Analysis of Internet of Things (IoT) sensor data is a key for achieving city smartness. In this paper a multitier fog computing model with large-scale data analytics service is proposed for smart cities applications. The multi-tier fog is consisted of ad-hoc fogs and dedicated fogs with opportunistic and dedicated computing resources, respectively. The proposed new fog computing model with clear functional modules is able to mitigate the potential problems of dedicated computing infrastructure and slow response in cloud computing. We run analytics benchmark experiments over fogs formed by Rapsberry Pi computers with a distributed computing engine to measure computing performance of various analytics tasks, and create easy-to-use workload models. QoS aware admission control, offloading and resource allocation schemes are designed to support data analytics services, and maximize analytics service utilities. Availability and cost models of networking and computing resources are taken into account in QoS scheme design. A scalable system level simulator is developed to evaluate the fog based analytics service and the QoS management schemes. Experiment results demonstrate the efficiency of analytics services over multi-tier fogs and the effectiveness of the proposed QoS schemes. Fogs can largely improve the performance of smart city analytics services than cloud only model in terms of job blocking probability and service utility.

Video games, virtual reality, augmented reality, and smart appliances all call for a new way for users to interact and control them. This paper develops high-preCision Acoustic Tracker (CAT), which aims to replace a traditional mouse and let a user control various devices by moving a smartphone in the air. At its heart lies a distributed Frequency Modulated Continuous Waveform (FMCW) that can accurately estimate the distance between a transmitter and a receiver that are separate and unsynchronized. We further develop an optimization framework to combine FMCW estimation with Doppler shifts to enhance the accuracy. We implement CAT on a mobile phone. The performance evaluation and user study show that our system achieves high tracking accuracy and ease of use using existing hardware.

This article provides a comprehensive overview of the scientific and technological advances that have the capability to shape future 6G vehicle-to-everything (6G-V2X) communications.

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Non-orthogonal multiple access (NOMA) is emerging as a promising multiple access technology for the 5th generation cellular networks to address the fast growing mobile data traffic. It applies superposition coding in transmitters, allowing simultaneous allocation of the same frequency resource to multiple intra-cell users. Successive interference cancellation is used at the receivers to cancel intra-cell interference. User pairing and power allocation (UPPA) is a key design aspect of NOMA. Existing UPPA algorithms are mainly based on exhaustive search method with extensive computation complexity, which can severely affect the NOMA performance. In this paper we propose a fast proportional fairness (PF) scheduling based UPPA algorithm to address the problem. The novel idea is to form user pairs around the users with the highest PF metrics with pre-configured fixed power allocation. System level simulation results show the proposed algorithm is significantly faster (7 times faster for the scenario with 20 users) with a negligible throughput loss than the existing exhaustive search algorithm. Introduction:Recently an exponential growth of mobile devices was witnessed with more than half a billion mobile devices (mainly smartphones) added in 2015 [1]. In addition it is expected there are 50 billions Internet of Things (IoT) devices connected to Internet by 2020. The ever-increasing smart mobile devices and IoT devices are driving a rapid growth of mobile data traffic. Significant innovations from cellular networks are needed to address the huge traffic, e.g., ultra-dense small cells, higher order sectorization, massive MIMO, cloud RAN and millimeter wave technologies [2].Multiple access is a key design aspect of cellular networks. Orthogonal multiple access (OMA) has been used in the first to the 4th generation cellular networks. To achieve higher spectrum efficiency non-orthogonal multiple access (NOMA) is considered as a promising multiple access technology for the 5th generation cellular networks. The root of NOMA is the superposition coding, which allows simultaneous allocation of the same frequency resource to multiple users. Then successive interference cancellation is used at the receivers to cancel intra-cell interference. Research on the application and evaluation of NOMA to the downlink communications of cellular networks has been conducted, reporting around 20% throughput gain over OMA [3,4,5].In this paper we focus on the problem of user pairing and power allocation (UPPA) for NOMA in downlink communications, which determines the set of intra-cell users multiplexed over the same frequency resource blocks and the power allocation to these users. UPPA is a key decision to make for NOMA with a significant impact on NOMA performance in terms of spectrum efficiency and computational complexity. However, existing UPPA algorithms are mainly based on exhaustive search to find proper user pairs and power allocation, which can result in excessive scheduling processing delay and lead to large system performance loss...

Current methods of fault diagnosis for the grounding grid using DC or AC are limited in accuracy and cannot be used to identify the locations of the faults. In this study, a new method of fault diagnosis for substation grounding grids is proposed using a square-wave. A frequency model of the grounding system is constructed by analyzing the frequency characteristics of the soil and the grounding conductors into which two different frequency square-wave sources are injected. By analyzing and comparing the corresponding information of the surface potentials of the output signals, the faults of the grounding grid can be diagnosed and located. Our method is verified by software simulation, scale model experiments and field experiments.

In this paper a Markov chain based analytical model is proposed to evaluate the slotted CSMA/CA algorithm specified in the MAC layer of IEEE 802.15.4 standard. The analytical model consists of two two-dimensional Markov chains, used to model the state transition of an 802.15.4 device, during the periods of a transmission and between two consecutive frame transmissions, respectively. By introducing the two Markov chains a small number of Markov states are required and the scalability of the analytical model is improved. The analytical model is used to investigate the impact of the CSMA/CA parameters, the number of contending devices, and the data frame size on the network performance in terms of throughput and energy efficiency. It is shown by simulations that the proposed analytical model can accurately predict the performance of slotted CSMA/CA algorithm for uplink, downlink and bi-direction traffic, with both acknowledgement and non-acknowledgement modes. Index Terms-IEEE 802.15.4, slotted CSMA/CA, wireless personal area network, MAC, Markov chain, ZigBee.