Optimal Power Allocation Research Articles

GWO-Based Power Allocation Optimization Algorithm for Consumer IoT Networks

GWO-Based Power Allocation Optimization Algorithm for Consumer IoT Networks

Research on Energy Management Strategy for Extended‐Range Electric Vehicle Based on Bargaining Game

To improve the fuel economy and battery life of extended‐range electric vehicles (EREVs), an energy management strategy (EMS) based on the bargaining game (BG) is proposed. This strategy optimizes the overall economy by optimizing power allocation. First, a bargaining model for EREVs is developed. The model considers the auxiliary power unit (APU) and the battery as two parties of the game. The power allocation between the APU and the battery optimizes both the fuel consumption and the battery life. And it also improves the overall benefit of the vehicle. Second, the effect of the discount factor on the control results is analyzed to obtain the best optimization results. Finally, compared to the thermostat strategy and the dynamic programming‐based strategy, the proposed BG‐based strategy reduces fuel consumption by 27.6% and 1.4% under the World Light Vehicle Test Procedure and reduces the effective ampere‐hour fluxes by 62.7% and 14.6%. Under the China Light‐duty Vehicle Test Cycle, it reduces fuel consumption by 32.5% and 0.5% and reduces the effective ampere‐hour fluxes by 56.8% and 27.5%. The simulation results manifest the excellent performance of the proposed BG‐based EMS.

Full‐duplex jamming for physical layer security improvement in NOMA‐enabled overlay cognitive radio networks

AbstractIn this paper, we analyze the physical layer security (PLS) performance of nonorthogonal multiple access (NOMA)‐enabled overlay cognitive radio networks (NOMA‐OCRNs) in the presence of an external passive eavesdropper. Here PLS is expressed in terms of the secrecy outage probabilities (SOPs) experienced by the primary user (PU) and secondary user (SU). We obtain approximate expressions for the SOPs of both PU as well as SU assuming a jamming‐free environment, where both primary and secondary destination nodes are half‐duplex devices. To improve the SOP performance, we propose a jamming‐assisted framework, where full‐duplex destination nodes are employed, which are capable of transmitting jamming signals to confound the eavesdropper. Approximate expressions for the SOPs of PU and SU are derived for the jamming‐assisted framework as well. It is demonstrated that the proposed jamming‐assisted framework significantly reduces the SOPs compared to the jamming‐free scenario. We also determine optimal power allocation coefficients (OPACs) for PU and SU at the secondary transmitter that maximizes the total secrecy throughput of the jamming‐assisted NOMA‐OCRN with FD destinations. It is shown that the suggested OPAC significantly enhances the total secrecy throughput, compared to the default selection of the PAC.

A cognitive spectrum allocation scheme for data transmission in smart distribution grids

As the communication needs in the smart distribution grid continue to rise, using existing resources to meet this growing demand poses a significant challenge. This paper researches on spectrum allocation strategies utilizing cognitive radio (CR) technology. We consider a model containing strong time-sensitive and regular communication service requirements such as distribution terminal communication services, which can be seen as a user with primary data (PD) and weak time-sensitive services such as power quality monitoring, which can be seen as a user with secondary data (SD). To fit the diversity of services in smart distribution grids (SDGs), we formulate an optimization problem with two indicators, including the sum of SD transmission rates and the maximum latency of them. Then, we analyze the two convex sub-problems and utilize convex optimization methods to obtain the optimal power and frequency bandwidth allocation for the users with SD. The simulation results indicate that, when the available transmission power of SD is low, Maximization of Transmission Sum Rate (MTSR) achieves lower maximum transmit time. Conversely, when the available transmission power is high, the performance of Minimization of the Maximum Latency (MML) is better, compared with MTSR.

Secure User Pairing and Power Allocation for Downlink Non-Orthogonal Multiple Access against External Eavesdropping.

We propose a secure user pairing (UP) and power allocation (PA) strategy for a downlink Non-Orthogonal Multiple Access (NOMA) system when there exists an external eavesdropper. The secure transmission of data through the downlink is constructed to optimize both UP and PA. This optimization aims to maximize the achievable sum secrecy rate (ASSR) while adhering to a limit on the rate for each user. However, this poses a challenge as it involves a mixed integer nonlinear programming (MINLP) problem, which cannot be efficiently solved through direct search methods due to its complexity. To handle this gracefully, we first divide the original problem into two smaller issues, i.e., an optimal PA problem for two paired users and an optimal UP problem. Next, we obtain the closed-form optimal solution for PA between two users and UP in a simplified NOMA system involving four users. Finally, the result is extended to a general 2K-user NOMA system. The proposed UP and PA method satisfies the minimum rate constraints with an optimal ASSR as shown theoretically and as validated by numerical simulations. According to the results, the proposed method outperforms random UP and that in a standard OMA system in terms of the ASSR and the average ASSR. It is also interesting to find that increasing the number of user pairs will bring more performance gain in terms of the average ASSR.

Reactive Power Demand Estimation and Dynamic Reactive Power Optimal Allocation for HVDC Receiving Network

The transient voltage stability of the receiver system is severely challenged by the AC-DC interaction and the short electrical distance between individual DC drop points of the receiver network. Firstly, the dynamic reactive power of DC receiver system is analyzed in this paper. The analysis of the dynamic reactive power in the DC receiver system is presented in this paper. In addition, the evaluation method for the reactive power necessary to sustain the voltage of the converter bus AC system is proposed, taking into consideration the voltage drop mechanism when a DC block occurs. Finally, a mechanism for the reactive power dynamic optimization of the AC-DC receiving power network is proposed based on the sensitivity of the transient voltage track index. The optimal access node is determined by quantitatively evaluating the bus transient voltage increase of the inverter station when each node is connected to the dynamic compensation device of reactive power, and the simulation calculation is carried out by the actual power network to validate the performance of the methodology.

Enhancement of Eurasian Oystercatcher Optimizer for Spectral Efficiency Maximization in Massive MIMO Systems through Optimal Power Allocation

Enhancement of Eurasian Oystercatcher Optimizer for Spectral Efficiency Maximization in Massive MIMO Systems through Optimal Power Allocation

Balancing Total Energy Consumption and Mean Makespan in Data Offloading for Space-Air-Ground Integrated Networks

We study the data offloading problem in space-air-ground integrated networks (SAGINs) by jointly optimizing task scheduling and power control to balance the total energy consumption and mean makespan. We consider a mixed integer nonlinear programming problem to minimize a normalized weighted combination of these two conflicting objectives. We first propose an approximation algorithm to find a high-quality solution, which is shown to be at most <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\frac{1}{2}$</tex-math></inline-formula> from the optimum to this problem for given power allocation. We further show that optimal power allocation can be obtained in closed form under the assumption that satellite-ground links have low signal-to-noise ratio (SNR). Thus, the proposed approximation algorithm can be directly utilized to obtain a constant-factor solution to the studied problem in low-SNR scenarios. To extend our solution to more general scenarios, we further propose an efficient hybird algorithm based on a genetic framework. Our simulation results demonstrate the near-optimality and correctness of the proposed algorithms, and they unveil the interplay between total energy consumption and mean makespan in SAGINs as well.

Reconfigurable Intelligent Surfaces-Aided Relaying in Correlated Rice Fading: Performance Analysis and Design Optimization

In this paper, we investigate the spatial correlation for a practical RIS-assisted communication system operating over Rician fading. Specifically, we derive a unified analytical framework for computing the outage probability and the achiev- able diversity order for arbitrary number of reflecting elements and over arbitrarily correlated Rice fading. We also investigate the impact of spatial correlation on a hybrid architecture that amalgamates both a practical RIS and a decode and forward relay. We then attain closed-form expressions for the outage probability and show that the activation of the relay boosts the outage performance by providing and additional diversity path. The tractable results empower the asymptotic outage analyses, which are conducted not only to reveal helpful insights into understanding the impact of spatial correlation, but also enable optimal power allocation strategies to enhance the system perfor- mance under both transmission modes. Numerical results validate the tightness and effectiveness of the closed-form expressions. In particular, the harmfulness of spatial correlation and the benefit of line-of-sight links are revealed and optimal power allocation is shown to yield impressive coding gains over equal power allocation.

Enhancement of Eurasian oystercatcher optimiser for spectral efficiency maximisation in massive MIMO systems through optimal power allocation

Enhancement of Eurasian oystercatcher optimiser for spectral efficiency maximisation in massive MIMO systems through optimal power allocation

Optimization of Access Points and Power Allocation for Indoor Multi-Input and Multi-Output Visible Light Communication Systems

Optimization of Access Points and Power Allocation for Indoor Multi-Input and Multi-Output Visible Light Communication Systems

An Iterative-Based Optimum Power and Resource Allocation in Application-Dependent Scenarios for One-to-One D2D Communication

An Iterative-Based Optimum Power and Resource Allocation in Application-Dependent Scenarios for One-to-One D2D Communication

Machine Learning Assisted Cross-Layer Joint Optimal Subcarrier and Power Allocation for Device-to-Device Video Transmission

Machine Learning Assisted Cross-Layer Joint Optimal Subcarrier and Power Allocation for Device-to-Device Video Transmission

Optimal Power and Resource Allocation For 5G Oriented system using a Hybridized Whale and Hosted Cuckoo (Hyb-WHC) Optimization Algorithm

Optimal Power and Resource Allocation For 5G Oriented system using a Hybridized Whale and Hosted Cuckoo (Hyb-WHC) Optimization Algorithm

RAT-Mania: Advancing Multi-RAT Networks With Optimal Beamforming, Slot, and Power Allocation, Through Optimization, Heuristics, and Learning

RAT-Mania: Advancing Multi-RAT Networks With Optimal Beamforming, Slot, and Power Allocation, Through Optimization, Heuristics, and Learning

Three-Level Optimal Scheduling and Power Allocation Strategy for Power System Containing Wind-Storage Combined Unit

Three-Level Optimal Scheduling and Power Allocation Strategy for Power System Containing Wind-Storage Combined Unit

Optimal Transmit Antenna Deployment and Power Allocation for Wireless Power Supply in an Indoor Space

Optimal Transmit Antenna Deployment and Power Allocation for Wireless Power Supply in an Indoor Space

Joint Design of Antenna Selection and Resource Allocation in Massive MIMO‐Based Ultra Dense Heterogeneous Networks

Fifth generation (5G) communication network is anticipated to satisfy the need for higher data rates, less latency, ubiquitous connectivity with minimum consumption of energy and acceptable quality of Service (QoS). The massive MIMO and heterogeneous network (HetNet) has evolved as a promising technology to address the aforementioned challenges. In the proposed framework, the massive MIMO technology at the macro base station and full duplex (FD) technology enabled at the small cell base station in HetNet are investigated. An optimal antenna selection strategy, user association (UA), and power allocation (PA) in a massive MIMO‐based HetNet with FD‐enabled small cells are proposed to optimize system sum rate. Initially, the objective function of the optimization problem is nonconvex and a mixed integer nonlinear programming problem. Then, the solution is obtained by transforming the problem into convex problem utilizing Lagrangian decomposition. Simulation results manifest the effect of the number of base station antennas, number of small cell base stations, self‐interference cancellation factor, and channel state information on system sum rate. Moreover, it is evident that the propounded algorithm is effective in terms of optimizing the system sum rate when compared to the conventional maximum signal‐ to ‐ interference ‐ plus ‐noise ‐ ratio (SINR) algorithm.

Pareto Optimal Energy Efficiency Power Allocation: Coping With Highly Constraints in NOMA Uplink Dense Access VLC Network

Pareto Optimal Energy Efficiency Power Allocation: Coping With Highly Constraints in NOMA Uplink Dense Access VLC Network

Optimum Power Allocation for HARQ-Aided NOMA With Proportional Fairness on Fading Channels

Optimum Power Allocation for HARQ-Aided NOMA With Proportional Fairness on Fading Channels