Zobrazeno 1 - 10
of 256
pro vyhledávání: '"Xiongwen ZHAO"'
Publikováno v:
IET Communications, Vol 16, Iss 16, Pp 1923-1933 (2022)
Abstract In order to overcome the disadvantages of traditional channel simulation approaches and achieve more accurate millimetre‐wave (mmWave) channel simulation under the condition of limited measured data, a novel Long Short‐term Memory Networ
Externí odkaz:
https://doaj.org/article/16a72aa5f5874c86862286d33f4bbfb0
Publikováno v:
Tongxin xuebao, Vol 43, Pp 113-125 (2022)
In order to reduce the number of road side unit (RSU) and meet the needs of mobile vehicle users for processing latency-sensitive and computation-intensive tasks, a context-aware resource allocation algorithm was proposed based on parked cars.Road si
Externí odkaz:
https://doaj.org/article/55602909483b4e929063b361ce684f2d
Publikováno v:
Tongxin xuebao, Vol 43, Pp 42-52 (2022)
To improve the spectrum efficiency and enhance the information security of wireless network, a sum secrecy rate maximization-based robust resource allocation algorithm was proposed for a downlink multicarrier NOMA security communication system.Firstl
Externí odkaz:
https://doaj.org/article/74e238599bec45f8997319d89f607247
Autor:
Zihao Fu, Yu Zhang, Xiongwen Zhao, Fei Du, Suiyan Geng, Peng Qin, Zhenyu Zhou, Lei Zhang, Suhong Chen
Publikováno v:
IET Communications, Vol 15, Iss 19, Pp 2425-2438 (2021)
Abstract In this work, an artificial neural network (ANN) based time‐varying channel modeling framework is proposed, including a playback model and a prediction model. The purpose of the ANN‐based modeling framework is to playback 5G measured rad
Externí odkaz:
https://doaj.org/article/02a59bda608f476dbea9cb8ce9e948a9
Publikováno v:
IET Communications, Vol 15, Iss 9, Pp 1240-1248 (2021)
Abstract In this paper, grey genetic optimization model (GGOM) is proposed for predicting insufficient channel parameters without increasing the amount of measurement data. Based on the millimetre wave 28 GHz indoor measurement data for both LOS and
Externí odkaz:
https://doaj.org/article/7ea28e1648004741ab638091d6dc54e4
Publikováno v:
Tongxin xuebao, Vol 42, Pp 111-121 (2021)
To solve the problem of large power consumption caused by a large number of phase shifter (PS) in millimeter wave multi-antenna systems, a new type of dynamic connection structure was designed.With the goal of maximizing spectrum efficiency, two hybr
Externí odkaz:
https://doaj.org/article/2b6c55f18fa340a48521555a87612d56
Publikováno v:
Sensors, Vol 23, Iss 8, p 3884 (2023)
With the rapid development of the 5G power Internet of Things (IoT), new power systems have higher requirements for data transmission rates, latency, reliability, and energy efficiency. Specifically, the hybrid service of enhanced mobile broadband (e
Externí odkaz:
https://doaj.org/article/59429708d1834c5889c64ee7916a99ef
Publikováno v:
Tongxin xuebao, Vol 42, Pp 150-159 (2021)
In view of the problems of severe access conflicts, high queue backlog, and low energy efficiency in the massive terminal access scenario of the power Internet of things (power IoT) in 6G era, a context-aware learning-based access control (CLAC) algo
Externí odkaz:
https://doaj.org/article/098df3b567304f7ea5787a737ff090b7
Publikováno v:
IEEE Access, Vol 8, Pp 203478-203487 (2020)
With the development and expansion of smart grid systems, vehicle-to-grid (V2G) has become a new type of energy interaction based on Internet of Electric Vehicles (IoEVs). By leveraging the charging/discharging capabilities of EVs, V2G can be impleme
Externí odkaz:
https://doaj.org/article/dff1ffcbb3344f6fa2e7ab46db81eff1
Autor:
Huixia Ding, Sicheng Zhu, Sachula Meng, Jinxia Han, Heng Liu, Miao Wang, Jiayan Liu, Peng Qin, Xiongwen Zhao
Publikováno v:
Sensors, Vol 22, Iss 21, p 8436 (2022)
With the vigorous development of information and communication technology, mobile internet has undergone tremendous changes. How to achieve global coverage of the network has become the primary problem to be solved. GEO satellites and LEO satellites,
Externí odkaz:
https://doaj.org/article/df14e6e3a9c846439521efa88a6f86fe