Energy-Efficient Low-Complexity Algorithm in 5G Massive MIMO Systems

Energy efficiency(EE)is a critical design when taking into account circuit power consumption(CPC)in fifth-generation cellular networks.These problems arise because of the increasing number of antennas in massive multiple-input multiple-output(MIMO)systems,attributable to inter-cell interference for channel state information.Apart from that,a higher number of radio frequency(RF)chains at the base station and active users consume more power due to the processing activities in digital-to-analogue converters and power amplifiers.Therefore,antenna selection,user selection,optimal transmission power,and pilot reuse power are important aspects in improving energy efficiency in massive MIMO systems.This work aims to investigate joint antenna selection,optimal transmit power and joint user selection based on deriving the closed-form of the maximal EE,with complete knowledge of large-scale fading with maximum ratio transmission.It also accounts for channel estimation and eliminating pilot contamination as antennas M→∞.This formulates the optimization problem of joint optimal antenna selection,transmits power allocation and joint user selection to mitigate inter-cellinterference in downlink multi-cell massive MIMO systems under minimized reuse of pilot sequences based on a novel iterative low-complexity algorithm(LCA)for Newton’s methods and Lagrange multipliers.To analyze the precise power consumption,a novel power consumption scheme is proposed for each individual antenna,based on the transmit power amplifier and CPC.Simulation results demonstrate that the maximal EE was achieved using the iterative LCA based on reasonable maximum transmit power,in the case the noise power is less than the received power pilot.The maximum EE was achieved with the desired maximum transmit power threshold by minimizing pilot reuse,in the case the transmit power allocationρd=40 dBm,and the optimal EE=71.232 Mb/j.

Two-vector Dimensionless Model Predictive Control of PMSM Drives Based on Fuzzy Decision Making

Model predictive controls(MPCs) with the merits of non-linear multi-variable control can achieve better performance than other commonly used control methods for permanent magnet synchronous motor(PMSM) drives.However,the conventional MPCs have various issues,including unsatisfactory steady-state performance,variable switching frequency,and difficult selection of appropriate weighting factors.This paper proposes two different improved MPC methods to deal with these issues.One method is the two-vector dimensionless model predictive torque control(MPTC).Two cost functions(torque and flux) and fuzzy decision-making are used to eliminate the weighting factor and select the first optimum vector.The torque cost function selects a second vector whose duty cycle is determined based on the torque error.The other method is the two-vector dimensionless model predictive current control(MPCC).The first vector is selected the same as in the conventional MPC method.Two separate current cost functions and fuzzy decision-making are used to select the second vector whose duty cycle is determined based on the current error.Both proposed methods utilize the space vector PWM modulator to regulate the switching frequency.Numerical simulation results show that the proposed methods have better steady-state and transient performances than the conventional MPCs and other existing improved MPCs.

A Compact Size 5G Hairpin Bandpass Filter with Multilayer Coupled Line

The multilayer structure is a promising technique used to minimize the size of planar microstrip filters.In the flexible design and incorporation of other microwave components,multilayer band-pass filter results in better and enhanced dimensions.This paper introduces a microstrip fifth-generation(5G)low-frequency band of 2.52–2.65 GHz using a parallel-coupled line(PCL)Bandpass filter and multilayer(ML)hairpin Bandpass filter.The targeted four-pole resonator has a center frequency of 2.585 GHz with a bandwidth of 130 MHz.The filters are designed with a 0.1 dB passband ripple with a Chebyshev response.The hairpin-line offers compact filter design structures.Theoretically,they can be obtained by bending half-wavelength resonator resonators with parallel couplings into a“U”shape.The proposed configuration of the parllel-coupled line resonator is used to design the ML band-pass filter.The FR4 substrate with a dielectric constant(Er)of 4.3 and 1.6 mm thickness was used.A comparative analysis between the simulated insertion loss and the reflection cofficient of substrates RO3003 and FR4 was performed to validate the eficiency of the proposed filter design.Simulation of PCL filter is accom-plished using computer simulation technology(CST)and an advanced design system(ADS)software.The PCL Bandpass filter was experimentally validated and a total tally between simulation results and measured results were achieved demonstrating a well-measured reflection coefficient.The simulated results obtained by the hairpin ML bandpass filter show that the circuit performs well in terms of Scattering(S)parameters and the filter size is significantly reduced.