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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第10期67卷 6507-6524页

作者： Weng, Jian-Jia Alajaji, Fady Linder, Tamas Natl Taiwan Ocean Univ Dept Elect Engn Keelung 202301 Taiwan Queens Univ Dept Math & Stat Kingston ON K7L 3N6 Canada

We propose an adaptive lossy joint source-channel coding (JSCC) scheme for sending correlated sources over two-terminal discrete-memoryless two-way channels (DM-TWCs). The main idea is to couple the independent operations of the terminals via an adaptive coding mechanism, which can mitigate cross-interference resulting from simultaneous channel transmissions and concurrently exploit the sources' correlation to reduce the end-to-end reconstruction distortions. Our adaptive JSCC scheme not only subsumes existing lossy coding methods for two-way simultaneous communication but also improves their performance. Furthermore, we derive outer bounds for our two-way lossy transmission problem and establish complete JSCC theorems in some special settings. In these special cases, a non-adaptive separate source-channel coding (SSCC) scheme achieves the optimal performance, thus simplifying the design of the source-channel communication system.

关键词： Channel coding Source coding Protocols Propagation losses adaptive coding Distortion Noise measurement Network information theory two-way channels lossy transmission joint source-channel coding correlated sources hybrid analog and digital coding superposition coding adaptive coding

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A 16-channel Real-time adaptive Neural Signal Compression Engine in 22nm FDSOI 21

A 16-channel Real-time Adaptive Neural Signal Compression En...

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21st IEEE Interregional NEWCAS Conference (NEWCAS)

作者： Guo, Liyuan Zeinolabedin, Seyed Mohammad Ali Schueffny, Franz Marcus Weisse, Annika Scholze, Stefan George, Richard Partzsch, Johannes Mayr, Christian Tech Univ Dresden Chair Highly Parallel VLSI Syst & Neuromicroelect Dresden Germany

ISBN: (纸本)9798350300246

The real-time multi-channel intracranial recording of neural signals is required in both neuroscientific research and clinical practice. Due to the limited power budget and the increasing number of recording channels, a compression engine is highly recommended. This paper proposes a 16-channel realtime adaptive compression engine (ACE) exploiting neural signal properties. It is able to switch between lossless and near-lossless compression modes. In near-lossless mode, it compresses the spike region lossless and discards the rest. The achieved space-saving ratio (SSR) is on average about 62.5% and 91% for lossless and near-lossless modes, respectively. It can save about 78.5% of the power consumption (near-lossless compression) compared to the transmission of raw neural signals. The 16-channel ACE is implemented in 22nm FDSOI technology and consumes 230.0 mu W dynamic- and 55.49 mu W leakage-power at 5 MHz.

关键词： Multi-channel neural signal compression compression algorithms adaptive coding digital signal processors low-power design

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ADAPTATION IN AUDITORY PROCESSING

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PHYSIOLOGICAL REVIEWS 2022年第2期103卷 1024-1058页

作者： Willmore, Ben D. B. King, Andrew J. Univ Oxford Dept Physiol Anat & Genet Oxford England

Adaptation is an essential feature of auditory neurons, which reduces their responses to unchanging and recur-ring sounds and allows their response properties to be matched to the constantly changing statistics of sounds that reach the ears. As a consequence, processing in the auditory system highlights novel or unpredictable sounds and produces an efficient representation of the vast range of sounds that animals can perceive by con-tinually adjusting the sensitivity and, to a lesser extent, the tuning properties of neurons to the most commonly encountered stimulus values. Together with attentional modulation, adaptation to sound statistics also helps to generate neural representations of sound that are tolerant to background noise and therefore plays a vital role in auditory scene analysis. In this review, we consider the diverse forms of adaptation that are found in the audi-tory system in terms of the processing levels at which they arise, the underlying neural mechanisms, and their impact on neural coding and perception. We also ask what the dynamics of adaptation, which can occur over multiple timescales, reveal about the statistical properties of the environment. Finally, we examine how adapta-tion to sound statistics is influenced by learning and experience and changes as a result of aging and hearing loss.

关键词： adaptation adaptive coding auditory cortex sound statistics

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Temporal Scalable coding For Dynamic Meshes

Temporal Scalable Coding For Dynamic Meshes

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IEEE International Conference on Image Processing

作者： Jianfeng Xu Haruhisa Kato Kei Kawamura Advanced Visual Communication Laboratory KDDI Research Inc 2-1-15 Ohara Fujimino-shi Saitama Japan

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

This paper presents the first implementation of temporal scalability in the ongoing standard for Video-based Dynamic Mesh coding (V-DMC), a crucial enhancement that enables bitstream adaptation to diverse network conditions and device capabilities. While displacement and texture, two of the V-DMC’s sub-bitstreams, already benefit from existing video codec temporal scalability, the non-video basemesh sub-bitstream lacks this feature. To address this gap, we propose an adaptive coding structure designed for the basemesh. Moreover, we propose a novel cost function to adaptively select the frame type between intra-frame and inter-frame in this coding structure. Our experimental results demonstrate significant improvements in coding efficiency compared to the original V-DMC, i.e., the total BD-rates of D1, D2, Luma, Cb, and Cr averaged across all eight test sequences are -15.1%, -15.0%, 0.3%,-9.9%, and -8.4 %, respectively.

关键词： Image coding Scalability Estimation Cost function Video codecs Standards adaptive coding

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Capacity of Remote Classification Over Wireless Channels

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第7期69卷 4489-4503页

作者： Lan, Qiao Du, Yuqing Popovski, Petar Huang, Kaibin Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Aalborg Univ Dept Elect Syst DK-9220 Aalborg Denmark

Remote classification involves offloading complex object-recognition tasks from mobile devices to servers at the network edge. It brings to the mobile device the capability of discerning hundreds of object classes by using the computational and storage capabilities of the infrastructure. Remote classification is challenged by the finite and variable data rate of the wireless channel, which affects the capability to transfer high-dimensional features and thus limits the classification resolution. We introduce a set of metrics under the name of classification capacity that are defined as the maximum number of classes that can be discerned over a given communication channel while meeting a target probability for classification error. We treat both the cases of a channel where the instantaneous rate is known and unknown. The objective is to choose a subset of classes from a class library that offers satisfactory performance over a given channel. We treat two different cases of subset selection. First, a device can select the subset by pruning the class library until arriving at a subset that meets the targeted error probability while maximizing the classification capacity. Adopting a subspace data model, we prove the equivalence of classification capacity maximization to the problem of packing on the Grass-mann manifold. The results show that the classification capacity grows exponentially with the instantaneous communication rate, and super-exponentially with the dimensions of each data cluster. This also holds for ergodic and outage capacities with fading if the instantaneous rate is replaced with an average rate and a fixed rate, respectively. In the second case, a device has a unique preference of class subset for every communication rate, which is modeled as an instance of uniformly sampling the library. Without class selection, the classification capacity and its ergodic and outage counterparts are proved to scale linearly with their corresponding communication ra

关键词： Edge computing adaptive coding fading channels

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Hybrid-ARQ Protocols Based on Tornado Codes for the Packet Erasure Channel

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IEEE TRANSACTIONS ON COMMUNICATIONS 2021年第11期69卷 7139-7153页

作者： Puducheri-Sundaravaradhan, Srinath Fuja, Thomas E. Univ Notre Dame Dept Elect Engn Notre Dame IN 46556 USA Broadcom Inc San Jose CA 95134 USA

Lossless data transfer over communication networks has traditionally been achieved by means of ARQ protocols. However, the last ten years have seen an increasing interest in using erasure-correcting codes as an alternative, with the goal of reducing latency, feedback overhead, etc. Since these two approaches possess advantages as well as drawbacks, several hybrid ARQ schemes have also been proposed as good compromise solutions, in order to attain the "best of both worlds". Extending this principle, this paper develops new classes of hybrid ARQ protocols for erasure channels that allow for flexible trade-offs between two important cost metrics, viz., the computational complexity of coding, and the amount of feedback needed. Our hybrid schemes make use of Tornado codes - a class of low-complexity capacity-achieving erasure codes - whose coding structure is well-suited for feedback-based communications. These schemes demonstrate significant cost reductions versus coding-only and feedback-only approaches over a wide region of interest. Moreover, these schemes are easily tuned to achieve different operating points on a trade-off curve. Finally, the proposed schemes showcase novel means of interweaving coding and feedback.

关键词： Encoding Tornadoes Complexity theory Protocols Decoding Parity check codes Receivers Feedback communication channel coding adaptive coding automatic repeat request computation time

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Fast Practical adaptive Encoding on Large Alphabets

Fast Practical Adaptive Encoding on Large Alphabets

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Data Compression Conference (DCC)

作者： Igor Zavadskyi Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (数字)9798331534714

ISBN: (纸本)9798331534721

We present two adaptive coding methods that perform especially well on large alphabets like those used in word-level text compression. The first is based on re-indexing a universal codeword set. The more evolved second method assumes that the underlying codeword set can be optimized and re-generated efficiently. Experiments show that this method, using the Binary Mixed-digit codes as an underlying solution, produces about 1% bigger compressed files than the classical Vitter's algorithm adapted to large alphabets, being more than an order of magnitude faster in encoding and decoding.

关键词： Computer languages Costs Codes Symbols Encoding Decoding adaptive coding

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Dual-Use Secure Key Distribution Protocol Based on FEC-Aided Unidirectional BER Estimation

Dual-Use Secure Key Distribution Protocol Based on FEC-Aided...

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OptoElectronics and Communications Conference, OECC

作者： Di Wu Lei Deng Qi Yang Zhijun Yan Xiaoxiao Dai Xiaojing Gao Mengfan Cheng National Engineering Research Center for Next Generation Internet Access System School of Optical and Electronic Information Huazhong University of Science and Technology (HUST) Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China The School of Computer Science China University of Geosciences Wuhan China

ISBN: (数字)9798350308396

ISBN: (纸本)9798350308402

We propose a unidirectional dual-use secure key distribution protocol based on the forward-error-correction-aided bit error rate estimation. Hybrid automatic repeat request and adaptive coding techniques are integrated to enhance the reliability of communication section. A simulation is conducted in a turbulent channel to verify the feasibility of the proposed protocol.

关键词： Protocols Bit error rate Estimation Parity check codes Reliability Automatic repeat request Optical devices adaptive coding

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$k^{\prime}$ -Lucas Sequence for Elliptic Curve Cryptography

$k^{\prime}$ -Lucas Sequence for Elliptic Curve Cryptography

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Advances in Computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), International Conference on

作者： Abhinav Surjeet Singh Chauhan Gonder Prachi Garg Sudhanshu Shekhar Dubey Department of Mathematics Chandigarh University Gharuan Punjab India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

The $\boldsymbol{k}^{\prime}$ -Lucas sequence is a significant generalization of the classical Lucas sequence, exhibiting various intriguing properties and applications across mathematics and cryptography. The study of $\boldsymbol{k}^{\prime}$ -Lucas-like sequences on elliptic curves has gained attention recently, which offer unique structural advantages for cryptographic systems. An extension of the $\boldsymbol{k}^{\prime}$ -Lucas sequence defined on elliptic curves (EC) is presented in this study, highlighting its recursive nature and algebraic characteristics. Additionally, we suggest an encryption scheme that makes use of this sequence, leveraging the complexities inherent in “Elliptic Curve Discrete Logarithm Problem (ECDLP)” [1]. Our findings indicate that this approach enhances security and opens new avenues for robust cryptographic protocols.

关键词： Computer science Electric potential Elliptic curves Elliptic curve cryptography Mathematics Communications technology Encryption Complexity theory Cryptographic protocols adaptive coding

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Xgboost Based Regression Forecast for ACM on Q/V-band Satellite Links

Xgboost Based Regression Forecast for ACM on Q/V-band Satell...

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European Conference on Antennas and Propagation, EuCAP

作者： Mirela Fetescu Johannes Ebert Karin Plimon Martin Winter Michael Schmidt Franz Teschl Antonio Martellucci Graz University of Technology Graz Austria JOANNEUM RESEARCH - DIGITAL Graz Austria ESA-ESTEC Noordwijk The Netherlands

ISBN: (数字)9788831299107

ISBN: (纸本)9798350366327

This paper presents a comparison between classical adaptive coding and modulation (ACM) with fixed modulation and coding (ModCod) margins and two machine learning (ML)-based approaches: univariate and multivariate forecasting models. Both ML approaches are based on variants of Extreme Gradient Boosting (XGBoost) to predict signal-tonoise ratio (SNR) time series, aiding ACM switching decisions. The evaluation of the ACM algorithms is conducted using two years of Q/V-band channel data recorded at the ground station in Graz, Austria, using the Alphasat TDP5 Aldo Paraboni Q/Vband payload. The results demonstrate that the multivariate forecasting model outperforms both the classical ACM algorithm and the univariate forecasting model in terms of spectral efficiency. Additionally, the multivariate model eliminates the need for direct SNR estimation by using easily measurable parameters from the modem.

关键词： Adaptation models Spectral efficiency Computational modeling Modulation Predictive models Modems Forecasting Signal to noise ratio Payloads adaptive coding

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