Achievable Rate Maximization for IRS-Assisted System With Relay Cooperation of IoT Network

The further integration of emerging technologies such as artificial intelligence (AI), mobile edge computing (MEC), blockchain, have recently emerged as a powerful weapon with the Internet of Things (IoT). A data-centric IoT network is particularly important for ensuring data and privacy security. Based on this, this paper proposes a secure IoT framework that integrates these technologies to enable the system to work efficiently. With the further transformation of IoT, the system puts forward higher requirements on the data rate to support real-time and reliable connection. Based on the trade-off between energy efficiency and data rate, this paper develops the data transmission of IoT system driven by intelligent reflective surface (IRS). At the same time, considering the widespread existence of relay nodes in the future wireless network, the optimal relay nodes from the surrounding environment are considered to cooperate with IRS communication. The achievable rate maximization problem of IoT system is constructed and the objective problem is solved by semi-definite relaxation (SDR) and alternate optimization (AO) algorithm. The simulation results show that the two algorithms approximate the upper bound of the achievable rate, and the effectiveness of the proposed scheme is proved by comparing with other benchmark schemes.