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November 24, 2017IEEE Journal on Selected Areas in Communications305 citations

Joint User Scheduling and Power Allocation Optimization for Energy-Efficient NOMA Systems With Imperfect CSI

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FFFang FangHZHaijun ZhangJCJulian Cheng

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Abstract

Non-orthogonal multiple access (NOMA) exploits successive interference cancellation technique at the receivers to improve the spectral efficiency. By using this technique, multiple users can be multiplexed on the same subchannel to achieve high sum rate. Most previous research works on NOMA systems assume perfect channel state information (CSI). However, in this paper, we investigate energy efficiency improvement for a downlink NOMA single-cell network by considering imperfect CSI. The energy efficient resource scheduling problem is formulated as a non-convex optimization problem with the constraints of outage probability limit, the maximum power of the system, the minimum user data rate, and the maximum number of multiplexed users sharing the same subchannel. Different from previous works, the maximum number of multiplexed users can be greater than two, and the imperfect CSI is first studied for resource allocation in NOMA. To efficiently solve this problem, the probabilistic mixed problem is first transformed into a non-probabilistic problem. An iterative algorithm for user scheduling and power allocation is proposed to maximize the system energy efficiency. The optimal user scheduling based on exhaustive search serves as a system performance benchmark, but it has high computational complexity. To balance the system performance and the computational complexity, a new suboptimal user scheduling scheme is proposed to schedule users on different subchannels. Based on the user scheduling scheme, the optimal power allocation expression is derived by the Lagrange approach. By transforming the fractional-form problem into an equivalent subtractive-form optimization problem, an iterative power allocation algorithm is proposed to maximize the system energy efficiency. Simulation results demonstrate that the proposed user scheduling algorithm closely attains the optimal performance.

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Cite This Study

Fang et al. (2017) studied this question.

synapsesocial.com/papers/69d70b8e8dca315383ed985bhttps://doi.org/10.1109/jsac.2017.2777672
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