Huawei

About: Huawei is a company organization based out in Shenzhen, China. It is known for research contribution in the topics: Terminal (electronics) & Signal. The organization has 41417 authors who have published 44698 publications receiving 343496 citations. The organization is also known as: Huawei Technologies & Huawei Technologies Co., Ltd..

Gabor Convolutional Networks

Abstract: Steerable properties dominate the design of traditional filters, e.g., Gabor filters, and endow features the capability of dealing with spatial transformations. However, such excellent properties have not been well explored in the popular deep convolutional neural networks (DCNNs). In this paper, we propose a new deep model, termed Gabor Convolutional Networks (GCNs or Gabor CNNs), which incorporates Gabor filters into DCNNs to enhance the resistance of deep learned features to the orientation and scale changes. By only manipulating the basic element of DCNNs based on Gabor filters, i.e., the convolution operator, GCNs can be easily implemented and are compatible with any popular deep learning architecture. Experimental results demonstrate the super capability of our algorithm in recognizing objects, where the scale and rotation changes occur frequently. The proposed GCNs have much fewer learnable network parameters, and thus is easier to train with an endtoend pipeline. The source code will be here 1.

Cyclic Prefixed OQAM-OFDM and its Application to Single-Carrier FDMA

Abstract: Single-carrier frequency division multiple access (SC-FDMA) has appeared to be a promising technique for high data rate uplink communications. Aimed at SC-FDMA applications, a cyclic prefixed version of the offset quadrature amplitude modulation based OFDM (OQAM-OFDM) is first proposed in this paper. We show that cyclic prefixed OQAM-OFDM (CP-OQAM-OFDM) can be realized within the framework of the standard OFDM system, and perfect recovery condition in the ideal channel is derived. We then apply CP-OQAM-OFDM to SC-FDMA transmission in frequency selective fading channels. Signal model and joint widely linear minimum mean square error (WLMMSE) equalization using a prior information with low complexity are developed. Compared with the existing DFTS-OFDM based SC-FDMA, the proposed SC-FDMA can significantly reduce envelope fluctuation (EF) of the transmitted signal while maintaining the bandwidth efficiency. The inherent structure of CP-OQAM-OFDM enables low-complexity joint equalization in the frequency domain to combat both the multiple access interference and the intersymbol interference. The joint WLMMSE equalization using a prior information guarantees optimal MMSE performance and supports Turbo receiver for improved bit error rate (BER) perform BER) performance. Simulation results confirm the effectiveness of the proposed SC-FDMA in terms of EF (including peak-to-average power ratio, instantaneous-to-average power ratio and cubic metric) and BER performances.

LIVE: Lightweight Integrity Verification and Content Access Control for Named Data Networking

Abstract: Named data networking (NDN) is a new paradigm for the future Internet wherein interest and data packets carry content names rather than the current IP paradigm of source and destination addresses. Security is built into NDN by embedding a public key signature in each data packet to enable verification of authenticity and integrity of the content. However, existing heavyweight signature generation and verification algorithms prevent universal integrity verification among NDN nodes, which may result in content pollution and denial of service attacks. Furthermore, caching and location-independent content access disables the capability of a content provider to control content access, e.g., who can cache a content and which end user or device can access it. We propose a lightweight integrity verification (LIVE) architecture, an extension to the NDN protocol, to address these two issues seamlessly. LIVE enables universal content signature verification in NDN with lightweight signature generation and verification algorithms. Furthermore, it allows a content provider to control content access in NDN nodes by selectively distributing integrity verification tokens to authorized nodes. We evaluate the effectiveness of LIVE with open source CCNx project. Our paper shows that LIVE only incurs average 10% delay in accessing contents. Compared with traditional public key signature schemes, the verification delay is reduced by over 20 times in LIVE.

Industrial Edge Computing: Enabling Embedded Intelligence

Abstract: The term industrial edge computing is used to describe a distributed platform that integrates communication, computation, and storage resources for performing real-time applications that can be directly accessed from the cloud. A step toward the industrial Internet revolution, industrial edge computing is designed to facilitate agile connectivity, real-time control, and data optimization, while enabling intelligent applications, ensuring tight security, and protecting privacy. Industrial edge computing makes use of what is known as edge computing nodes (ECNs), which bridge the gap between the physical world and the digital world by acting as smart gateways for assets, services, and systems. The IEEE P2805 Standards are being developed for defining protocols for self-management, data acquisition, and machine learning through cloud-edge collaboration on ECNs.