Resource allocation method of energy-carrying NOMA system based on deep learning

• Main Authors: TANG HENGBIN, SU ZHIJIE, TANG JIE, LUO JINGCI, FENG WANMEI, SONG JINGRU
• Format: Patent
• Language: Chinese; English
• Published: 09.08.2019
• Subjects: ELECTRIC COMMUNICATION TECHNIQUE; ELECTRICITY; TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION

The invention discloses a resource allocation method of an energy-carrying NOMA system based on deep learning. The resource allocation method comprises the following steps: (1) constructing a mathematical optimization problem of joint resource allocation based on minimum transmitting power in the energy-carrying NOMA system; and (2) designing a joint resource allocation strategy based on a deep learning algorithm. Aiming at an energy-carrying NOMA system, starting from the perspective of energy conservation, the mathematical optimization problem for minimum transmitting power is constructed under the condition that the Quality of Service (QoS) demand and the transmission power constraint are met;, and a joint resource allocation strategy based on a deep learning algorithm is designed, so that low-power-consumption resource allocation is realized, and the requirement for low time delay is better met. 本发明公开了一种基于深度学习的携能NOMA系统的资源分配方法，包括以下步骤：(1)构建携能NOMA系统中基于发射功率最小化的联合资源分配的数学优化问题；(2)设计基于深度学习算法的联合资源分配策略。本发明针对携能NOMA系