Power allocation method in power domain NOMA based on reinforcement learning algorithm

A technology of reinforcement learning and distribution method, applied in the field of wireless communication, can solve the problems that the optimized system performance cannot achieve good results and the complexity is high

Inactive Publication Date: 2018-11-30
NORTHWESTERN POLYTECHNICAL UNIV
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Problems solved by technology

[0009] The purpose of the present invention is to provide a power allocation method in NOMA based on the power domain of the reinforcement learning algorithm to solve the problem that the existing medium power allocation method has high complexity and cannot achieve good results in optimizing the performance of the system

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  • Power allocation method in power domain NOMA based on reinforcement learning algorithm
  • Power allocation method in power domain NOMA based on reinforcement learning algorithm
  • Power allocation method in power domain NOMA based on reinforcement learning algorithm

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[0060] The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0061] The present invention provides a power allocation method in NOMA based on the reinforcement learning algorithm power domain, such as figure 1 As shown, the model is established based on the downlink of a single-cell wireless cellular network. It is assumed that there is a single base station and K users, and all terminals are equipped with a single antenna. The base station transmits data to all users under the constraint of total power. Classify channels as 01 | 2 2 | 2 K | 2 , where h i (1

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Abstract

The invention discloses a power allocation method in a power domain NOMA based on a reinforcement learning algorithm. Value function update is performed on a Critic part in an Actor-Critic algorithm,and then, an instant reward and a time difference error are fed back into an Actor part in the Actor-Critic algorithm to perform strategy update; and through continuous iteration, a state action valuefunction and a strategy finally tend to the optimal value function and the optimal strategy at last, the energy efficiency of the system is optimal at the moment, and the problems that the complexityof the existing power allocation method is high and that a good effect cannot be achieved on the optimization of the performance of the system are solved.

Description

【Technical field】 [0001] The invention belongs to the technical field of wireless communication, and in particular relates to a power allocation method in NOMA based on a reinforcement learning algorithm power domain. 【Background technique】 [0002] With the popularization and application of smart terminals and the continuous growth of new mobile service demands, the demand for wireless transmission rate is increasing exponentially, and the transmission rate of wireless communication will still be difficult to meet the application requirements of future mobile communications. Based on the 4G network, the 5G network is positioned as a wireless network with higher spectral efficiency, faster rate, and larger capacity. Therefore, the industry proposes to use non-orthogonal multiple access (NOMA) to improve spectral efficiency. The NOMA method can allocate one resource to multiple users, so NOMA plays an important role in providing large system throughput, high reliability, low ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W72/04G06N99/00
CPCH04W72/0473H04W72/53Y02D30/70
Inventor 李立欣张少敏梁微李旭高昂
Owner NORTHWESTERN POLYTECHNICAL UNIV
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