arXiv subjects

Chuan Zhang

Publications and source records attributed to Chuan Zhang.

At least 55 records · Page 3Linked to original sources

arXiv2021

Design Guideline for Minimizing Space-Charge-Induced Emittance Growth

Space-charge-induced emittance growth is a big con-cern for designing low energy and high intensity linacs. The Equipartitioning Principle was introduced to mini-mize space-charge-induced emittance growth by remov-ing free energy between the transverse and longitudinal degrees of freedom. In this study, a different design guide-line is being proposed. It suggests to hold the ratio of longitudinal emittance to transverse emittance around one and take advantage of low emittance transfer for minimizing emittance growth. Using a high intensity RFQ accelerator as an example, a comparison between the two design methods has been made.

physics.acc-ph↗

arXiv2020

Realizing long radio-frequency quadrupole accelerators with multiple shorter and independent cavities

It is well known that the tuning of a long radio-frequency quadrupole accelerator is demanding. This study investigated how to realize efficient long RFQ accelerators with multiple shorter and independent cavities. From the RF point of view, the use of shorter cavities has many advantages e.g. enlarged mode separation and simplified RF tuning, but the beam matching between cavities will become an issue, especially at high current and low energy. Taking a more than 9 m long, high current machine as an example, this paper presents the design concepts and methods leading to good beam quality and high beam transmission throughout a multi-stage RFQ accelerator.

physics.acc-ph↗

arXiv2020

Hybrid Beamforming/Combining for Millimeter Wave MIMO: A Machine Learning Approach

Hybrid beamforming (HB) has emerged as a promising technology to support ultra high transmission capacity and with low complexity for Millimeter Wave (mmWave) multiple-input and multiple-output (MIMO) system. However, the design of digital and analog beamformer is a challenge task with non-convex optimization, especially for the multi-user scenario. Recently, the blooming of deep learning research provides a new vision for the signal processing of communication system. In this work, we propose a deep neural network based HB for the multi-User mmWave massive MIMO system, referred as DNHB. The HB system is formulated as an autoencoder neural network, which is trained in a style of end-to-end self-supervised learning. With the strong representation capability of deep neural network, the proposed DNHB exhibits superior performance than the traditional linear processing methods. According to the simulation results, DNHB outperforms about 2 dB in terms of bit error rate (BER) performance compared with existing methods.

eess.SP↗

arXiv2019

A General Construction and Encoder Implementation of Polar Codes

Similar to existing codes, puncturing and shortening are two general ways to obtain an arbitrary code length and code rate for polar codes. When some of the coded bits are punctured or shortened, it is equivalent to a situation in which the underlying channels of the polar codes are different. Therefore, the quality of bit channels with puncturing or shortening differ from the original qualities, which can greatly affect the construction of polar codes. In this paper, a general construction of polar codes is studied in two aspects: 1) the theoretical foundation of the construction; and 2) the hardware implementation of polar codes encoders. In contrast to the original identical and independent binary-input, memoryless, symmetric (BMS) channels, these underlying BMS channels can be different. For binary erasure channel (BEC) channels, recursive equations can be employed assuming independent BMS channels. For all other channel types, the proposed general construction of polar codes is based on the existing Tal-Vardy's procedure. The symmetric property and the degradation relationship are shown to be preserved under the general setting, rendering the possibility of a modification of Tal-Vardy's procedure. Simulation results clearly show improved error performance with re-ordering using the proposed new procedures. In terms of hardware, a novel pruned folded encoder architecture is proposed which saves the computation for the beginning frozen bits. Implementation results show the pruned encoder achieve 28% throughput improvement.

cs.IT↗

arXiv2019

Polar Codes with Memory

Polar codes with memory (PCM) are proposed in this paper: a pair of consecutive code blocks containing a controlled number of mutual information bits. The shared mutual information bits of the succeeded block can help the failed block to recover. The underlying polar codes can employ any decoding scheme such as the successive cancellation (SC) decoding (PCM-SC), the belief propagation (BP) decoding (PCM-BP), and the successive cancellation list (SCL) decoding (PCM-SCL). The analysis shows that the packet error rate (PER) of PCM decreases to the order of PER squared while maintaining the same complexity as the underlying polar codes. Simulation results indicate that for PCM-SC, the PER is comparable to (less than 0.3 dB) the stand-alone SCL decoding with two lists for the block length $N=256$. The PER of PCM-SCL with $L$ lists can match that of the stand-alone SCL decoding with $2L$ lists. Two hardware decoders for PCM are also implemented: the in-serial (IS) decoder and the low-latency interleaved (LLI) decoder. For $N=256$, synthesis results show that in the worst case, the latency of the PCM LLI decoder is only $16.1\%$ of the adaptive SCL decoder with $L=2$, while the throughput is improved by 13 times compared to it.

cs.IT↗

arXiv2019

An Atom-Probe Tomographic Study of the Compositional Trajectories During gamma(f.c.c.)/gamma-prime(L12) Phase-Separation in a Ni-Al-Cr-Re Superalloy

The compositional diffusional-trajectories for a phase separation of gamma(f.c.c.)/gamma-prime(L12) phases are studied in a quaternary Ni-10Al-8.5Cr-2Re alloy, aged at 700 deg.C for 0 to 1024 h, utilizing atom-probe tomography (APT). As the gamma-prime(L12)-precipitates grow, the enrichments of Ni, Cr, and Re and depletion of Al on the gamma(f.c.c.) matrix-side develop as a result of diffusional fluxes crossing the gamma(f.c.c.)/gamma-prime(L12) interface.The experimental (APT) compositional trajectories of the two-phases, gamma(f.c.c.)/gamma-prime(L12), are displayed in a quaternary phase-diagram, employing a tetrahedron, and compared with the Philippe-Voorhees (P-V) coarsening model which includes the off-diagonal terms in the diffusion tensor for the multi-component system.

cond-mat.mtrl-sci↗

arXiv2019

Design approach for modern high-current, radio-frequency quadrupole accelerators with low emittance transfer

Radio Frequency Quadrupole (RFQ) accelerators often need to face the challenges of space charge effects from high beam currents. This study investigated how to reach RFQ beam dynamics designs with not only high beam transmission and short structure length but also high beam quality simultaneously. To avoid beam instabilities induced by emittance transfer, a so-called el/et (ratio of the longitudinal and transverse emittances) = 1.0 design guideline is being proposed. The application of this design guideline integrated with the BABBLE/NFSP design method for a high current, high frequency, high injection energy RFQ accelerator is described.

physics.acc-ph↗

arXiv2019

An efficient solution for accelerating very high intensity beams in the low and medium energy regime

Taking advantage of the 0° synchronous phase, the KONUS ("Combined 0° Structure" translated from German "Kombinierte Null Grad Struktur") beam dynamics strategy enables long accelerating sections with lens-free slim drift tubes in the low and medium energy regime. It has successfully realized worldwide many room temperature H-type linacs with compact layouts and good beam performance. In this paper, a further development of this solution i.e. to combine the KONUS dynamics with the young superconducting CH (Crossbar H-Type) structure for accelerating very high intensity beams is being presented. The efficiency of the new solution has been shown by the systematic design studies performed for a 150mA, 6MW deuteron linac.

physics.acc-ph↗

arXiv2019

Molecular Polar Belief Propagation Decoder and Successive Cancellation Decoder

By constructing chemical reaction networks (CRNs), this paper proposes a method of synthesizing polar decoder using belief propagation (BP) algorithm and successive cancellation (SC) algorithm, respectively. Theoretical analysis and simulation results have validated the feasibility of the method. Reactions in the proposed design could be experimentally implemented with DNA strand displacement reactions, making the proposed polar decoders promising for wide application in nanoscale devices.

eess.SP↗

arXiv2019

Achieving Trust-Based and Privacy-Preserving Customer Selection in Ubiquitous Computing

The recent proliferation of smart devices has given rise to ubiquitous computing, an emerging computing paradigm which allows anytime & anywhere computing possible. In such a ubiquitous computing environment, customers release different computing or sensing tasks, and people, also known as data processors, participate in these tasks and get paid for providing their idle computing and communication resources. Thus, how to select an appropriate and reliable customer while not disclosing processors' privacy has become an interesting problem. In this article, we present a trust-based and privacy-preserving customer selection scheme in ubiquitous computing, called TPCS, to enable potential processors select the customers with good reputation. The basic concept of TPCS is that each data processor holds a trust value, and the reputation score of the customer is calculated based on processors' trust values and feedbacks via a truth discovery process. To preserve processors' privacy, pseudonyms and Paillier cryptosystem are applied to conceal each processor's real identity. In addition, three authentication protocols are designed to ensure that only the valid data processors (i.e., the processors registering in the system, holding the truthful trust values, and joining the computing tasks) can pass the authentication. A comprehensive security analysis is conducted to prove that our proposed TPCS scheme is secure and can defend against several sophisticated attacks. Moreover, extensive simulations are conducted to demonstrate the correctness and effectiveness of the proposed scheme.

cs.CR↗

arXiv2019

A Privacy-Preserving Traffic Monitoring Scheme via Vehicular Crowdsourcing

The explosive growth of vehicle amount has given rise to a series of traffic problems, such as traffic congestion, road safety, and fuel waste. Collecting vehicles' speed information is an effective way to monitor the traffic condition and avoid vehicles being congested, which however may bring threats to vehicles' location and trajectory privacy. Motivated by the fact that traffic monitoring does not need to know each individual vehicle's speed and the average speed would be sufficient, we propose a privacy-preserving traffic monitoring (PPTM) scheme to aggregate vehicles' speeds at different locations. In PPTM, the roadside unit (RSU) collects vehicles' speed information at multiple road segments, and further cooperates with a service provider to calculate the average speed information for every road segment. To preserve vehicles' privacy, both homomorphic Paillier cryptosystem and super-increasing sequence are adopted. A comprehensive security analysis indicates that the proposed PPTM can preserve vehicles' identities, speeds, locations, and trajectories privacy from being disclosed. In addition, extensive simulations are conducted to validate the effectiveness and efficiency of the proposed PPTM scheme.

cs.CR↗

arXiv2018

A Correlation-Breaking Interleaving of Polar Codes in Concatenated Systems

It is known that the bit errors of polar codes with successive cancellation (SC) decoding are coupled. However, existing concatenation schemes of polar codes with other error correction codes rarely take this coupling effect into consideration. To achieve a better error performance of concatenated systems with polar codes as inner codes, one can divide all bits in an outer block into different polar blocks to completely de-correlate the possible coupled errors in the transmitter side. We call this interleaving a blind interleaving (BI) which serves as a benchmark. Two BI schemes, termed BI-DP and BI-CDP, are proposed in the paper. To better balance performance, memory size, and the decoding delay from the de-interleaving, a novel interleaving scheme, named the correlation-breaking interleaving (CBI), is proposed. The CBI breaks the correlated information bits based on the error correlation pattern proposed and proven in this paper. The proposed CBI scheme is general in the sense that any error correction code can serve as the outer code. In this paper, Low-Density Parity-Check (LDPC) codes and BCH codes are used as two examples of the outer codes of the interleaving scheme. The CBI scheme 1) can keep the simple SC polar decoding while achieving a better error performance than the state-of-the-art (SOA) direct concatenation of polar codes with LDPC codes and BCH codes; 2) achieves a comparable error performance as the BI-DP scheme with a smaller memory size and a shorter decoding delay. Numerical results are provided to verify the performance of the BI schemes and the CBI scheme.

cs.IT↗

arXiv2018

Polar Decoding on Sparse Graphs with Deep Learning

In this paper, we present a sparse neural network decoder (SNND) of polar codes based on belief propagation (BP) and deep learning. At first, the conventional factor graph of polar BP decoding is converted to the bipartite Tanner graph similar to low-density parity-check (LDPC) codes. Then the Tanner graph is unfolded and translated into the graphical representation of deep neural network (DNN). The complex sum-product algorithm (SPA) is modified to min-sum (MS) approximation with low complexity. We dramatically reduce the number of weight by using single weight to parameterize the networks. Optimized by the training techniques of deep learning, proposed SNND achieves comparative decoding performance of SPA and obtains about $0.5$ dB gain over MS decoding on ($128,64$) and ($256,128$) codes. Moreover, $60 \%$ complexity reduction is achieved and the decoding latency is significantly lower than the conventional polar BP.

eess.SP↗

arXiv2018

AI for 5G: Research Directions and Paradigms

The 5th wireless communication (5G) techniques not only fulfil the requirement of $1,000$ times increase of internet traffic in the next decade, but also offer the underlying technologies to the entire industry and ecology for internet of everything. Compared to the existing mobile communication techniques, 5G techniques are more-widely applicable and the corresponding system design is more complicated. The resurgence of artificial intelligence (AI) techniques offers as an alternative option, which is possibly superior over traditional ideas and performance. Typical and potential research directions to which AI can make promising contributions need to be identified, evaluated, and investigated. To this end, this overview paper first combs through several promising research directions of AI for 5G, based on the understanding of the 5G key techniques. Also, the paper devotes itself in providing design paradigms including 5G network optimization, optimal resource allocation, 5G physical layer unified acceleration, end-to-end physical layer joint optimization, and so on.

eess.SP↗

arXiv2018

DNA Computing for Combinational Logic

With the progressive scale-down of semiconductor's feature size, people are looking forward to More Moore and More than Moore. In order to offer a possible alternative implementation process, people are trying to figure out a feasible transfer from silicon to molecular computing. Such transfer lies on bio-based modules programming with computer-like logic, aiming at realizing the Turing machine. To accomplish this, the DNA-based combinational logic is inevitably the first step we have taken care of. This timely overview paper introduces combinational logic synthesized in DNA computing from both analog and digital perspectives separately. State-of-the-art research progress is summarized for interested readers to quick understand DNA computing, initiate discussion on existing techniques and inspire innovation solutions. We hope this paper can pave the way for the future DNA computing synthesis.

cs.ET↗

arXiv2018

Joint Neural Network Equalizer and Decoder

Recently, deep learning methods have shown significant improvements in communication systems. In this paper, we study the equalization problem over the nonlinear channel using neural networks. The joint equalizer and decoder based on neural networks are proposed to realize blind equalization and decoding process without the knowledge of channel state information (CSI). Different from previous methods, we use two neural networks instead of one. First, convolutional neural network (CNN) is used to adaptively recover the transmitted signal from channel impairment and nonlinear distortions. Then the deep neural network decoder (NND) decodes the detected signal from CNN equalizer. Under various channel conditions, the experiment results demonstrate that the proposed CNN equalizer achieves better performance than other solutions based on machine learning methods. The proposed model reduces about $2/3$ of the parameters compared to state-of-the-art counterparts. Besides, our model can be easily applied to long sequence with $\mathcal{O}(n)$ complexity.

eess.SP↗

arXiv2018

Frequency Jump at Low Energies

One or more radio-frequency jumps are usually necessary for realizing a >= 100 AMeV/u proton or ion driver linac. Typically, such jumps happen in the range of \b{eta} = 0.2-0.6 between the resonator structures fitting to this \b{eta}-range, e.g. DTL, HWR, CCL or elliptical cavities. We propose to perform the first frequency jump already at low energies (\b{eta} <= 0.1) between two RFQ accelerators, which can bring some unique advantages. First studies have been performed and the results proved that this idea is feasible and promising. Many efforts have been and are being made to address the most critical issue for the jumps i.e. the beam matching at the transition.

physics.acc-ph↗

arXiv2018

Efficient Soft-Output Gauss-Seidel Data Detector for Massive MIMO Systems

For massive multiple-input multiple-output (MIMO) systems, linear minimum mean-square error (MMSE) detection has been shown to achieve near-optimal performance but suffers from excessively high complexity due to the large-scale matrix inversion. Being matrix inversion free, detection algorithms based on the Gauss-Seidel (GS) method have been proved more efficient than conventional Neumann series expansion (NSE) based ones. In this paper, an efficient GS-based soft-output data detector for massive MIMO and a corresponding VLSI architecture are proposed. To accelerate the convergence of the GS method, a new initial solution is proposed. Several optimizations on the VLSI architecture level are proposed to further reduce the processing latency and area. Our reference implementation results on a Xilinx Virtex-7 XC7VX690T FPGA for a 128 base-station antenna and 8 user massive MIMO system show that our GS-based data detector achieves a throughput of 732 Mb/s with close-to-MMSE error-rate performance. Our implementation results demonstrate that the proposed solution has advantages over existing designs in terms of complexity and efficiency, especially under challenging propagation conditions.

eess.SP↗