期刊
IEEE INTERNET OF THINGS JOURNAL
卷 7, 期 6, 页码 5401-5411出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2020.2979169
关键词
Resource management; Optimization; Internet of Things; Quality of service; Energy consumption; Transmitting antennas; Energy efficiency maximization; Internet of Things (IoT); Lagrangian dual decomposition; power allocation and user selection
资金
- National Key Research and Development Program [2017YFE0125300]
- National Natural Science Foundation of China-Guangdong Joint Fund [U1801264]
- Jiangsu Key Research and Development Program [BE2019648]
- National Natural Science Foundation of China [61971206, 61773254, U1813217]
- Project of Shanghai Municipal Science and Technology Commission [17DZ1205000]
Internet of Things (IoT) is an emerging networking paradigm that enhances smart device communications through Internet-enabled systems. Due to massive IoT devices connectivity with economic and greenhouse emission effects, the energy-efficiency poses critical concerns. Under imperfect channel state information (CSI), this article investigates joint optimization of user selection, power allocation, and the number of activated base station (BS) antennas of multiple IoT devices considering the transmit power and different Quality-of-Service (QoS) requirements in combinatorial mode to maximize energy-efficiency. The optimization problem formulated is a nonconvex mixed-integer nonlinear programming, which is NP-hard with no practical solution. The primal optimization problem is transformed into a tractable convex optimization problem and separated into inner and outer loop subproblems. This article proposes a joint energy-efficient iterative algorithm, which utilizes a successive convex approximation technique and the Lagrangian dual decomposition method to achieve near-optimal solutions with guaranteed convergence. The simulation results are provided to evaluate the proposed algorithm and its significant performance gain over the baseline algorithms in terms of energy-efficiency maximization.
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