Full length articleDesign architecture and algorithm of wireless network integrated circuit based on 5G+AI
Introduction
While the IC industry is developing rapidly, it is also facing more and more design problems. With the continuous shrinking of chips, the design scale of chips is getting larger and larger, and the technical risks are also increasing, which eventually leads to great challenges to the design capabilities of chips. Compared to a few years ago, the level of complexity that existing IC design teams have to deal with has increased by several orders of magnitude. They have to deal with an increasing number of physical effects on packages, power grids, interconnects, devices and substrates. The survey results showed that the current IC design still has a certain lag. That is, the development of IC design capabilities cannot adapt to it. Meanwhile, the emergence of 5G also provides technical support for the design of IC, so that it can adapt to the current application environment. It is very important to study a new type of IC detection with high gain, good gain accuracy and wide common mode voltage range to promote the progress of chip management technology.
Research on the design architecture and algorithms of wireless network integrated circuits has been ongoing. Rth A developed a compact band-stop filter (BSF) with four attenuation narrow bands for multiple wireless network systems [1]. Wu Y studied the channel current magnetic effect of complementary metal–oxide–semiconductor (CMOS) transistors and proposed an improved small-signal equivalent circuit model (SSECM) [2]. Xiu L proposed an emerging frequency synthesis technique featuring small frequency granularity and fast frequency switching as an on-chip integrated synchronizer for periodically adjusting the clock frequency of each node to assist the time synchronization task [3]. Ma C proposed a substrate-integrated gap waveguide (SIGW) sequentially rotated phase (SRP) fed 2 × 2 circularly polarized (CP) patch antenna array for broadband mmWave applications [4]. Ding Q proposed a new combination of wireless and traditional metal interconnects to improve the performance of on-chip clock distribution [5]. Buckley J L presented the design of a tunable 433MHz antenna tailored for wearable wireless sensor applications [6]. The solutions of these studies are not intelligent enough, and the data cannot be received in real time. Therefore, 5G + artificial intelligence is needed to realize it.
Many scholars have conducted research on 5G + artificial intelligence. Ding Z reviewed the recent progress in standardization activities regarding the implementation of non-orthogonal multiple access in LTE and 5G networks [7]. Shafi M outlined 5G research, standardization trials and deployment challenges [8]. Burton E provided practical case studies and links to resources for use by AI educators [9]. The results of these studies did not generalize to the field of electronics, so this paper studies the design architecture and algorithm of wireless network integrated circuits based on 5G + artificial intelligence.
In this paper, the performance of the entire circuit is considered from the perspectives of power consumption, circuit delay, the influence of temperature on the circuit, the size of the output logic “0” level, and the output current. The simulation results are also analyzed. IP circuit migration and IP layout migration are discussed in detail. From the perspective of IP design reuse, the design process of wireless network IC is further improved. The experimental data showed that when the output is low, the total current of the circuit decreases with the increase of temperature. The maximum value of the current was 2.75 mA and the minimum value was 2.59 mA. This quiescent current can meet the design specifications.
Section snippets
Wireless network integrated circuit design
In the actual design, according to the different functional applications of the designed circuit module, a hybrid mode of circuit schematic input and hardware description language can also be used in the design to describe the circuit [10], [11]. Electronic circuit diagram is a kind of diagram that is drawn with agreed symbols to represent the circuit structure for the needs of research and engineering.
The parameter definition of the circuit is an attribute as important as the connection
Circuit simulation and testing
In this paper, the performance of the entire circuit was considered from the perspectives of power consumption, circuit delay, the influence of temperature on the circuit, the size of the output logic “0” level, and the output current. The simulation results were also analyzed.
The relationship between quiescent current and temperature is shown in Fig. 4.
Fig. 4A shows that when the output was low, the total current of the circuit decreased with increasing temperature. The maximum value of the
Conclusions
Digital integrated circuits have achieved rapid development due to the characteristics of small differences in design methodologies, which have been very mature so far. The types of wireless network integrated circuits are relatively complex, and the design process of each type is different. This distinction has greatly hindered the development of the wireless network IC design flow. The content of this paper is to try to further explore the design process of wireless network integrated
Funding
This work was supported by National Key R and D Program of China (No. 2019YFB1600400).
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Pengjun Wang was born in Shaanxi, P.R. China, in 1982. He received the B.S. and Ph.D.degrees from the Department of Electronic Engineering, Tsinghua University, Beijing, China, in 2006 and 2011, respectively. He is currently an Associate Research Scientist with the Department of Electronic Engineering with Tsinghua University. Since 2014, he has also been the CEO of Smartbow Tech., Inc. His recent research mainly focuses on wireless sensor networks and structural health monitoring.
E-mail: [email protected]
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Pengjun Wang was born in Shaanxi, P.R. China, in 1982. He received the B.S. and Ph.D.degrees from the Department of Electronic Engineering, Tsinghua University, Beijing, China, in 2006 and 2011, respectively. He is currently an Associate Research Scientist with the Department of Electronic Engineering with Tsinghua University. Since 2014, he has also been the CEO of Smartbow Tech., Inc. His recent research mainly focuses on wireless sensor networks and structural health monitoring.
E-mail: [email protected].
Jiahao Qin received a B.S. degree in 2019 from the Department of Electronic Engineering, Tsinghua University, Beijing, China. He is currently pursuing a M.E degree under the supervisor of Dr. Pengjun Wang. His recent research mainly focuses on the Internet of Things, prognostics health management and machine learning.
E-mail: [email protected].
Jiucheng Li was born in Heilongjiang, P.R. China, in 1999. He received the B.E. degree from the Department of Electrical Engineering, Tsinghua University, Beijing, China, in 2021. He is studying for a master’s degree at the Department of Electronic Engineering, Tsinghua University. His recent research mainly focuses on time series data processing and data compression.
E-mail: [email protected].
Meng Wu was born in Beijing, P.R. China, in 1984. He received the B.S. and Master’s degrees from the Department of Electronic Engineering, Tsinghua University, Beijing, China, in 2006 and 2009, respectively. He has been worked as an engineer and architect for Tencent, Yahoo Global Beijing R&D, and Umeng which was acquired by Alibaba. He mainly works on big data platforms, data mining, and advertising recommendation algorithms. Since 2019, he has also been the CTO of Smartbow Tech, Inc. His recent research mainly focuses on IoT platforms and structural health monitoring.
E-mail: [email protected].
Shan Zhou was born in Beijing, P.R. China in 1984. He received his B.E. and M.S. degree in Automation from Tsinghua University, Beijing, China, and his Ph.D. in Electrical Engineering from Arizona State University, United States. He is currently VP of Engineering of Smartbow Tech., Inc. His work is broadly in the interplay of large distributed system, big data, machine learning and IoT.
E-mail: [email protected].
Le Feng received a B.S. degree in 2014 from the School of Information Science and Engineering, Yanshan University, Qinhuangdao, China. Since 2014, he has been an engineer in Smartbow Tech. His recent work mainly focuses on the Internet of Things.
E-mail: [email protected].