物联网业务特征及业务模型研究

介绍了物联网多种应用方式,特别对车联网、智能家居等物联网应用的网络通信方式、资源消耗等通信特征及参数进行重点分析,得出普遍适用的物联网应用网络层通信模型分析方法。     

A tool for power and phase noise optimization in frequency synthesizers

In this paper, we present a CAD technique to design low-power and low phase noise integrated frequency synthesizers. This technique introduces a key parameter, Phase Noise per Unit Power, which correlates phase noise and power among all the sub-circuits in the frequency synthesizer. By correlating the performance of all the independent circuits together, sophisticated synthesizer design and optimization can be significantly simplified. We demonstrate a 1.8 GHz frequency synthesizer design in a 0.18 μm CMOS process achieving −132 dBc/Hz phase noise at 100 kHz offset with less than 4.3 mW power consumption.     

Using directionality in mobile routing

The increased usage of directional methods of communications has prompted research into leveraging directionality in every layer of the network stack. In this paper, we explore the use of directionality in layer 3 to facilitate routing in highly mobile environments. We introduce Mobile Orthogonal Rendezvous Routing Protocol (MORRP) for mobile ad-hoc networks (MANETs). MORRP is a lightweight, but scalable routing protocol utilizing directional communications (such as directional antennas or free-space-optical transceivers) to relax information requirements such as coordinate space embedding, node localization, and mobility. This relaxation is done by introducing a novel concept called the directional routing table (DRT) which maps a set-of-IDs to each interface direction to provide probabilistic routing information based on interface direction. We show that MORRP achieves connectivity with high probability even in highly mobile environments while maintaining only probabilistic information about destinations. Additionally, we compare MORRP with various proactive, reactive, and position-based routing protocols using single omni-directional interfaces and multiple directional interfaces and show that MORRP gains over 10–14 × additional goodput vs. traditional protocols and 15–20% additional goodput vs. traditional protocols using multiple interfaces. MORRP scales well without imposing DHT-like graph structures (eg: trees, rings, torus etc). We also show that high connectivity can be achieved without the need to frequently disseminate node position resulting increased scalability even in highly mobile environments.     

SNR wall and cooperative spectrum sensing in cognitive radio under noise uncertainty

Cooperative energy spectrum sensing has been proved effective to detect the spectrum holes in Cognitive Radio (CR). However, its performance may suffer from the noise uncertainty, which is portrayed by the SNR wall in some literatures. In this paper we analyze the spectrum sensing performance under noise uncertainty and find an alternative approach to obtain the SNR wall. Then the average SNR wall is proposed to illustrate the statistically average impact of noise uncertainty. In addition, the cooperative sensing performance under noise uncertainty with AND rule is discussed. Analyses and numerical results show that cooperative sensing can significantly improve the sensing performance under the condition of noise uncertainty.     

One-to-Many: Context-Oriented Code for Concurrent Error Detection

The paper deals with context-oriented codes for concurrent error detection. We consider a fault model for which, in the presence of a fault, the values on the circuit’s output are arbitrary. This model allows one to design an error detection code without analyzing sensitive parts or error cones in the synthesized circuit. Conventional coding schemes are based on a one-to-one mapping between an original output vector (information word) and a codeword. In this paper, we introduce a different approach, which we call one-to-many coding. In one-to-many code, each codeword comprises a predefined set of words. The functional unit is referred to as an encoder enabling each activation to map an information word to a different word. This flexible mapping system results in a lower implementation cost of the functional unit and its checker.     

Ambulatory Hip Angle Estimation using Gaussian Particle Filter

Hip angle is a major parameter in gait analysis while gait analysis plays an important role in healthcare, animation and other applications. Accurate estimation of hip angle using wearable inertial sensors in ambulatory environment remains a challenge because 1) the non-linear nature of thigh movement has not been well addressed, and 2) the variation of micro-inertial sensor measurement noise has not been studied yet. We propose to use Hybrid Dynamic Bayesian Network (HDBN) to model the non-linear hip angle dynamics and variation of measurement noise levels, and Gaussian Particle Filter (GPF) to estimate the hip angle during gait cycles from the measurements of the wearable accelerometers that are attached to the thighs. The experiments have been conducted and the results have shown that the proposed method can achieve significant accuracy improvement over the previous work on the ambulatory hip angle estimation.     

Ellipse-underlay protection algorithm to deal with regional demolishments in mesh optical networks

For the abundant bandwidth, a malfunction in optical networks causes a great deal of loss to traffic, and hence the survivability of optical networks must be considered. Two technologies, protection and restoration, are used in general, and the former is investigated in this paper. The existing protection strategies mainly cope with a single link failure or a double-link failure in an optical network and not consider what causes these failures. In this paper, we study the reasons which lead to the network malfunctions, and pose a new concept named regional demolishment. A protection algorithm named Ellipse-underlay algorithm is also proposed. We compare the performance of the Ellipse-underlay algorithm to the Node-disjoint algorithm. Simulation results show that the Ellipse-underlay algorithm is more effective to the survivability of traffic than the Node-disjoint algorithm.     

Finding Multiple Equivalence-Preserving Transformations in Combinational Circuits through Incremental-SAT

This paper introduces an approach to effectively exploit incremental SAT in order to search for multiple equivalence-preserving transformations of combinational circuits. Typical applications, such as redundancy removal with observability and external care conditions, adequate abstractions and other optimizations used in a state-of-the-art SAT-based model checker, can reap benefits from the proposed strategies. Our techniques exploit SAT incrementality, by iteratively refining the set of candidate transformations with a counter-example driven analysis, until an unsatisfiable point is reached. The key point of our technique is the ability to address satisfiable instances first, where SAT solvers are generally much faster than with unsatisfiable runs. We also discuss partitioning and problem reduction issues, that are fundamental in order to provide a scalable approach. Experimental results show the effectiveness of the proposed strategies.     

Power consumption of analog circuits: a tutorial

A systematic approach to the power consumption of analog circuits is presented. The power consumption is related to basic circuit requirements, as dynamic range, bandwidth, noise figure and sampling speed and is considering basic device and device scaling behavior. Several kinds of circuits are treated, as samplers, amplifiers, filters and oscillators. The objective is to derive lower bounds to power consumption in analog circuits, to be used as design targets when designing power-constrained analog systems.     

Perfect histogram matching PCA for face recognition

We present an enhanced principal component analysis (PCA) algorithm for improving rate of face recognition. The proposed pre-processing method, termed as perfect histogram matching, modifies the image histogram to match a Gaussian shaped tonal distribution in the face images such that spatially the entire set of face images presents similar facial gray-level intensities while the face content in the frequency domain remains mostly unaltered. Computationally inexpensive, the perfect histogram matching algorithm proves to yield superior results when applied as a pre-processing module prior to the conventional PCA algorithm for face recognition. Experimental results are presented to demonstrate effectiveness of the technique.