Providing statistical QoS guarantees in large cognitive machine-to-machine networks

Promising machine-to-machine (M2M) communication emerges to achieve ubiquitous communications among objects and the surrounding environment in everyday life. For a large M2M network to support scrupulous connections among abundant devices, sharing radio resource efficiently with the existing wireless networks while maintaining sufficient quality-of-service (QoS) for reliable communications becomes an essential and challenging requirement. Via social network analysis, we provide mathematical examination on network connectivity and network diameter. Upon such connected M2M networks, an opportunistic transmission protocol is proposed for spectrum-efficient communications by leveraging cognitive radio technology with cooperative communication. Specifically, the cognitive machines can autonomously sense the radio resource usage to mitigate interference and exploit opportunistic relay selection with lower link delay for packet transmissions. Under this protocol, analytical bound of end-to-end delay is derived and the corresponding QoS guaranteed throughput is examined for practical applications. Simulation results confirm that the proposed protocol successfully accommodates statistical QoS guarantees, to facilitate a new paradigm for dependable data transportation in large M2M communication networks.