Pub Date : 2024-12-03DOI: 10.1109/OJCAS.2024.3509746
Bangda Yang;Trevor Caldwell;Anthony Chan Carusone
Recently, dynamic amplifier (DA) has emerged as a popular alternative to static current closed-loop operational transconductance amplifier (OTA) due to their highly power-efficient integration-based settling, with the main limitation being their linearity performance. We present a DA that achieves −52 dB in total harmonic distortion (THD) through an analog technique by which the expanding and compressing nonlinearities in the input transistors cancel one another. A pipeline-SAR analog-to-digital converter (ADC) incorporating the linearized DA in both the input buffer and the first residue amplifier (RA) stage was designed and fabricated using the GlobalFoundries 22nm fully depleted silicon-on-insulator (FDSOI) process. Measurements showed the ADC achieved a signal-to-noise-distortion ratio (SNDR) of 37 dB at 920 MS/s consuming a total power of 1.8mW for a Walden FOM (FOMW) of 34.9 fJ/conv. With the input buffer, the achieved FOMW is 68.4 fJ/conv. The linearization technique provided a 8 dB improvement in SNDR at its optimal biasing with a negligible power overhead of approximately 5%. In general, it is expected that an 8 dB SNDR improvement would require 2.5 times the power consumption for a mismatch-limited design (Walden FOM) or 6.3 times the power for a noise-limited design (Schreier FOM).
近年来,动态放大器(DA)由于其基于集成的高能效解决方案而成为静态电流闭环运算跨导放大器(OTA)的热门替代方案,但其主要限制是其线性性能。我们提出了一种通过模拟技术实现- 52 dB总谐波失真(THD)的DA,通过这种模拟技术,输入晶体管中的扩展和压缩非线性相互抵消。采用GlobalFoundries的22nm完全耗尽绝缘体上硅(FDSOI)工艺,设计并制造了一种在输入缓冲器和第一残留放大器(RA)级均采用线性化DA的管道sar模数转换器(ADC)。测量结果表明,该ADC在920 MS/s下的信噪比(SNDR)为37 dB,消耗的总功率为1.8mW, Walden form (FOMW)为34.9 fJ/conv。使用输入缓冲器,实现的FOMW为68.4 fJ/conv。在最佳偏置下,线性化技术提供了8db的SNDR改进,而功率开销约为5%,可以忽略不计。一般来说,预计8 dB SNDR的改进将需要限制失配设计(Walden FOM)的2.5倍功耗或限制噪声设计(Schreier FOM)的6.3倍功耗。
{"title":"An Energy-Efficient Pipeline-SAR ADC Using Linearized Dynamic Amplifiers and Input Buffer in 22nm FDSOI","authors":"Bangda Yang;Trevor Caldwell;Anthony Chan Carusone","doi":"10.1109/OJCAS.2024.3509746","DOIUrl":"https://doi.org/10.1109/OJCAS.2024.3509746","url":null,"abstract":"Recently, dynamic amplifier (DA) has emerged as a popular alternative to static current closed-loop operational transconductance amplifier (OTA) due to their highly power-efficient integration-based settling, with the main limitation being their linearity performance. We present a DA that achieves −52 dB in total harmonic distortion (THD) through an analog technique by which the expanding and compressing nonlinearities in the input transistors cancel one another. A pipeline-SAR analog-to-digital converter (ADC) incorporating the linearized DA in both the input buffer and the first residue amplifier (RA) stage was designed and fabricated using the GlobalFoundries 22nm fully depleted silicon-on-insulator (FDSOI) process. Measurements showed the ADC achieved a signal-to-noise-distortion ratio (SNDR) of 37 dB at 920 MS/s consuming a total power of 1.8mW for a Walden FOM (FOMW) of 34.9 fJ/conv. With the input buffer, the achieved FOMW is 68.4 fJ/conv. The linearization technique provided a 8 dB improvement in SNDR at its optimal biasing with a negligible power overhead of approximately 5%. In general, it is expected that an 8 dB SNDR improvement would require 2.5 times the power consumption for a mismatch-limited design (Walden FOM) or 6.3 times the power for a noise-limited design (Schreier FOM).","PeriodicalId":93442,"journal":{"name":"IEEE open journal of circuits and systems","volume":"6 ","pages":"50-62"},"PeriodicalIF":2.4,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10774063","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-03DOI: 10.1109/OJCAS.2024.3509627
Andrew Maclellan;Louise H. Crockett;Robert W. Stewart
This paper introduces a novel FPGA-based Convolutional Neural Network (CNN) architecture for continuous radio data processing, specifically targeting modulation classification on the Zynq UltraScale+ Radio Frequency System on Chip (RFSoC) operating in real-time. Evaluated on AMD’s RFSoC2x2 development board, the design integrates General Matrix Multiplication (GEMM) optimisations and fixed-point arithmetic. We also present a method for creating Deep Learning (DL) data sets for wireless communications, incorporating the RFSoC into the data generation loop. Furthermore, we explore quantised-aware training, producing three modulation classification models with different fixed-point weight precisions (16-bit, 8-bit, and 4-bit). We interface with the implemented hardware through the open-source PYNQ project, which combines Python with programmable logic interaction, enabling real-time modulation prediction via a PYNQ-enabled Jupyter app. The three models, operating at a 128 MHz sampling rate prior to the decimation stage, were evaluated for accuracy and resource consumption. The 16-bit model achieved the highest accuracy with minimal additional resource usage compared to the 8-bit and 4-bit models, making it the optimal choice for deploying a modulation classifier at the receiver.
{"title":"RFSoC Modulation Classification With Streaming CNN: Data Set Generation & Quantized-Aware Training","authors":"Andrew Maclellan;Louise H. Crockett;Robert W. Stewart","doi":"10.1109/OJCAS.2024.3509627","DOIUrl":"https://doi.org/10.1109/OJCAS.2024.3509627","url":null,"abstract":"This paper introduces a novel FPGA-based Convolutional Neural Network (CNN) architecture for continuous radio data processing, specifically targeting modulation classification on the Zynq UltraScale+ Radio Frequency System on Chip (RFSoC) operating in real-time. Evaluated on AMD’s RFSoC2x2 development board, the design integrates General Matrix Multiplication (GEMM) optimisations and fixed-point arithmetic. We also present a method for creating Deep Learning (DL) data sets for wireless communications, incorporating the RFSoC into the data generation loop. Furthermore, we explore quantised-aware training, producing three modulation classification models with different fixed-point weight precisions (16-bit, 8-bit, and 4-bit). We interface with the implemented hardware through the open-source PYNQ project, which combines Python with programmable logic interaction, enabling real-time modulation prediction via a PYNQ-enabled Jupyter app. The three models, operating at a 128 MHz sampling rate prior to the decimation stage, were evaluated for accuracy and resource consumption. The 16-bit model achieved the highest accuracy with minimal additional resource usage compared to the 8-bit and 4-bit models, making it the optimal choice for deploying a modulation classifier at the receiver.","PeriodicalId":93442,"journal":{"name":"IEEE open journal of circuits and systems","volume":"6 ","pages":"38-49"},"PeriodicalIF":2.4,"publicationDate":"2024-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10772713","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a comprehensive analysis of nonlinearities in differential pairs with source degeneration and their impact on wireline communication applications. We assess the suitability of three nonlinearity metrics to quantify the receiver analog front-end performance. This work identifies the primary sources of nonlinearity in differential pair circuits including, broadband Variable Gain Amplifiers (VGAs) and Continuous-Time Linear Equalizers (CTLEs) using circuit simulations. Furthermore, the linearity performance of different front-end configurations is evaluated, providing design insights. The analysis is validated through simulations with a 22-nm FDSOI technology.
{"title":"Linearity Analysis of Source-Degenerated Differential Pairs for Wireline Applications","authors":"Kunal Yadav;Ping-Hsuan Hsieh;Anthony Chan Carusone","doi":"10.1109/OJCAS.2024.3507543","DOIUrl":"https://doi.org/10.1109/OJCAS.2024.3507543","url":null,"abstract":"This paper presents a comprehensive analysis of nonlinearities in differential pairs with source degeneration and their impact on wireline communication applications. We assess the suitability of three nonlinearity metrics to quantify the receiver analog front-end performance. This work identifies the primary sources of nonlinearity in differential pair circuits including, broadband Variable Gain Amplifiers (VGAs) and Continuous-Time Linear Equalizers (CTLEs) using circuit simulations. Furthermore, the linearity performance of different front-end configurations is evaluated, providing design insights. The analysis is validated through simulations with a 22-nm FDSOI technology.","PeriodicalId":93442,"journal":{"name":"IEEE open journal of circuits and systems","volume":"6 ","pages":"26-37"},"PeriodicalIF":2.4,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10769573","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a generalized control architecture for implementing the active balancing of the flying capacitor voltage in any kind of 3-level switching-mode DC-DC converters, independently from the desired conversion ratio or targeted output power level. The proposed strategy is based on the detection of the flying capacitor voltage through the inductor voltage, sensed at the switching node, and acts on the duty cycle of the PWM (Pulse Width Modulation) control signals in order to make the correction, implementing the voltage balancing. The circuit implementation and its operation are described in detail. Extensive simulations were performed in the SIMPLIS environment, taking as examples the cases of a 3-level buck, 3-level boost and 3-level inverting buck-boost DC-DC converter and considering different combinations of input voltage, output voltage and load current. Moreover, the proposed strategy was implemented in the control architecture of a hybrid switched-capacitor 3-level inverting buck-boost converter, fabricated in a 180-nm BCD process. The effectiveness and the versatility of the proposed active voltage balancing strategy and its circuit implementation were, therefore, verified both through simulations and experimentally.
{"title":"A Generalized Active Voltage Balancing Circuit Implementation for Flying Capacitor 3-Level Switching-Mode DC–DC Converters","authors":"Elisabetta Moisello;Samuele Fusetto;Piero Malcovati;Edoardo Bonizzoni","doi":"10.1109/OJCAS.2024.3492320","DOIUrl":"https://doi.org/10.1109/OJCAS.2024.3492320","url":null,"abstract":"This paper presents a generalized control architecture for implementing the active balancing of the flying capacitor voltage in any kind of 3-level switching-mode DC-DC converters, independently from the desired conversion ratio or targeted output power level. The proposed strategy is based on the detection of the flying capacitor voltage through the inductor voltage, sensed at the switching node, and acts on the duty cycle of the PWM (Pulse Width Modulation) control signals in order to make the correction, implementing the voltage balancing. The circuit implementation and its operation are described in detail. Extensive simulations were performed in the SIMPLIS environment, taking as examples the cases of a 3-level buck, 3-level boost and 3-level inverting buck-boost DC-DC converter and considering different combinations of input voltage, output voltage and load current. Moreover, the proposed strategy was implemented in the control architecture of a hybrid switched-capacitor 3-level inverting buck-boost converter, fabricated in a 180-nm BCD process. The effectiveness and the versatility of the proposed active voltage balancing strategy and its circuit implementation were, therefore, verified both through simulations and experimentally.","PeriodicalId":93442,"journal":{"name":"IEEE open journal of circuits and systems","volume":"5 ","pages":"365-376"},"PeriodicalIF":2.4,"publicationDate":"2024-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10745640","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142672080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, we propose a correlation-based background linearity calibration technique to digitally correct the bit weights in successive approximation register (SAR)-assisted analog-to-digital converters (ADCs). Unlike typical dithering-based calibration techniques in which signal dynamic range (DR) is unavoidably reduced, in this work, a small dither signal is injected into the input path by a simple switching scheme. The associated DR loss is avoided by the back-end redundancy. We also describe a capacitor-scanning dither method to accomplish simultaneous and independent identification of multiple bit weights. In addition, a digital-domain input-interference cancellation (IIC) technique is proposed to accelerate the convergence speed of the correlation-based calibration. The proposed calibration and acceleration techniques are analyzed by using both theoretical formulation and system simulation. The simulation results are presented with a 12-bit SAR-assisted two-stage pipeline ADC model. Owing to our proposed calibration, the spurious-free dynamic range (SFDR) increased from 60.1 to 84.8 dB and the signal to noise and distortion ratio (SNDR) improved from 55.4 to 72.5 dB. By comparing the cases with and without the proposed IIC technique, a $50times $