Emerging 5G communication solutions utilize the millimeter wave(mmWave)band to alleviate the spectrum deficit.In the mmWave range,Multiple Input Multiple Output(MIMO)technologies support a large number of simultaneous...Emerging 5G communication solutions utilize the millimeter wave(mmWave)band to alleviate the spectrum deficit.In the mmWave range,Multiple Input Multiple Output(MIMO)technologies support a large number of simultaneous users.In mmWave MIMO wireless systems,hybrid analog/digital precoding topologies provide a reduced complexity substitute for digital precoding.Bit Error Rate(BER)and Spectral efficiency performances can be improved by hybrid Minimum Mean Square Error(MMSE)precoding,but the computation involves matrix inversion process.The number of antennas at the broadcasting and receiving ends is quite large for mm-wave MIMO systems,thus computing the inverse of a matrix of such high dimension may not be practically feasible.Due to the need for matrix inversion and known candidate matrices,the classic Orthogonal Matching Pursuit(OMP)approach will be more complicated.The novelty of research presented in this manuscript is to create a hybrid precoder for mmWave communication systems using metaheuristic algorithms that do not require matrix inversion processing.The metaheuristic approach has not employed much in the formulation of a precoder in wireless systems.Five distinct evolutionary algorithms,such as Harris–Hawks Optimization(HHO),Runge–Kutta Optimization(RUN),Slime Mould Algorithm(SMA),Hunger Game Search(HGS)Algorithm and Aquila Optimizer(AO)are considered to design optimal hybrid precoder for downlink transmission and their performances are tested under similar practical conditions.According to simulation studies,the RUN-based precoder performs better than the conventional algorithms and other nature-inspired algorithms based precoding in terms of spectral efficiency and BER.展开更多
The estimation of sequence or symmetrical components and frequency in three-phase unbalanced power system is of great importance for protection and relay.This paper proposes a new H∞filter based on sparse model to tr...The estimation of sequence or symmetrical components and frequency in three-phase unbalanced power system is of great importance for protection and relay.This paper proposes a new H∞filter based on sparse model to track the sequence components and the frequency of three-phase unbalanced power systems.The inclusion of sparsity improves the error convergence behavior of estimation model and hence short-duration non-stationary PQ events can easily be tracked in the time domain.The proposed model is developed using l1 norm penalty in the cost function of H∞filter,which is quite suitable for estimation across all the three phases of an unbalanced system.This model uses real state space modeling across three phases to estimate amplitude and phase parameters of sequence components.However,frequency estimation uses complex state space modeling and Clarke transformation generates a complex measurement signal from the unbalanced three-phase voltages.The state vector used for frequency estimation consists of two state variables.The proposed sparse model is tested using distorted three-phase signals from IEEE-1159-PQE database and the data generated from experimental laboratory setup.The analysis of absolute and mean square error is presented to validate the performance of the proposed model.展开更多
文摘Emerging 5G communication solutions utilize the millimeter wave(mmWave)band to alleviate the spectrum deficit.In the mmWave range,Multiple Input Multiple Output(MIMO)technologies support a large number of simultaneous users.In mmWave MIMO wireless systems,hybrid analog/digital precoding topologies provide a reduced complexity substitute for digital precoding.Bit Error Rate(BER)and Spectral efficiency performances can be improved by hybrid Minimum Mean Square Error(MMSE)precoding,but the computation involves matrix inversion process.The number of antennas at the broadcasting and receiving ends is quite large for mm-wave MIMO systems,thus computing the inverse of a matrix of such high dimension may not be practically feasible.Due to the need for matrix inversion and known candidate matrices,the classic Orthogonal Matching Pursuit(OMP)approach will be more complicated.The novelty of research presented in this manuscript is to create a hybrid precoder for mmWave communication systems using metaheuristic algorithms that do not require matrix inversion processing.The metaheuristic approach has not employed much in the formulation of a precoder in wireless systems.Five distinct evolutionary algorithms,such as Harris–Hawks Optimization(HHO),Runge–Kutta Optimization(RUN),Slime Mould Algorithm(SMA),Hunger Game Search(HGS)Algorithm and Aquila Optimizer(AO)are considered to design optimal hybrid precoder for downlink transmission and their performances are tested under similar practical conditions.According to simulation studies,the RUN-based precoder performs better than the conventional algorithms and other nature-inspired algorithms based precoding in terms of spectral efficiency and BER.
基金the support of Indian Institute of Information Technology,Bhubaneswar,IndiaVeer Surendra Sai University of Tecnology(Burla),Sambalpur,India,in terms of Laboratory and online Journal facilities to carry out this research work
文摘The estimation of sequence or symmetrical components and frequency in three-phase unbalanced power system is of great importance for protection and relay.This paper proposes a new H∞filter based on sparse model to track the sequence components and the frequency of three-phase unbalanced power systems.The inclusion of sparsity improves the error convergence behavior of estimation model and hence short-duration non-stationary PQ events can easily be tracked in the time domain.The proposed model is developed using l1 norm penalty in the cost function of H∞filter,which is quite suitable for estimation across all the three phases of an unbalanced system.This model uses real state space modeling across three phases to estimate amplitude and phase parameters of sequence components.However,frequency estimation uses complex state space modeling and Clarke transformation generates a complex measurement signal from the unbalanced three-phase voltages.The state vector used for frequency estimation consists of two state variables.The proposed sparse model is tested using distorted three-phase signals from IEEE-1159-PQE database and the data generated from experimental laboratory setup.The analysis of absolute and mean square error is presented to validate the performance of the proposed model.
