# Prediction of Microwave Characteristic Parameters Based on MMIC Gold Wire Bonding
## 1 Introduction  
Integrated circuits are an integral and important part of electronic products such as smartphones, computers, and robots [1; 2; 3]. The IC industry chain includes design, manufacturing, packaging, and testing, and packaging plays an important role in this field [4; 5]. Gold wire bonding [6; 7; 8] is a special soldering technique that mainly uses gold wire to connect homogeneous or heterogeneous metals, semiconductors, plastics, and ceramics, and is widely used in semiconductor devices and integrated circuit packaging, which is the most versatile and simple and effective method. In microwave chip circuits, each MMCM module has hundreds or even thousands of bonding wires to achieve interconnection between components [9]. X-band T/R components and other microwave multi-chip circuits often use gold wire bonding technology to achieve interconnection between a single microwave integrated circuit chip (MMIC) [10], an application-specific integrated circuit chip (ASIC) and other components. Figure 1 for the group's laboratory design of a microwave multi-chip circuit products, the product internal chip through the bonding alloy wire and the substrate to achieve electrical interconnection, so as to achieve inter-chip information interoperability [11; 12]. Each of these chips and modules, the microwave characteristics of each bonding alloy wire parameters may havean impact on the overall performance. The effect of interconnect wires on microwave transmission is weak and generally negligible in low frequency applications, but as the frequency increases, parameters such as the number of bonding alloy wires, length, arch height, span, and solder joint location, can have a serious impact on the microwave transmission characteristics [13; 14; 15]. Whether the span or the increase in arch height, will lead to an increase in loss, so that the standing wave ratio increases, the forward transmission coefficient decreases transmission performance decreases. Bonding alloy wires are commonly used in the press-soldering process of low power devices and integrated circuit packages due to their advantages of high conductivity, corrosion resistance and good toughness [16]. In the semiconductor manufacturing industry, about one-third of all failures are caused by lead bonding, and the quality of lead bonding plays a very important role in ensuring the proper operation of electronic systems. [PERSON] et al. [17] introduced the development history of gold wire bonding wires, as well as the reliability and basic performance of interconnect wires under different materials. They also compared the application of interconnect wires under three different materials, and finally identified gold wires for interconnecting between chips. Thereafter, [PERSON] et al. [18] proposed the use of finite difference method in time domain (FDTD) to analyze the electromagnetic properties of gold wire bonding. It is now widely used in the calculation of microwave three-dimensional structures, but it requires high computer performance and the calculation is time-consuming. Such methods include trial and error, tuning parameter optimization and parameter scanning, which is a long process [19]. Therefore, in order to solve similar problems and seek an efficient method, deep learning methods benefit us. Currently, deep learning methods have been widely used in various fields. Machine learning has had an impressive impact on sensor data processing through embedded features such as robustness, resolution enhancement in measurement data points, and other applications for analyzing/optimizing sensor data [20]. Methods based on fully connected neural networks (FCNN) have achieved many results in prediction-related tasks [21]. [PERSON] et al. [22] developed a deep learning-based fault diagnosis framework, which can detect the bonding head in the bonding line equipment and determine whether the bonding head is installed correctly to further reduce the cost.