An Adaptive Power Allocation Scheme for Performance Improvement of Cooperative SWIPT NOMA Wireless Networks

Future wireless networks demand high spectral efficiency,energy efficiency and reliability.Cooperative non-orthogonal multiple access(NOMA)with simultaneous wireless information and power transfer(SWIPT)is considered as one of the novel techniques to meet this demand.In this work,an adaptive power allocation scheme called SWIPT based adaptive power allocation(SWIPT-APA-NOMA)is proposed for a power domain NOMA network.The proposed scheme considers the receiver sensitivity of the end users while calculating the power allocation coefficients in order to prevent wastage of power allocated to user in outage and by offering priority to any one of the users to use maximum harvested power.A detailed analysis on the bit error rate(BER)performance of the proposed scheme is done and closed form expression is obtained.Simulations have been carried out with various parameters that influence the receiver sensitivity and the results show that the network achieves better outage and BER performance using the proposed scheme.It is found that the proposed scheme leads to a ten-fold decrease in transmit power for the same error performance of a fixed power allocation scheme.Further,it offers 96.06%improvement in the capacity for a cumulative noise figure and fading margin of 10 dB.

Mobile Station Position Estimation using Remote Radio Head with Adaptive Power Control

The adaptive power control of CDMA （Code Division Multiple Access） communications between multiple MSs （Mobile Stations） with a link-budget based SIR （Signal-to-lnterference Ratio） estimate is applied to inner loop power control algorithms. CTR （Consecutive Transmit-Power-Control Ratio） calculated from these algorithms can estimate MS speed, together with MS moving distance, but cannot estimate MS position. In this paper, RRH （Remote Radio Head） is introduced and it is concluded that BS （Base Station） calculates MS distance with CTR from one of RRHs, in addition BS that has RSSIs （Received Signal Strength Indicators） information from other two RRHs can estimate MS position.

NOMA with Adaptive Transmit Power Using Intelligent Reflecting Surfaces

In this article,we use Intelligent Reflecting Surfaces(IRS)to improve the throughput of Non Orthogonal Multiple Access(NOMA)with Adaptive Transmit Power(ATP).The results are valid for Cognitive Radio Networks(CRN)where secondary source adapts its power to generate low interference at primary receiver.In all previous studies,IRS were implemented with fixed transmit power and previous results are not valid when the power of the secondary source is adaptive.In CRN,secondary nodes are allowed to transmit over the same band as primary users since they adapt their power to minimize the generated interference.Each NOMA user has a subset of dedicated reflectors.At any NOMA user,all IRS reflections have the same phase.CRN-NOMA using IRS offers 7,13,20 dB gain vs.CRN-NOMAwithout IRS for N=8,16,32 reflectors.We also evaluate the effects of primary interference.The results are valid for any number of NOMA users,Quadrature Amplitude Modulation(QAM)and Rayleigh channels.

A wideband LC-VCO with small VCO gain variation and adaptive power control

A wideband LC tank voltage-controlled-oscillator（VCO） is proposed.To solve the impacts of wideband operation on VCO gain（K_（VCO）） variation and start-up constraint,a binary-weighted varactor array and a binary-weighted negative resistance array all with optimal unit values are designed.Implemented in a 0.18μm CMOS process,the proposed VCO shows a frequency tuning range from 1.9 to 3.1 GHz,with a current consumption varying accordingly from 14.2 to 4 mA from a 1.8 V supply.With the proposed K_（VCO） suppression technique,the K_（VCO） varies from 50 to 60 MHz/V in the entire frequency range.The measured phase noise is -117 dBc/Hz at a 1 MHz offset from a 3 GHz carrier.

Adaptive Power Control Based on Double-layer Q-learning Algorithm for Multi-parallel Power Conversion Systems in Energy Storage Station

An energy storage station(ESS)usually includes multiple battery systems under parallel operation.In each battery system,a power conversion system(PCS)is used to connect the power system with the battery pack.When allocating the ESS power to multi-parallel PCSs in situations with fluctuating operation,the existing power control methods for parallel PCSs have difficulty in achieving the optimal efficiency during a long-term time period.In addition,existing Q-learning algorithms for adaptive power allocation suffer from the curse of dimensionality.To overcome these challenges,an adaptive power control method based on the double-layer Q-learning algorithm for n parallel PCSs of the ESS is proposed in this paper.First,a selection method for the power allocation coefficient is developed to avoid repeated actions.Then,the outer action space is divided into n+1 power allocation modes according to the power allocation characteristics of the optimal operation efficiency.The inner layer uses an actor neural network to determine the optimal action strategy of power allocations in the non-steady state.Compared with existing power control methods,the proposed method achieves better performance for both static and dynamic operation efficiency optimization.The proposed method optimizes the overall operation efficiency of PCSs effectively under the fluctuating power outputs of the ESS.

Adaptive Energy-Efficient Power Allocation for DAS with Imperfect Channel State Information and Antenna Selection

Considering that perfect channel state information(CSI) is difficult to obtain in practice,energy efficiency(EE) for distributed antenna systems(DAS) based on imperfect CSI and antennas selection is investigated in Rayleigh fading channel.A novel EE that is defined as the average transmission rate divided by the total consumed power is introduced.In accordance with this definition,an adaptive power allocation(PA) scheme for DAS is proposed to maximize the EE under the maximum transmit power constraint.The solution of PA in the constrained EE optimization does exist and is unique.A practical iterative algorithm with Newton method is presented to obtain the solution of PA.The proposed scheme includes the one under perfect CSI as a special case,and it only needs large scale and statistical information.As a result,the scheme has low overhead and good robustness.The theoretical EE is also derived for performance evaluation,and simulation result shows the validity of the theoretical analysis.Moreover,EE can be enhanced by decreasing the estimation error and/or path loss exponents.

Combining Task Scheduling in Power Adaptive Dynamic Reconfigurable System

Supplying the electronic equipment by exploiting ambient energy sources is a hot spot. In order to achieve the match between power supply and demands under the variance of environments at real time, a reconfigurable technique is taken. In this paper, a dynamic power consumption model by using a lookup table as a unit is proposed. Then, we establish a system-level task scheduling model according to the task type. Based on single instruction multiple data （SIMD） architecture which contains a processing system and a control system with a Nios II processor, a practical dynamic reconfigurable system is built. The approach is evaluated on a hardware platform. The test results show that the system can automatically adjust the power consumption in case of external energy input changing. The utilization of the system dynamic power of their portion is from 80.05% to 91.75% during the first task assignment. During the entire processing cycle, the total energy efficiency is 97.67%.

MULTICARRIER DS-CDMA WITH ADAPTIVE MODULATION AND POWER ALLOCATION

Adaptive modulation and power allocation is introduced into the multicarrier DS-CDMA system to improve the system performance and bandwidth efficiency. First, the systemdesign appropriate for adaptive modulation and power allocation is given, then the algorithmof adaptive modulation and power allocation is applied. Simulation results demonstrate greatperformance improvement compared with the fixed modulated one.

Novel Energy-Efficient Opportunistic Routing Protocol for Marine Wireless Sensor Networks Based on Compressed Sensing and Power Control

In marine wireless sensor networks(MWSNs),an appropriate routing protocol is the key to the collaborative collection and efficient transmission of massive data.However,designing an appropriate routing protocol under the condition of sparse marine node deployment,highly dynamic network topology,and limited node energy is complicated.Moreover,the absence of continuous endto-end connection introduces further difficulties in the design of routing protocols.In this case,we present a novel energy-efficient opportunistic routing(Novel Energy-Efficient Opportunistic Routing,NEOR)protocol for MWSNs that is based on compressed sensing and power control.First,a lightweight time-series prediction method-weighted moving average method is proposed to predict the packet advancement value such that the number of location information that is exchanged among a node and its neighbor nodes can be minimized.Second,an adaptive power control mechanism is presented to determine the optimal transmitting power and candidate nodeset on the basis of node mobility,packet advancement,communication link quality,and remaining node energy.Subsequently,a timer-based scheduling algorithm is utilized to coordinate packet forwarding to avoid packet conflict.Furthermore,we introduce the compressed sensing theory to compress perceptual data at source nodes and reconstruct the original data at sink nodes.Therefore,energy consumption in the MWSNs is greatly reduced due to the decrease in the amount of data perception and transmission.Numerical simulation experiments are carried out in a wide range of marine scenarios to verify the superiority of our approach over selected benchmark algorithms.

Time-domain clustered transmit power adaptation for OFDM system in fading channels

This paper proposes a time-domain clustered transmitter power adaptation scheme for orthogonal frequency division multiplexing (OFDM) system, which can significantly reduce the feedback amount during power adaptation comparison with conventional frequency-domain adaptation schemes. It was found that the cluster size plays an important role on the adaptation performance, especially for the vehicular environment. Simulation results showed that using Lagrange interpolation to obtain an explicit curve of Doppler frequency vs cluster size yields good trade-off between the resulted bit error rate (BER) and the amount of feedback.

Nonparametric VSS-APA based on precise background noise power estimate

The adaptive algorithm used for echo cancellation(EC) system needs to provide 1) low misadjustment and 2) high convergence rate. The affine projection algorithm(APA) is a better alternative than normalized least mean square(NLMS) algorithm in EC applications where the input signal is highly correlated. Since the APA with a constant step-size has to make compromise between the performance criteria 1) and 2), a variable step-size APA(VSS-APA) provides a more reliable solution. A nonparametric VSS-APA(NPVSS-APA) is proposed by recovering the background noise within the error signal instead of cancelling the a posteriori errors. The most problematic term of its variable step-size formula is the value of background noise power(BNP). The power difference between the desired signal and output signal, which equals the power of error signal statistically, has been considered the BNP estimate in a rough manner. Considering that the error signal consists of background noise and misalignment noise, a precise BNP estimate is achieved by multiplying the rough estimate with a corrective factor. After the analysis on the power ratio of misalignment noise to background noise of APA, the corrective factor is formulated depending on the projection order and the latest value of variable step-size. The new algorithm which does not require any a priori knowledge of EC environment has the advantage of easier controllability in practical application. The simulation results in the EC context indicate the accuracy of the proposed BNP estimate and the more effective behavior of the proposed algorithm compared with other versions of APA class.

Adaptive Subband Bit and Power Loading Algorithm and its Application to OFDM Based IEEE 802 .16e

For OFDM systems with hundreds or thousands subcarriers with the adaptive bit and power loading according to each subcarrier , the signaling overhead will be awfully large. However, the adaptive bit and power loading according to “subband” is an effective solution to this problem, with which the signaling overhead is expected to be dramatically decreased at the cost of some performance loss. In this paper, based on Ref . [5] but with some modification to the subband bit and power loading algorithm, we apply the algorithm to the IEEE 802.16e OFDM system. The results show that the modified subband bit and power loading algorithm can achieve better BER performance and the signaling overhead is reduced by 75% at the cost of performance loss less than 1 dB if the number of subcarriers per subband is 4 when the BER is around 10^-3.

Adaptive fractional integral terminal sliding mode power control of UPFC in DFIG wind farm penetrated multimachine power system

With an aim to improve the transient stability of a DFIG wind farm penetrated multimachine power system(MPN),an adaptive fractional integral terminal sliding mode power control(AFITSMPC)strategy has been proposed for the unified power flow controller(UPFC),which is compensating the MPN.The proposed AFITSMPC controls the dq-axis series injected voltage,which controls the admittance model(AM)of the UPFC.As a result the power output of the DFIG stabilizes which helps in maintaining the equilibrium between the electrical and mechanical power of the nearby generators.Subsequently the rotor angular deviation of the respective generators gets recovered,which significantly stabilizes the MPN.The proposed AFITSMPC for the admittance model of the UPFC has been validated in a DFIG wind farm penetrated 2 area 4 machine power system in the MATLAB environment.The robustness and efficacy of the proposed control strategy of the UPFC,in contrast to the conventional PI control is vindicated under a number of intrinsic operating conditions,and the results analyzed are satisfactory.

High power generation of adaptive laser beams in a Nd：YVO4 MOPA system

We report efficient power scaling of the laser output with an adaptive bemn profile from an Nd：YAG dual-cavity master oscillator using a three-stage end-pumped Nd：YVO4 amplifier. We succeed ill the last switching of an excited laser mode by modulating an acousto-optic modulator loss in a dual-cavity master oscillator, thereby achieving temporal modulation of the output beam profile. The outputs from the master oscillator are amplified via a three-stage power amplifier yielding 36.6, 40.5, and 45.4 W of the maximum output at 116.8 W of incident pump power for the transverse electromagnetic, Laguerre-Gaussian, and quasi-top-hat beam, respectively. The prospects for further power scaling and applications via the dual-cavity master-oscillator power-amplifier （MOPA） system are considered.

Wireless Transmission Based Image Quality Analysis Using Uni-Level Haar Wavelet Transform

This article deals with picture excellence examination by different parameters utilizing uni-level Haar wavelet transmission in excess of remote channel. The quality is analyzed based on power. The goal is towards reducing absolute power assigned in favour of picture compression and communication, while power in favour of every bit is reserved at prearranged value. Two Power Algorithms were presented. The greatest iterative power control calculation and Minimum Power Adaptation Algorithm (MPAA) are proposed. Those algorithms methodology was utilized for improving the aggregate power dispensed for multimedia such as picture because of input compression and transmission focus towards a settled bit source mutilation. Simulations were performed utilizing Haar wavelet than Additive White Gaussian Ration (AWGN) channel. Different picture excellence parameters, for example, Peak Signal to Noise Ratio (PSNR), M-Normalized Cross-Correla- tion, Average Difference;Structural Content parameters, for example, Maximum Difference, Normalized Absolute Error, Elapsed Time, CPU time, demonstrate a improved presentation with MPAA, Maximum Power Adaptation Algorithms (MAPAA) instead of Conventional Power Adaptation Algorithm (CPAA).

The Detection of Inter-Turn Short Circuits in the Stator Windings of Sensorless Operating Induction Motors

This work proposes an alternative strategy to the use of a speed sensor in the implementation of active and reactive power based model reference adaptive system (PQ-MRAS) estimator in order to calculate the rotor and stator resistances of an induction motor (IM) and the use of these parameters for the detection of inter-turn short circuits (ITSC) faults in the stator of this motor. The rotor and stator resistance estimation part of the IM is performed by the PQ-MRAS method in which the rotor angular velocity is reconstructed from the interconnected high gain observer (IHGO). The ITSC fault detection part is done by the derivation of stator resistance estimated by the PQ-MRAS estimator. In addition to the speed sensorless detection of ITSC faults of the IM, an approach to determine the number of shorted turns based on the difference between the phase current of the healthy and faulty machine is proposed. Simulation results obtained from the MATLAB/Simulink platform have shown that the PQ-MRAS estimator using an interconnected high-gain observer gives very similar results to those using the speed sensor. The estimation errors in the cases of speed variation and load torque are almost identical. Variations in stator and rotor resistances influence the performance of the observer and lead to poor estimation of the rotor resistance. The results of ITSC fault detection using IHGO are very similar to the results in the literature using the same diagnostic approach with a speed sensor.

Decentralized beamforming design and power allocation for limited coordinated multi-cell network

Multi-cell processing （MCP） is capable of providing significant performance gain, but this improvement is accompanied by dramatic signaling overhead between cooperative base stations. Therefore, balancing the performance gain and overhead growth is crucial for a practical multi-base cooperation scheme. In this paper, we propose a decentralized algorithm to jointly optimize the power allocation and beamforming vector with the goal of maximizing the system performance under the constraint of limited overhead signal and backhaul link capacity. In particular, combined with calculating the transmission beamforming vector according to the local channel state information, an adaptive power allocation is presented based on the result of sum capacity estimation. Furthermore, by utilizing the concept of cell clustering, the proposed framework can be implemented in a practical cellular system without major modification of network architecture. Simulation results demonstrate that the proposed scheme improves the system performance in terms of the sum capacity and cell-edge capacity.

Parallel processing architecture of H.264 adaptive deblocking filters

In H.264,computational complexity and memory access of deblocking filters are variable,dependent on video contents.This paper proposes a VLSI architecture of deblocking filters with adaptive dynamic power,which avoids redundant computations and memory accesses by precluding the blocks that can be skipped.The vertical and horizontal edges are simulta-neously processed in an advanced scan order to speed up the decoder.As a result,dynamic power of the proposed architecture can be reduced adaptively(up to about 89%) for different videos,and the off-chip memory access is improved when compared to previous designs.Moreover,the processing capability of the proposed architecture is in particular appropriate for real-time deblocking of high-definition television(HDTV,1920×1080 pixels/frame,60 frames/s video signals) video operation at 62 MHz.Using the proposed architecture,power can be reduced by up to about 89% and processing time by from 25% to 81% compared with previous designs.

Adaptive IF selection and IQ mismatch compensation in a low-IF GSM receiver

This paper presents an algorithm that can adaptively select the intermediate frequency（IF） and compensate the IQ mismatch according to the power ratio of the adjacent channel interference to the desired signal in a low-IF GSM receiver.The IF can be adaptively selected between 100 and 130 kHz.Test result shows an improvement of phase error from 6.78°to 3.23°.Also a least mean squares（LMS） based IQ mismatch compensation algorithm is applied to improve image rejection ratio（IRR） for the desired signal along with strong adjacent channel interference.The IRR is improved from 29.1 to 44.3 dB in measurement.The design is verified in a low-IF GSM receiver fabricated in SMIC 0.13μm RF CMOS process with a working voltage of 1.2 V.

Active,compact,wideband,receiving filtenna with power adaptation for space-limited wireless platforms

An active,compact,wideband,receiving filtenna with power adaptation for space-limited wireless platforms is presented.By organically combining a filtering antenna and a Variable Gain Amplifier(VGA),the proposed co-designed active filtenna is achieved.Its power adaptation is empowered by controlling gain of the VGA unit.A demonstrated prototype with a compact overall size is fabricated,assembled and measured.Good performances are achieved.Furthermore,in any condition,the proposed active filtenna displays outstanding impedance matching(|S_(11)|<−10 dB)and high passband skirt selectivity at upper and lower stopbands(Selectivity≥170 dB/GHz).