期刊：
Information Fusion,2020年54:61-71 ISSN：1566-2535
通讯作者：
Deng, Xianjun
作者机构：
[Wang, Xu; Wang, Minghua; Deng, Xianjun] Univ South China, Hunan Prov Key Lab UltraFast Micronano Technol &, Sch Elect Engn, Hengyang, Hunan, Peoples R China.;[Yang, Laurence T.] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS, Canada.;[Yi, Lingzhi] Univ South China, Sch Civil Engn, Hengyang, Hunan, Peoples R China.;[Wang, Minghua; Yi, Lingzhi] Univ South China, Cooperat Innovat Ctr Nucl Fuel Cycle Technol & Eq, Hengyang, Hunan, Peoples R China.;[Deng, Xianjun] Hunan Prov Engn Technol Res Ctr Uranium Tailings, Hengyang, Hunan, Peoples R China.
通讯机构：
[Deng, Xianjun] U;Univ South China, 28 Changsheng West Rd, Hengyang 421001, Hunan, Peoples R China.
关键词：
Body sensor networks (BSNs);Health and safety monitoring;Mobile wireless sensor networks (MWSNs);Multi-Sensor fusion;Sensor relocation
摘要：
The body sensor networks (BSNs) have attracted great attention due to their numerous important features and wide applications in health and safety monitoring, especially in some hostile or potentially dangerous workplaces. In this paper, aiming to provide continuous coverage from the initial Region of Interest (ROI) to a New Region of Interest (NROI) to trace the BSNs for human health and safety monitoring, we formulate and define the novel confident information coverage (CIC)-based Intelligent Sensor Relocation for NROI (CIC-ISR-NROI) problem in mobile wireless sensor networks (MWSNs) based on the novel CIC model. For handing the CIC-ISR-NROI problem, we develop two energy-efficient intelligent sensor relocation algorithms based on multi-sensor fusion, the Rapid Relocation Time Low Energy Consumption (RRTLEC) algorithm and optimized RRTLEC algorithm, to relocate redundant mobile sensors from the ROI to cover the NROI in a timely and energy-efficient manner while constructing the communication chain to connect the ROI and the NROI. To verify the effectiveness and efficiency of the proposed schemes, we conduct a series of experiments which correspond to the realistic scenarios in health and safety monitoring in the 272 uranium tailing. Experimental results show that the performance of our approaches is better than the other typical peer approaches by the metrics of the total moving energy consumption and the maximum relocation time.
期刊：
IEEE INTERNET OF THINGS JOURNAL,2020年7(10):9919-9929 ISSN：2327-4662
通讯作者：
Yi, Lingzhi
作者机构：
[Deng, Xianjun; Jiang, Yalan] Univ South China, Sch Elect Engn, Hunan Prov Key Lab Ultrafast Micro Nano Technol &, Hengyang 421001, Peoples R China.;[Yang, Laurence T.; Yi, Lingzhi] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G 2W5, Canada.;[Yi, Lingzhi] Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.;[Chen, Jiaoyan] Nanchang Univ, Sch Informat Engn, Nanchang 330031, Jiangxi, Peoples R China.;[Liu, Yong; Li, Xiangyang] Univ South China, Sch Resource Environm & Safety Engn, Hunan Prov Engn Res Ctr Radioact Control Technol, Hengyang 421001, Peoples R China.
通讯机构：
[Yi, Lingzhi] U;Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.
关键词：
Oceans;Learning automata;Surveillance;Sensors;Internet of Things;Peer-to-peer computing;Barrier coverage;confident information coverage (CIC) model;Internet of Things (IoT);learning automata (LA);smart ocean
摘要：
As an emerging network paradigm, the Internet of Things (IoT) which consists of a significant number of multifunctional and heterogeneous IoT nodes has attracted dramatic attentions from both academia and industry. With the merits of intelligent capacity, desirable scalability, and high reliability, the IoT recently has been applied for smart ocean applications to provide protection for ocean environment monitoring and surveillance. Aiming to provide coverage service for ocean border environmental surveillance, this article studies the barrier coverage problem which investigates how to select a collection of IoT nodes to obtain an IoT node chain and build barrier paths to detect intruders and trespassers crossing the border region of interest. To overcome the disadvantages in the existing works on barrier coverage, we adopt a novel and widely adopted confident information coverage (CIC) model as the fundamental coverage model and formulate the CIC barrier path construction (CICBC) problem with the goals of maximizing the number of barrier paths and minimizing the amount of IoT nodes in each barrier path. We propose a distributed CIC barrier path (CICBP) construction approach based on learning automata (CBLA). The CBLA includes four crucial phases which are initialization phase, learning phase, monitoring phase, and repairing phase. Each IoT node equips a learning automaton. CBLA selects an optimal IoT node to construct the barrier path by learning. The simulation results show that the performance of the CBLA algorithm outperforms two peer algorithms in terms of the number of barrier paths and the average number of nodes in each barrier path.
摘要：
Sensor networks, as a promising network paradigm, have been widely applied in a great deal of critical real-world applications. A key challenge in sensor networks is how to improve and optimize coverage quality which is a fundamental metric to characterize how well a point or a region or a barrier can be sensed by the geographically deployed heterogeneous sensors. Because of the resource-limited, battery-powered and type-diverse features of the sensors, maintaining and optimizing coverage quality includes a significant amount of challenges in heterogeneous sensor networks. Many researchers from both academic and industrial communities have performed numerous significant works on coverage optimization problem in the past decades. Some of them also have surveyed the current models, theories and solutions on the problem of coverage optimization. However, most of the existing surveys and analytical studies ignore how to exploit data fusion and cooperation of the deployed sensors to enhance coverage performance. In this paper, we provide an insightful and comprehensive summarization and classification on the data fusion based coverage optimization problem and techniques. Aiming at overcoming the shortcomings existed in current solutions, we also discuss the future issues and challenges in this area and sketch a general research framework in the context of reinforcement learning.
期刊：
IEEE INTERNET OF THINGS JOURNAL,2019年6(6):9217-9225 ISSN：2327-4662
通讯作者：
Deng, Xianjun
作者机构：
[Dai, Lu; Wang, Bang] Huazhong Univ Sci & Technol, Sch Elect Informat & Commun, Wuhan 430074, Hubei, Peoples R China.;[Yang, Laurence T.] St Francis Xavier Univ, Dept Comp Sci, Antigonish, NS B2G2W5, Canada.;[Deng, Xianjun] Univ South China, Sch Elect Engn, Hunan Prov Key Lab Ultra Fast Micro Nano Technol, Hengyang 421001, Peoples R China.;[Yi, Lingzhi] Univ South China, Sch Civil Engn, Hengyang 421001, Peoples R China.
通讯机构：
[Deng, Xianjun] U;Univ South China, Sch Elect Engn, Hunan Prov Key Lab Ultra Fast Micro Nano Technol, Hengyang 421001, Peoples R China.
关键词：
Confident information coverage (CIC);genetic algorithms (GEAs);Industrial Internet of Things (IIoT);Internet of Things (IoT) node deployment;network lifetime
摘要：
The ever-growing Industrial Internet of Things (IoT) provides a powerful method to sense a series of critical industrial environments. This paper studies how to deploy the fixed number of IoT nodes so that the network lifetime is maximized in a sensing field with obstacles while guaranteeing the requirements of confident information coverage, network connectivity, energy efficiency, fault tolerance, and reliability. An IoT node deployment scheme based on an improved nature-inspired genetic algorithm is proposed to solve the defined constrained optimization problem. In the proposed IoT node deployment scheme, we utilize a population initialization based on the Delaunay triangulation to generate the better initial population, a chromosome modification operation to achieve both connectivity and coverage for each chromosome and a chromosome mirror-crossover operation to produce the better offsprings. Experimental results show that our deployment schema equips better performance in terms of longer network lifetime and comparable coverage ratio compared with the other four peer algorithms.
摘要：
针对具有较大多普勒扩展和时延扩展的车载通信环境,利用后训练序列信道响应携带的信道变化信息,提出一种结合后训练序列的判决反馈信道估计方法。该方法采用最小二乘算法估计后训练序列的信道响应;对前一个正交频分复用(orthogonal frequency division multiplexing, OFDM)符号和后训练序列的信道响应估计值进行系数加权求和来估计当前OFDM符号的信道响应,并利用其4个导频子载波的信道频率响应关系自动获取加权系数;最后,对获得的信道响应估计值进行判决反馈和低通滤波以降低噪声影响。仿真结果表明,与目前取得较好性能的STA(spectral temporal averaging)方法、CDP(constructing data pilot)方法和结合平滑滤波的判决反馈信道估计方法相比,所提方法具有更优的误包率性能。
摘要：
针对多用户配对虚拟MIMO (multiple input multiple output)安全性差,对信道估计器依赖性强的问题,提出一种基于非相干空频码(non-coherent space frequency code, NSFC)和正交频分复用(orthogonal frequency division multiplexing, OFDM)的非协作式虚拟MIMO。在分析NSFC成对错误概率的基础上,给出能满足全分集阶数和最大编码增益的编码准则。为了获得平行子信道传输效果,利用信道循环矩阵奇异值分解(singular value decomposition, SVD)后得到的酉矩阵分别进行预编码和预解码。基于最优NSFC和OFDM预编解码,提出一种新颖的虚拟MIMO策略。该虚拟MIMO在收发两端均无需信道瞬时信息,以非协作方式在单天线内模拟多天线收发效果。理论和仿真分析结果表明,虚拟MIMO系统能有效逼近实际理想MIMO的系统容量和误比特率性能,显著降低了虚拟MIMO系统的检测门限。
