The hest for technological advancement in mobile communication is due to augmentation of wireless user. The deployment of 5G mobile communication is less than 4G mobile communication due to challenges in security like cyberwarfare, espionage, critical infrastructure threats. Nevertheless, critic of neurological discomforts, tissue damage in living organisms occur in the existence of EMF radiation. Also, physical scarcity for spectral efficiency arises due to ubiquitous data traffic. Inspite of these disputes data rate, low latency, device to device communication is also a challenge. In this paper we provide a survey on radiation effects, security threats, traffic management.
In this paper, antipodal Vivaldi antenna is designed for 5th generation (5G) mobile communication and Ku-band applications. The proposed designed has three layers. The upper layer consists of eight-element array of split-shaped leaf structures, which is fed by a 1-to-8 power divider network. Middle layer is a substrate made of Rogers 5880. The bottom layer consists of truncated ground and shorter mirror-image split leaf structures. The overall size of the designed antenna is confined significantly to 33.31 × 54.96 × 0.787 (volume in mm3), which is equivalent to 2λo× 3.3λo× 0.05λo (λo is free-space wavelength at 18 GHz). Proposed eight elements antenna is multi-band in nature covering Ku-bands (14.44–20.98 GHz), two millimeter wave (mmW) bands i.e., 24.34–29 GHz and 33–40 GHz, which are candidate frequency bands for 5G communications. The Ku-Band is suitable for radar applications. Proposed eight elements antenna is very efficient and has stable gain for 5G mobile communication and Ku-band applications. The simulation results are experimentally validated by testing the fabricated prototypes of the proposed design.
In order to overcome the limitations of traditional road test methods in 5G mobile communication network signal coverage detection, a signal coverage detection algorithm based on distributed sensor network for 5G mobile communication network is proposed. First, the received signal strength of the communication base station is collected and pre-processed by randomly deploying distributed sensor nodes. Then, the neural network objective function is modified by using the variogram function, and the initial weight coefficient of the neural network is optimized by using the improved particle swarm optimization algorithm. Next, the trained network model is used to interpolate the perceptual blind zone. Finally, the sensor node sampling data and the interpolation estimation result are combined to generate an effective coverage of the 5G mobile communication network signal. Simulation results indicate that the proposed algorithm can detect the real situation of 5G mobile communication network signal coverage better than other algorithms, and has certain feasibility and application prospects.
High-Gain Vivaldi Antenna with Wide Bandwidth Characteristics for 5G Mobile and Ku-Band Radar Applications