## 1 Introduction  
Recently, with the development of the Internet of Things (IoT), the requirements for high spectral efficiency (SE) and energy efficiency (EE) are higher and higher [1]. In communication systems, different popularly used technologies are either designed for sending information on communication channels of mobile devices (including cellular networks, wireless LANs, and Bluetooth) or are designed for power transfer (such as Qi and WiTricity) [2]. Moreover, RF has been regarded as a potential resource for energy harvesting in wireless systems. Since the information and energy are contained simultaneously in RF signals, simultaneous wireless information and power transfer (SWIPT) is presented for the first time in [3], and is regarded as a potential technology, where both information and energy of the common transmit signal are transmitted to the receivers [4; 5]. Therefore, SWIPT has engaged a lot of attention in the research community. SWIPT schemes for single-input single-output (SISO) system have been investigated [3; 6; 7], where the time-switching (TS) scheme and power-splitting (PS) scheme were considered. The study of SWIPT in interference channels is of more practical interest than in non-interference channels. Therefore, many studies on SWIPT addressing the interference channel (IFC) have been done [8; 9; 10; 11; 12; 13; 14; 15; 16]. Two practical architectures at receiver in SWIPT systems are the time-switching (TS) receiver and the power-splitting (PS) receiver [5; 16]. The TS scheme at the receiver switches between information decoding (ID) and energy harvesting (EH) over time, while the PS scheme splits the received signal into two parts, one is implemented for the ID and the other is done for EH. The SWIPT system with a PS scheme has been investigated for solving the minimum transmit power problem [10; 11]. In this paper, we investigate a SWIPT system with multiple single-antenna transmitters and multiple single-antenna receivers. The studied scenario is based on the PS structure. By optimizing transmit power and PS ratios, the power optimization problem is studied under considering of the requirements for SINR and energy harvesting. The system with the PS scheme is similar to the SWIPT system that has been studied in [10], but is studied in a single-input single-output (SISO) SWIPT scenario with IFC. Moreover, our purpose is to open up new research directions with a combination of the two areas of deep learning and optimization problems by taking advantage of deep learning to solve the optimization problems. In wireless communication systems (WCSs), the management and allocation of wireless resources like transmit power must be properly executed in order to obtain high network performance. For example, user equipments (UEs) manage transmit power inefficiently, which can cause a large amount of interference among UEs, and further result in a decrease in network performance. Therefore, the proper allocation of wireless resources is becoming more important with the increase in the popularity of UE density in WCSs. In this work, we also study power problem in WCSs but in a SWIPT system, and we are not too focused on optimization algorithms. In previous researches, transmit power was obtained by solving iterative optimization problems, which had a specified set of network condition parameters such as channel gains and SINR requirements as their input. Those studies ran an entailed number of iterations before achieving convergence, and produced the optimized resource allocation strategy as their output. The iterative optimization algorithms have been efficiently solved the associated resource allocation problems and achieved relatively high performance. However, the iterative nature of these algorithms increases the computation time, which may lead to long latency and high computation costs in real-time operations due to the significant changing of some network parameters, so the entire iterative procedure of the algorithms has to be re-executed.