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Analysis of 3D NAND technologies and comparison between charge-trap-based and floating-gate-based flash devices
JOURNAL OF CHINA UNIVERSITIES OF POSTS AND TELECOM    2017, 24 (3): 75-82.   DOI: 10.1016/S1005-8885(17)60214-0
Abstract876)      PDF(pc) (1498KB)(1506)       Save
NAND flash chips have been innovated from two-dimension (2D) design which is based on planar NAND cells to three-dimension (3D) design which is based on vertical NAND cells. Two types of NAND flash technologies–charge-trap (CT) and floating-gate (FG) are presented in this paper to introduce NAND flash designs in detail. The physical characteristics of CT-based and FG-based 3D NAND flashes are analyzed. Moreover, the advantages and disadvantages of these two technologies in architecture, manufacture, interference and reliability are studied and compared.
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Superjunction 4H-SiC trench-gate IGBT with an integrated clamping PN diode
The Journal of China Universities of Posts and Telecommunications    2024, 31 (2): 3-9.   DOI: 10.19682/j.cnki.1005-8885.2024.0001
Abstract82)      PDF(pc) (4079KB)(49)       Save

In this paper, a novel superjunction 4H-silicon carbide (4H-SiC) trench-gate insulated-gate bipolar transistor (IGBT) featuring an integrated clamping PN diode between the P-shield and emitter (TSD-IGBT) is designed and theoretically studied. The heavily doping superjunction layer contributes to a low specific on-resistance, excellent electric field distribution, and quasi-unipolar drift current. The anode of the clamping diode is in floating contact with the P-shield. In the on-state, the potential of the P-shield is raised to the turn-on voltage of the clamping diode, which prevents the hole extraction below the N-type carrier storage layer (NCSL). Additionally, during the turn-off transient, once the clamping diode is turned on, it also promotes an additional hole extraction path. Furthermore, the potential dropped at the semiconductor near the trench-gate oxide is effectively reduced in the off-state.

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Dynamic computation offloading in time-varying environment for  ultra-dense networks: a stochastic game approach
Xie Renchao, Liu Xu, Duan Xuefei, Tang Qinqin, Yu Fei Richard, Huang Tao
The Journal of China Universities of Posts and Telecommunications    2021, 28 (2): 24-37.   DOI: 10.19682/j.cnki.1005-8885.2021.1003
Abstract312)      PDF(pc) (3234KB)(297)       Save
To meet the demands of large-scale user access with computation-intensive and delay-sensitive applications,
combining ultra-dense networks (UDNs) and mobile edge computing (MEC)are considered as important solutions.
In the MEC enabled UDNs, one of the most important issues is computation offloading. Although a number of work
have been done toward this issue, the problem of dynamic computation offloading in time-varying environment,
especially the dynamic computation offloading problem for multi-user, has not been fully considered. Therefore, in
order to fill this gap, the dynamic computation offloading problem in time-varying environment for multi-user is
considered in this paper. By considering the dynamic changes of channel state and users queue state, the dynamic
computation offloading problem for multi-user is formulated as a stochastic game, which aims to optimize the delay
and packet loss rate of users. To find the optimal solution of the formulated optimization problem, Nash 
Q-l earning
(NQLN) algorithm is proposed which can be quickly converged to a Nash equilibrium solution. Finally, extensive
simulation results are presented to demonstrate the superiority of NQLN algorithm. It is shown that NQLN algorithm
has better optimization performance than the benchmark schemes.
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Meta-heuristic optimization inspired by proton-electron swarm
The Journal of China Universities of Posts and Telecommunications    2020, 27 (3): 42-52.   DOI: 10.19682/j.cnki.1005-8885.2020.0015
Abstract375)      PDF(pc) (4683KB)(416)       Save
While solving unimodal function problems, conventional meta-heuristic algorithms often suffer from low accuracy and slow convergence. Therefore, in this paper, a novel meta-heuristic optimization algorithm, named proton-electron swarm (PES), is proposed based on physical rules. This algorithm simulates the physical phenomena of like-charges repelling each other while opposite charges attracting in protons and electrons, and establishes a mathematical model to realize the optimization process. By balancing the global exploration and local exploitation ability, this algorithm achieves high accuracy and avoids falling into local optimum when solving target problem. In order to evaluate the effectiveness of this algorithm, 23 classical benchmark functions were selected for comparative experiments. Experimental results show that, compared with the contrast algorithms, the proposed algorithm cannot only obtain higher accuracy and convergence speed in solving unimodal function problems, but also maintain strong optimization ability in solving multimodal function problems.
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Research on cross-chain and interoperability for blockchain system

李鸣 邱鸿霖 徐泉清 宋文鹏 Liu Baixiang
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 1-17.   DOI: 10.19682/j.cnki.1005-8885.2021.0029
Abstract714)      PDF(pc) (3984KB)(325)       Save

At present, there is an urgent need for blockchain interoperability technology to realize interconnection between various blockchains, data communication and value transfer between blockchains, so as to break the ‘ value silo’ phenomenon of each blockchain. Firstly, it lists what people understand about the concept of interoperability. Secondly, it gives the key technical issues of cross-chain, including cross-chain mechanism, interoperability, eventual consistency, and universality. Then, the implementation of each cross-chain key technology is analyzed, including Hash-locking, two-way peg, notary schemes, relay chain scheme, cross-chain protocol, and global identity system. Immediately after that, five typical cross-chain systems are introduced and comparative analysis is made. In addition, two examples of cross-chain programmability and their analysis are given. Finally, the current state of cross-chain technology is summarized from two aspects: key technology implementation and cross-chain application enforcement. The cross-chain technology as a whole has formed a centralized fixed mechanism, as well as a trend of modular design, and some of the solutions to mature applications were established in the relevant standards organizations, and the cross-chain technology architecture tends to be unified, which is expected to accelerate the evolution of the open cross-chain network that supports the real needs of the interconnection of all chains.

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Trench gate GaN IGBT with controlled hole injection efficiency

The Journal of China Universities of Posts and Telecommunications    2024, 31 (2): 10-16.   DOI: 10.19682/j.cnki.1005-8885.2024.0012
Abstract63)      PDF(pc) (2095KB)(33)       Save

In this paper, a novel trench gate gallium nitride insulated gate bipolar transistor (GaN IGBT), in which the collector is divided into multiple regions to control the hole injection efficiency, is designed and theoretically studied. The incorporation of a P+/P- multi-region alternating structure in the collector region mitigates hole injection within the collector region. When the device is in forward conduction, the conductivity modulation effect results in a reduced storage of carriers in the drift region. As a result, the number of carriers requiring extraction during device turn-off is minimized, leading to faster turn-off speed. The results illustrate that the GaN IGBT with controlled hole injection efficiency (CEH GaN IGBT) exhibits markedly enhanced performance compared to conventional GaN IGBT, showing a remarkable 42.2% reduction in turn-off time and a notable 28.5% decrease in turn-off loss.

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Performance study of vertical MSM solar-blind photodetectors based on β-Ga 2O 3 thin film
The Journal of China Universities of Posts and Telecommunications    2024, 31 (2): 17-27.   DOI: 10.19682/j.cnki.1005-8885.2024.0006
Abstract72)      PDF(pc) (4363KB)(34)       Save

In this work, β-Ga2O3 thin films were grown on SiO2 substrate by atomic layer deposition (ALD) and annealed in N2 atmosphere to enhance the crystallization quality of the thin films, which were verified from X-rays diffraction (XRD). Based on the grown β-Ga2O3 thin films, vertical metal-semiconductor-metal (MSM) interdigital photodetectors (PDs) were fabricated and investigated. The PDs have an ultralow dark current of 1.92 pA, ultra-high photo-to-dark current ratio (PDCR) of 1.7×106, and ultra-high detectivity of 4.25×1014 Jones at a bias voltage of 10 V under 254 nm deep ultraviolet (DUV). Compared with the horizontal MSM PDs under the same process, the PDCR and detectivity of the fabricated vertical PDs are increased by 1 000 times and 100 times, respectively. In addition, the vertical PDs possess a high responsivity of 34.24 A/W and an external quantμm efficiency of 1.67×104%, and also exhibit robustness and repeatability, which indicate excellent performance. Then the effects of electrode size and external irradiation conditions on the performance of the vertical PDs continued to be investigated.

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SNR-adaptive deep joint source-channel coding scheme for imagesemantic transmission with convolutional block attention module
Yang Yujia, Liu Yiming, Zhang Wenjia, Zhang Zhi
The Journal of China Universities of Posts and Telecommunications    2024, 31 (1): 1-11.   DOI: 10.19682/j.cnki.1005-8885.2024.2001
Abstract496)      PDF(pc) (2443KB)(95)       Save
With the development of deep learning (DL), joint source-channel coding (JSCC) solutions for end-to-end transmission have gained a lot of attention. Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission, enhancing robustness in dynamic wireless environment. However, most of the existing adaptive JSCC schemes only consider different channel conditions, ignoring the different feature importance in the image processing and transmission. The uniform compression of different features in the image may result in the compromise of critical image details, particularly in low signal-to-noise ratio (SNR) scenarios. To address the above issues, in this paper, a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module (CBAM) is proposed, in which matrix operations are applied to features in spatial and channel dimensions respectively. The proposedsolution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result. Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR (PSNR) and structural similarity (SSIM), particularly in low SNR scenarios or when dealing with complex image content.
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Image label transfer: Short video labelling by using frame auto-encoder
Chao-Hui LV
The Journal of China Universities of Posts and Telecommunications    2020, 27 (1): 92-99.   DOI: 10.19682/j.cnki.1005-8885.2020.0002
Abstract455)      PDF(pc) (2804KB)(285)       Save
The number of short videos on the Internet is huge, but most of them are unlabeled. In this paper, a rough labelling method of short video based on the neural network of image classification is proposed. Convolutional auto-encoder is applied to train and learn unlabeled video frames, in order to obtain the feature in certain level of the network. Using these features, we extract key-frames of the video by our method of feature clustering. We put these key-frames which represent the video content into the image classification network, so that we can get the labels for every video clip. We also compare the different architectures of convolutional auto-encoder, while optimizing and selecting the better performance architecture through our experiment result. In addition, the video frame feature from the convolutional auto-encoder is compared with those features from other extraction methods. On the whole, this paper propose a method of image labels transferring for the realization of short video rough labelling, which can be applied to the video classes with few labeled samples.
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QoE-based video segments caching strategy in urban public  transportation system
Wang Hang, Li Xi, Ji Hong, Zhang Heli
The Journal of China Universities of Posts and Telecommunications    2021, 28 (4): 29-38.   DOI: 10.19682/j.cnki.1005-8885.2021.2003
Abstract464)      PDF(pc) (1902KB)(174)       Save
With the rapid development of vehicle-based applications, entertainment videos have gained popularity for  passengers on public vehicles. Therefore, how to provide high quality video service for passengers in typical public  transportation scenarios is an essential problem. This paper proposes a quality of experience (QoE)-based video  segments caching (QoE-VSC) strategy to guarantee the smooth watching experience of passengers. Consequently,  this paper considers a jointly caching scenario where the bus provides the beginning segments of a video, and the  road side unit (RSU) offers the remaining for passengers. To evaluate the effectiveness, QoE hit ratio is defined to  represent the probability that the bus and RSUs jointly provide passengers with desirable video segments  successfully. Furthermore, since passenger volume change will lead to different video preferences, a deep  reinforcement learning (DRL) network is trained to generate the segment replacing policy on the video segments  cached by the bus server. And the training target of DRL is to maximize the QoE hit ratio, thus enabling more  passengers to get the required video. The simulation results prove that the proposed method has a better  performance than baseline methods in terms of QoE hit ratio and cache costs.
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Semantic segmentation of track image based on deep neural network
Wang Zhaoying, Zhou Junhua, Liao Zhonghua, Zhai Xiang, Zhang Lianping
The Journal of China Universities of Posts and Telecommunications    2020, 27 (5): 23-33.   DOI: 10.19682/j.cnki.1005-8885.2020.0023
Abstract464)      PDF(pc) (1624KB)(127)       Save
In this paper, deep learning technology was utilited to solve the railway track recognition in intrusion detection  problem. The railway track recognition can be viewed as semantic segmentation task which extends image  processing to pixel level prediction. An encoder-decoder architecture DeepLabv3 + model was applied in this work  due to its good performance in semantic segmentation task. Since images of the railway track collected from the  video surveillance of the train cab were used as experiment dataset in this work, the following improvements were  made to the model. The first aspect deals with over-fitting problem due to the limited amount of training data. Data  augmentation and transfer learning are applied consequently to rich the diversity of data and enhance model  robustness during the training process. Besides, different gradient descent methods are compared to obtain the  optimal optimizer for training model parameters. The third problem relates to data sample imbalance, cross entropy  (CE) loss is replaced by focal loss (FL) to address the issue of serious imbalance between positive and negative  sample. Effectiveness of the improved DeepLabv3 + model with above solutions is demonstrated by experiment  results with different system parameters.
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Polarization-based optimal detection scheme for digital self-interference cancellation in full-duplex system
The Journal of China Universities of Posts and Telecommunications    2020, 27 (3): 73-82.   DOI: 10.19682/j.cnki.1005-8885.2020.0018
Abstract415)      PDF(pc) (1433KB)(358)       Save
In order to detect and cancel the self-interference (SI) signal from desired binary phase-shift keying (BPSK) signal, the polarization-based optimal detection (POD) scheme for cancellation of digital SI in a full-duplex (FD) system is proposed. The POD scheme exploits the polarization domain to isolate the desired signal from the SI signal and then cancel the SI to obtain the interference-free desired signal at the receiver. In FD communication, after antenna and analog cancellation, the receiver still contains residual SI due to non-linearities of hardware imperfections. In POD scheme, a likelihood ratio expression is obtained, which isolates and detects SI bits from the desired bits. After isolation of these signal points, the POD scheme cancels the residual SI. As compared to the conventional schemes, the proposed POD scheme gives significantly low bit error rate (BER), a clear constellation diagram to obtain the boundary between desired and SI signal points, and increases the receiver's SI cancellation performance in low signal to interference ratio (SIR) environment.
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Supervised learning of enhancing convolutional Hash for image retrieval
Zhai Qi, Jiang Mingyan
The Journal of China Universities of Posts and Telecommunications    2019, 26 (4): 51-61.   DOI: DOI: 10.19682/j.cnki.1005-8885.2019.1017
Abstract206)      PDF(pc) (6709KB)(142)       Save
Deep convolutional neural network (CNN) makes great breakthroughs in computer vision. Recently, many works have demonstrated that the performance of the CNN depends on the stacked convolutional layers. It is obvious that the features of the fully connected layers lose the topological structures of images, and the convolutional layer features contain a large amount of redundant information that interferes with the performance of model. Thus, we propose an effective supervised deep Hashing method, enhancing convolutional deep Hashing (ECDH), which learns the binary codes from the strengthened convolutional layer. Specifically, an enhanced convolutional Hash layer is constructed between the top convolutional layer and the output layer, enhancing the local features of the convolutional layer outputs while learning the binary codes by optimizing an objective function. The proposed method works well for existing deep learning models such as Alex neural network (AlexNet), visual geometry group neural network (VGGNet), residual neural network (ResNet), and is easier to be trained. Compared with state-of-the-art methods, extensive experiments show that the proposed method achieves better retrieval performance.
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Design of high frequency broadband low insertion loss SAW filter at 3.5 GHz

The Journal of China Universities of Posts and Telecommunications    2024, 31 (2): 55-61.   DOI: 10.19682/j.cnki.1005-8885.2024.0004
Abstract46)      PDF(pc) (2226KB)(22)       Save
With the wide application of the fifth-generation mobile communication system (5G) technology, wireless communication equipment tends to develop in miniaturization, high frequency , and low loss. In this paper, a surface acoustic wave (SAW) filter with a center frequency of 3.5 GHz was designed. Firstly, the acoustic waveguide structure of the longitudinal leaky SAW (LLSAW) excitation is determined, and the two-dimensional (2D) theoretical model of the device is established by COMSOL Multiphysics. Secondly, the influence of electrode parameters on the performance of the device is studied, and the electrode parameters are optimized on this basis. By setting the device structure parameters reasonably, the spurious in the passband can be effectively suppressed. Finally, the center frequency of the mirror T-structure LLSAW filter is 3.536 GHz, the insertion loss is -1.414 dB, the bandwidth of -3 dB is 276 MHz, and the out-of-band rejection is greater than -30 dB.
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ESO-KELM-based minor sensor fault identification
Zhao Kai, Song Jia, Wang Xinlong
The Journal of China Universities of Posts and Telecommunications    2021, 28 (4): 53-63.   DOI: 10.19682/j.cnki.1005-8885.2021.2005
Abstract299)      PDF(pc) (5082KB)(185)       Save
Aiming at the sensor faults of near-space hypersonic vehicles (NSHV), a fault identification method based on the  extended state observer and kernel extreme learning machine (ESO-KELM) is proposed in this paper. The method  is generated by a combination of the model-based method and the data-driven method. As the source of the fault  diagnosis, the residual signals represent the difference between the ESO output and the result measured by the  sensor in particular. The energy of the residual signals is distributed in both low frequency bands and high  frequency bands. However, the energy of the sensor concentrates on the low-frequency bands. Combined with more  different features detected by KELM, the proposed method devotes to improving the accuracy. Meanwhile, it is  competent to calculate the magnitude of minor faults based on time-frequency analysis. Finally, the simulation is  performed on the longitudinal channel of the Winged-Cone model published by the national aeronautics and space  administration (NASA). Results show the validity and the accuracy in calculating the magnitude of the minor  faults.
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Exo-LSTM: traffic flow prediction based on multifractal wavelet theory
杨帆, 姜梦雅,
The Journal of China Universities of Posts and Telecommunications    2021, 28 (5): 102-110.   DOI: 10.19682/j.cnki.1005-8885.2021.0027
Abstract330)      PDF(pc) (2021KB)(146)       Save

In order to predict traffic flow more accurately and improve network performance, based on the multifractal wavelet theory, a new traffic prediction model named exo-LSTM is proposed. Exo represents exogenous sequence used to provide a detailed sequence for the model, LSTM represents long short-term memory used to predict unstable traffic flow. Applying multifractal traffic flow to the exo-LSTM model and other existing models, the experiment result proves that exo-LSTM prediction model achieves better prediction accuracy.

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All-dielectric terahertz metasurface governed by bound states in the continuum with high-Q factor
The Journal of China Universities of Posts and Telecommunications    2024, 31 (2): 44-54.   DOI: 10.19682/j.cnki.1005-8885.2024.0003
Abstract65)      PDF(pc) (3460KB)(19)       Save
The method of terahertz (THz) resonance with a high-quality (high-Q) factor offers a vital physical mechanism for metasurface sensors and other high-Q factor applications. However, it is challenging to excite the resonance with a high-Q factor in metasurfaces with proper sensitivity as well as figure of merit (FOM) values. Here,  an all-dielectric metasurface composed of two asymmetrical rectangular blocks is suggested. Quartz and silicon are the materials applied for the substrate and cuboids respectively. The distinct resonance governed by bound states in the continuum (BIC) is excited by forming an asymmetric cluster by a novel hybrid method of cutting and moving the cuboids. The investigation focuses on analyzing the transmission spectra of the metasurface under different variations in structural parameters and the loss of silicon refractive index. When the proposed defective metasurface serves as a transmittance sensor, it shows a Q factor of 1.08×10 4 and achieves a FOM up to 4.8×10 6, which is obtained under the asymmetric parameter equalling 1 μm. Simultaneously, the proposed defective metasurface is sensitive to small changes in refractive index. When the thickness of the analyte is 180 μm, the sensitivity reaches a maximum value of 578 GHz / RIU. Hence, the proposed defective metasurface exhibits an extensive number of possible applications in the filters, biomedical diagnosis, security screening, and so on.
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Design of a Unified Rendering Shader for Mobile Device
The Journal of China Universities of Posts and Telecommunications    2019, 26 (3): 81-90.   DOI: 10.19682/j.cnki.1005-8885.2019.0024
Abstract451)      PDF(pc) (2422KB)(275)       Save
Real-time graphics processing is all along a crucial task of mobile device, and it is conventionally supported by programmable graphics processing unit (GPU). These GPUs are designed to flexibly support vertex and pixel processing with classic techniques such as on-chip cache and dynamic programmable pipelining. However, it is difficult for the vertex shader and pixel shader to achieve high utilization of hardware resources, even though there is a certain balance by reasonable processor quantity ratio. In this paper, a unified render shader with a very long instruction word (VLIW) processor was designed. The viewport transformation algorithm and the mipmap mapping algorithm are respectively mapped on the shader, with the purpose of providing an energy-efficient and flexible hardware platform for graphics processing in mobile device. The implemented operating frequency is up to 134 MHz on Xilinx XC7Z045-2-FFG900 field programmable gate array (FPGA), and unified architecture shader has a performance of 134 Mpixels/s in pixel fill rate, 546Mtexels/s in Texel Fill rate.
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Adaptive access points deployment for Indoor bluetooth positioning accuracy enhancement
Tian Zengshan, Ren Haoliang, Zhou Mu
The Journal of China Universities of Posts and Telecommunications    2019, 26 (5): 82-93.   DOI: 10.19682/j.cnki.1005-8885.2019.0023
Abstract301)      PDF(pc) (3686KB)(145)       Save
The indoor positioning system based on fingerprint receives more and more attention due to its high positioning accuracy and time efficiency. In the existing positioning approaches, much consideration is given to the positioning accuracy improvement by using the angle of signal, but the optimization of access points (APs) deployment is ignored. In this circumstance, an adaptive APs deployment approach is proposed. First of all, the criterion of reference points (RPs) effective coverage is proposed, and the number of deployed APs in target environment is obtained by using the region partition algorithm and full coverage algorithm. Secondly, the wireless signal propagation model is established for target environment, and meanwhile based on the initial APs deployment, the simulation fingerprint database is constructed for the sake of establishing the discrimination function with respect to fingerprint database. Thirdly, the greedy algorithm is applied to optimize APs deployment. Finally, the extensive experiments show that the proposed approach is capable of achieving adaptive APs deployment as well as improving positioning accuracy.
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12-bit 2.6 GS/ s RF DAC based on return-to-zero technology
Li Xiaopeng, Wang Zhigong, Zhang Yi, Zhang Youtao, Zhang Mi
The Journal of China Universities of Posts and Telecommunications    2019, 26 (4): 36-42.   DOI: DOI: 10.19682/j.cnki.1005-8885.2019.1015
Abstract270)      PDF(pc) (2813KB)(194)       Save
A 12-bit 2.6 GS/ s radio frequency digital to analog converter (RF DAC) based on 1 um GaAs heterojunction
bipolar transistor (HBT) process is presented. The DAC integrates a 4:1 multiplexer to reduce the data rate of
input ports, which greatly facilitates the application. DAC core adopts 4 +8 segmented current steering structure. R-2R ladder network is used for 8 least significant bit (LSB) to realize binary current weighting and thermometer
coding is used for 4 most significant bit (MSB). Return-to-zero (RZ) technology is used to expand the effective
bandwidth of DAC output to the third Nyquist band. The proposed DAC has a better output power flatness and
spurious-free dynamic range (SFDR). Compared to traditional DAC, measured results demonstrate that the output
power of this RZ DAC is increased by 33 dB and the SFDR is enhanced by 27 dB near the second Nyquist band.
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