Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters ...Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.展开更多
In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connectio...In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connection requests and huge traffic load from all kinds of smart devices,e.g.bike,watch,phone,ring,glasses,shoes,etc..To solve this hard problem in distributed scenarios with massive competing devices,this paper proposes and evaluates a Neighbor-Aware Multiple Access(NAMA) protocol,which is scalable and adaptive to different connectivity size and traffic load.By exploiting acknowledgement signals broadcasted from the neighboring devices with successful packet transmissions,NAMA is able to turn itself from a contention-based random access protocol to become a contention-free deterministic access protocol with particular transmission schedules for all neighboring devices after a short transition period.The performance of NAMA is fully evaluated from random state to deterministic state through extensive computer simulations under different network sizes and Contention Window(CW)settings.Compared with traditional IEEE802.11 Distributed Coordination Function(DCF),for a crowded network with 50 devices,NAMA can greatly improve system throughput and energy efficiency by more than 110%and210%,respectively,while reducing average access delay by 53%in the deterministic state.展开更多
The coexistence of wireless body sensor networks(WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral effi...The coexistence of wireless body sensor networks(WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral efficiency are two key performance evaluation metrics for wireless communication networks. In this paper, the fundamental tradeoff between energy efficiency and area spectral efficiency of WBSNs is first investigated under the Poisson point process(PPP) model and Matern hard-core point process(HCPP) model using stochastic geometry. The circuit power consumption is taken into consideration in energy efficiency calculation. The tradeoff judgement coefficient is developed and is shown to serve as a promising complementary measure. In addition, this paper proposes a new nearest neighbour distance power control strategy to improve energy efficiency. We show that there exists an optimal transmit power highly dependant on the density of WBSNs and the nearest neighbour distance. Some important properties are also addressed in the analysis of coexisting WBSNs based on the IEEE 802.15.4 standard, such as the impact of intensity nodes distribution,optimal guard zone, and outage probability. Simulation results show that the proposed power control design can reduce the outage probability and enhance energy efficiency. Energy efficiency and area spectral efficiency of the HCPP model are better than those of the PPP model. In addition, the optimal density of WBSNs coexistence is obtained.展开更多
CaCu(3-x)FexTi4O(12)(x=0, 0.015, 0.03, 0.045, 0.06) ceramics were synthesized by sol-gel method. The electrical conduction and dielectric measurements show that the doping of a very small amount of Fe(3+) ion...CaCu(3-x)FexTi4O(12)(x=0, 0.015, 0.03, 0.045, 0.06) ceramics were synthesized by sol-gel method. The electrical conduction and dielectric measurements show that the doping of a very small amount of Fe(3+) ions greatly reduces the low-frequency dielectric constants and leakage, and enhances grain resistivity. For the doped samples, the appearance of the strong low-frequency peaks in the spectra of dielectric loss confirms that the doping of Fe(3+) ions induces the contact-electrode effect on ceramic surface. These great changes of electrical properties may originate from the reduced amount of oxygen vacancies by doping Fe(3+)展开更多
The UK has set plans to increase offshore wind capacity from 22GW to 154GW by 2030. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle ser...The UK has set plans to increase offshore wind capacity from 22GW to 154GW by 2030. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants. Our study concludes with identification of technological priorities and outlines their integration into a new ‘symbiotic digital architecture’ to deliver the future of offshore wind farm lifecycle management.展开更多
基金support from the Natural Science Foundation of China (Grant No. 61210002, 61371110)EU H2020 ITN 5G Wireless project (No. 641985)+1 种基金EU H2020 RISE TESTBED project (No. 734325)EPSRC TOUCAN project (Grant No. EP/L020009/1)
文摘Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.
基金funded by the National Natural Science Foundation of China (Grant No.61231009)the National HighTech R&D Program of China(863)(Grant No.2014AA01A701)+5 种基金the National Science and Technology Major Project(Grant No. 2015ZX03001033-003)Ministry of Science and Technology International Cooperation Project(Grant No.2014DFE10160)the Science and Technology Commission of Shanghai Municipality(Grant No.14ZR1439600)the EU H2020 5G Wireless project(Grant No.641985)the EU FP7 QUICK project(Grant No. PIRSES-GA-2013-612652)the EPSRC TOUCAN project(Grant No.EP/L020009/1)
文摘In order to support massive Machine Type Communication(mMTC) applications in future Fifth Generation(5G) systems,a key technical challenge is to design a highly effective multiple access protocol for massive connection requests and huge traffic load from all kinds of smart devices,e.g.bike,watch,phone,ring,glasses,shoes,etc..To solve this hard problem in distributed scenarios with massive competing devices,this paper proposes and evaluates a Neighbor-Aware Multiple Access(NAMA) protocol,which is scalable and adaptive to different connectivity size and traffic load.By exploiting acknowledgement signals broadcasted from the neighboring devices with successful packet transmissions,NAMA is able to turn itself from a contention-based random access protocol to become a contention-free deterministic access protocol with particular transmission schedules for all neighboring devices after a short transition period.The performance of NAMA is fully evaluated from random state to deterministic state through extensive computer simulations under different network sizes and Contention Window(CW)settings.Compared with traditional IEEE802.11 Distributed Coordination Function(DCF),for a crowded network with 50 devices,NAMA can greatly improve system throughput and energy efficiency by more than 110%and210%,respectively,while reducing average access delay by 53%in the deterministic state.
基金supported by EPSRC TOUCAN Project (Grant No. EP/L020009/1)EU FP7 QUICK Project (Grant No. PIRSES-GA-2013-612652)+3 种基金EU H2020 ITN 5G Wireless Project (Grant No. 641985)National Natural Science Foundation of China (Grant Nos. 61210002, 61401256)MOST 863 Project in 5G (Grant No. 2014AA01A701)International S&T Cooperation Program of China (Grant No. 2014DFA11640)
文摘The coexistence of wireless body sensor networks(WBSNs) is a very challenging problem, due to strong interference, which seriously affects energy consumption and spectral reuse. The energy efficiency and spectral efficiency are two key performance evaluation metrics for wireless communication networks. In this paper, the fundamental tradeoff between energy efficiency and area spectral efficiency of WBSNs is first investigated under the Poisson point process(PPP) model and Matern hard-core point process(HCPP) model using stochastic geometry. The circuit power consumption is taken into consideration in energy efficiency calculation. The tradeoff judgement coefficient is developed and is shown to serve as a promising complementary measure. In addition, this paper proposes a new nearest neighbour distance power control strategy to improve energy efficiency. We show that there exists an optimal transmit power highly dependant on the density of WBSNs and the nearest neighbour distance. Some important properties are also addressed in the analysis of coexisting WBSNs based on the IEEE 802.15.4 standard, such as the impact of intensity nodes distribution,optimal guard zone, and outage probability. Simulation results show that the proposed power control design can reduce the outage probability and enhance energy efficiency. Energy efficiency and area spectral efficiency of the HCPP model are better than those of the PPP model. In addition, the optimal density of WBSNs coexistence is obtained.
基金support from the National Natural Science Foundation of China (Nos.51172166 and 51202078)the Huazhong University of Science and Technology, China (No. 01-18-185011)
文摘CaCu(3-x)FexTi4O(12)(x=0, 0.015, 0.03, 0.045, 0.06) ceramics were synthesized by sol-gel method. The electrical conduction and dielectric measurements show that the doping of a very small amount of Fe(3+) ions greatly reduces the low-frequency dielectric constants and leakage, and enhances grain resistivity. For the doped samples, the appearance of the strong low-frequency peaks in the spectra of dielectric loss confirms that the doping of Fe(3+) ions induces the contact-electrode effect on ceramic surface. These great changes of electrical properties may originate from the reduced amount of oxygen vacancies by doping Fe(3+)
文摘The UK has set plans to increase offshore wind capacity from 22GW to 154GW by 2030. With such tremendous growth, the sector is now looking to Robotics and Artificial Intelligence (RAI) in order to tackle lifecycle service barriers as to support sustainable and profitable offshore wind energy production. Today, RAI applications are predominately being used to support short term objectives in operation and maintenance. However, moving forward, RAI has the potential to play a critical role throughout the full lifecycle of offshore wind infrastructure, from surveying, planning, design, logistics, operational support, training and decommissioning. This paper presents one of the first systematic reviews of RAI for the offshore renewable energy sector. The state-of-the-art in RAI is analyzed with respect to offshore energy requirements, from both industry and academia, in terms of current and future requirements. Our review also includes a detailed evaluation of investment, regulation and skills development required to support the adoption of RAI. The key trends identified through a detailed analysis of patent and academic publication databases provide insights to barriers such as certification of autonomous platforms for safety compliance and reliability, the need for digital architectures for scalability in autonomous fleets, adaptive mission planning for resilient resident operations and optimization of human machine interaction for trusted partnerships between people and autonomous assistants. Our study concludes with identification of technological priorities and outlines their integration into a new ‘symbiotic digital architecture’ to deliver the future of offshore wind farm lifecycle management.