Confidence interval based model predictive control of transmit power with reliability constraint
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Because the wireless signal, such as 5G, is propagated in the medium of air, it is easily been interfered by other devices or environmental factors. Adjusting the transmit power of wireless transceiver could control the signal-to-noise ratio (SNR) and accordingly improves the reliability of communication. However, the control of stochastic SNR with deterministic requirements is still a challenging problem. Hence we study the control of transmit power to satisfy the reliability requirements and, in the meanwhile, save battery energy. To deal with the stochastic character of the wireless link, we introduce the confidence interval bound and then propose confidence interval based model predictive control (CI-MPC), in which we creatively separated the SNR as the feedback signal and the confidence interval based compensating signal. To verify the performance of our CI-MPC, we compared it with the state-of-the-art methods by simulation. Besides, we also tested the proposed CI-MPC method in the real-world industrial environment on the test-bed to show its effectiveness.
KeywordsTransmit power control Confidence interval Model predictive control Wireless communication reliability Internet of things
This work was supported by National Natural Science Foundation of China (51877060), the Fundamental Research Funds for the Central Universities of China (PA2019GDQT0006 and JZ2018HGTB0253), and the Science and Technology Project of State Grid “Research and application of key Technologies for operation and maintenance of smart substation based on the fusion of heterogeneous network and data”.
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