demodulation) once a transmission error occurs. In such an asymmetric condition, the quality of service (QoS) of such video transmissions is impacted by many different factors across the physical (PHY-), medium access control (MAC-), and application (APP-) layers. To address this, we propose a cross-layer optimization-based strategy for asymmetric medical video transmission in IoT systems. The proposed strategy jointly utilizes the video-coding structure in the APP- layer, the power control and channel allocation in the MAC- layer, and the modulation and coding schemes in the PHY- layer. To obtain the optimum configuration efficiently, the proposed strategy is formulated and proofed by a quasi-convex problem. Consequently, the proposed strategy could not only outperform the classical algorithms in terms of resource utilization but also improve the video quality under the resource-limited network efficiently.