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..

Circulant Binary Convolutional Networks: Enhancing the Performance of 1-Bit DCNNs With Circulant Back Propagation

Abstract: The rapidly decreasing computation and memory cost has recently driven the success of many applications in the field of deep learning. Practical applications of deep learning in resource-limited hardware, such as embedded devices and smart phones, however, remain challenging. For binary convolutional networks, the reason lies in the degraded representation caused by binarizing full-precision filters. To address this problem, we propose new circulant filters (CiFs) and a circulant binary convolution (CBConv) to enhance the capacity of binarized convolutional features via our circulant back propagation (CBP). The CiFs can be easily incorporated into existing deep convolutional neural networks (DCNNs), which leads to new Circulant Binary Convolutional Networks (CBCNs). Extensive experiments confirm that the performance gap between the 1-bit and full-precision DCNNs is minimized by increasing the filter diversity, which further increases the representational ability in our networks. Our experiments on ImageNet show that CBCNs achieve 61.4% top-1 accuracy with ResNet18. Compared to the state-of-the-art such as XNOR, CBCNs can achieve up to 10% higher top-1 accuracy with more powerful representational ability.

Millimeter wave MIMO channel tracking systems

Abstract: We consider channel/subspace tracking systems for temporally correlated millimeter wave (e.g., E-band) multiple-input multiple-output (MIMO) channels. Our focus is given to the tracking algorithm in the non-line-of-sight (NLoS) environment, where the transmitter and the receiver are equipped with hybrid analog/digital precoder and combiner, respectively. In the absence of straightforward time-correlated channel model in the millimeter wave MIMO literature, we present a temporal MIMO channel evolution model for NLoS millimeter wave scenarios. Considering that conventional MIMO channel tracking algorithms in microwave bands are not directly applicable, we propose a new channel tracking technique based on sequentially updating the precoder and combiner. Numerical results demonstrate the superior channel tracking ability of the proposed technique over independent sounding approach in the presented channel model and the spatial channel model (SCM) adopted in 3GPP specification.

Method for a root path calculation in a shortest path bridge

Abstract: A method for root path calculation in a shortest path bridge, including: in the case that there are a plurality of equivalent paths whose total path cost to a root bridge is equal, determining a root path corresponding to the root bridge based on the minimum/maximum value of bridge ID in the plurality of equivalent paths. The method can generate symmetric paths for different root bridges under a multiple spanning tree circumstance of shortest path bridge.

Robust and Accurate Smartphone-Based Step Counting for Indoor Localization

Abstract: Robust and accurate step counting is important for indoor localization algorithms that rely on smartphone inertial sensors. Existing solutions for step counting do not consider users’ false walking state (e.g., when a user in still state uses her phone for texting, playing games, and watching movies), which results in the over-counting problem. In this paper, we propose a robust and accurate step counting algorithm to solve the overcounting problem caused by false walking. Experimental results show that the proposed algorithm outperforms the commonly-used peak detection-based method and can improve the step counting accuracy by 6.56% for normal walking case, 9.54% for free walking case, and by 58.92% for false walking case, which is a significant improvement in the accuracy and robustness. We also compare the proposed method with popular commercial step counting applications including S Health, i-Health, and Pedometer++, which shows that our method can achieve better accuracy.

Optimization Framework and Graph-Based Approach for Relay-Assisted Bidirectional OFDMA Cellular Networks

Abstract: This paper considers a relay-assisted bidirectional cellular network where the base station (BS) communicates with each mobile station (MS) using OFDMA for both uplink and downlink. The goal is to improve the overall system performance by exploring the full potential of the network in various dimensions including user, subcarrier, relay, and bidirectional traffic. In this work, we first introduce a novel three-time-slot time-division duplexing (TDD) transmission protocol. This protocol unifies direct transmission, one-way relaying and network-coded two-way relaying between the BS and each MS. Using the proposed three-time-slot TDD protocol, we then propose an optimization framework for resource allocation to achieve the following gains: cooperative diversity (via relay selection), network coding gain (via bidirectional transmission mode selection), and multiuser diversity (via subcarrier assignment). We formulate the problem as a combinatorial optimization problem, which is NP-complete. To make it more tractable, we adopt a graph-based approach. We first establish the equivalence between the original problem and a maximum weighted clique problem in graph theory. A metaheuristic algorithm based on any colony optimization (ACO) is then employed to find the solution in polynomial time. Simulation results demonstrate that the proposed protocol together with the ACO algorithm significantly enhances the system total throughput.