Transceiver Design Of Industrial Wireless Communications Under Impulsive Noise

With the gradual commercialization of 5G technology worldwide,the smart industrial internet of things(IIo T)has put forward new standards for wireless communication performance such as spectrum efficiency,energy efficiency,and data transmission reliability to meet the needs of wireless communication applications.Impulsive noise,as a source of interference that exists widely in industrial communication scenarios where large machinery and intelligent equipment robots exist in digital mines,smart ports,smart factories,etc.,can cause sudden data errors in the communication system,and significantly reduce the reliability of data transmission and communication quality.To cope with these challenges,the massive noise sources in industrial Io T is taken as the background,and orthogonal frequency division multiplexing technology as the technical support,then the system sum rate,energy efficiency,and system error rate(SER)are studied from the perspectives of transceiver design,precoder design,and impulsive noise mitigation schemes to improve industrial wireless communications performance.The main work and contributions of this paper are as follows:To investigate how the impulsive noise impacts the performance of industrial wireless communication,we build the multiuser multiple-input single-output(MUMISO)-OFDM system model whose transmitter and receiver are designed jointly.Middleton Class A noise model is introduced to simulate industrial impulsive noise distribution.To improve communication performance,we design a precoding scheme and impulsive noise mitigation module at the transmitter and receiver,respectively.It is challenging to ensure efficient and reliable transmission with quality of service guarantee for machine-type communication devices.Two precoding schemes are designed to improve communication effectiveness at the transmitter.More specifically,the precoder design scheme which combines semidefinite relaxation with differenceof-two-convex-function iterative algorithm,is developed by utilizing the Dinkelbach method to improve the system effectiveness.To decrease the computational complexity,we devise the quadratic-based fractional programming algorithm,which decouples the variables by using a quadratic transform method.On this basis,the impulsive noise mitigation scheme is studied to reduce the SER at the receiver.With the goal of improving the reliability of industrial wireless communications,we propose a hybrid nonlinear impulsive noise mitigation scheme and then derive its closed-form expression of SER.The simulation results show that the proposed quadratic-based fractional programming algorithm achieves superior performance while the hybrid nonlinear impulsive noise mitigation scheme decreases the SER of industrial wireless communications.On this basis,further operation for guaranteeing quality of service as well as decoupling the variables and decreasing the computational complexity is conducted,in which a precoding algorithm is designed to maximize the system sum rate by utilizing the quadratic transform method.Furthermore,we derive the closed-form expression of the system sum rate under the impulsive noise environment.Then,a deep clipping module is designed at the receiver to achieve impulsive noise mitigation,and the closedform expression of SER is given.The simulation results demonstrate that the proposed quadratic-based precoding algorithm and the deep clipping impulsive noise mitigation scheme have significant performance advantages compared with the existing scheme.This thesis contains 23 figures,6 tables and 82 references.