scholarly journals On the Performance of the Multiple Active Antenna Spatial Modulation with 3-Dimensional Constellation

2020 ◽  
Vol 10 (11) ◽  
pp. 3718 ◽  
Author(s):  
Sheriff Murtala ◽  
Tasnim Holoubi ◽  
Nishal Muchena ◽  
Manar Mohaisen ◽  
Kang-Sun Choi
Keyword(s):  
Spectral Efficiency ◽  
Error Probability ◽  
Optimization Problem ◽  
Spatial Modulation ◽  
Active Antenna ◽  
Multi Objective Optimization ◽  
3 Dimensional ◽  
Active Antennas ◽  
Optimal Rotation ◽  
Simulation Results

In spatial modulation (SM), a single signal symbol is transmitted from a given physical antenna, where both the signal symbol and the antenna index carry information. SM with multiple active antennas (MA-SM) transmits several signal symbols from a combination of antennas at each channel use, thereby increasing the spectral efficiency. MA-SM is proposed in combination with a new 3-dimensional constellation, where signal symbols transmitted from a given antenna combination are rotated before transmission. In this paper, we derived an upper-bound on the error probability of the MA-SM as a function of the rotation angles. The search for the optimal rotation angles is modeled as a multi-objective optimization problem. We concluded based on both analytical and simulation results that the 3-dimensional constellation with the optimal angles achieved negligible improvement. Therefore, we do not recommend using the 3-dimensional constellation with the MA-SM system.

scholarly journals Max–Min Fairness Optimization for D2D Communications Coexisting with Cellular Networks

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1422
Author(s):  
Hoai Giang Nguyen ◽  
Xuan Tung Nguyen ◽  
Van Son Nguyen ◽  
Trinh Van Chien ◽  
Tien Hoa Nguyen ◽  
...  
Keyword(s):  
Spectral Efficiency ◽  
Multiple Access ◽  
Optimization Problem ◽  
Mutual Interference ◽  
D2d Communications ◽  
Power Budget ◽  
Good Service ◽  
Coverage Area ◽  
Channel Condition ◽  
Simulation Results

This paper considers a system consisting of a nonorthogonal multiple access (NOMA)-based device-to-device (D2D) communication system within a cellular network, in which the time and frequency resources are shared by everyone. In particular, D2D groups that constitute different pairs are assigned to the subchannels that the cellular users occupy. A max–min fairness optimization problem with power budget constraints is formulated and solved in this paper to reduce the mutual interference between the cellular users and D2D devices that substantially impacts that with the worst channel condition. For a low computational complexity solution, we propose the use of the bisection method together with the solution of a system of linear equalities. The proposed algorithm can provide uniformly good service to all of the cellular users and D2D devices in the coverage area by utilizing the minimal total transmit power. The simulation results indicate the effectiveness of the proposed algorithm in the improvement of the spectral efficiency of the worst user under the different widely used subchannel assignments and pairing techniques.

Modified Multiobjective Dynamic Multi-Swarm Particle Swarm Optimization for Mineral Grinding Process

2014 ◽  
Vol 971-973 ◽  
pp. 1242-1246
Author(s):  
Tie Jun Chen ◽  
Yan Ling Zheng
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Problem ◽  
Pareto Frontier ◽  
Particle Swarm ◽  
Similarity Criterion ◽  
Grinding Process ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Multi Objective ◽  
Simulation Results

The mineral grinding process is a typical constrained multi-objective optimization problem for its two main goals are quality and quantity. This paper established a similarity criterion mathematical model and combined Multi-objective Dynamic Multi-Swarm Particle Swarm Optimization with modified feasibility rule to optimize the two goals. The simulation results showed that the results of high quality were achieved and the Pareto frontier was evenly distributed and the proposed approach is efficient to solve the multi-objective problem for the mineral grinding process.

scholarly journals Exploring Innovative Design Principles using Innovization in Multi- Objective Optimal Reactive Power Dispatch Problem

2019 ◽  
Vol 9 (1) ◽  
pp. 2711-2719
Keyword(s):  
Optimization Problem ◽  
Reactive Power ◽  
Design Principles ◽  
Multi Objective Optimization ◽  
Innovative Design ◽  
Multi Objective ◽  
Optimal Reactive Power Dispatch ◽  
Decision Variables ◽  
Reactive Power Dispatch ◽  
Simulation Results

Recently, researchers in the field of Evolutionary Multi-Objective Optimization give a systematic approach for exploring innovative design principles in a conflicting multi-objective optimization problem by analyzing pareto optimal solution using either manual or automated approach. They call it “Innovization” and defined as: “innovation through optimization”. This paper applies manual innovization to multi-objective Optimal Reactive Power Dispatch Problem using Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) as multi-objective optimization algorithm and manually searches for all possible innovative design principles by analyzing multiple pareto optimal solutions. Standard IEEE 30 bus test system is considered for the current work. Simulation results reveal number of innovative design principles. Innovative design principles includes function approximation of relationship between conflicting objectives, characteristics of decision variable with respect to different objectives and actual range of decision variables. Simulation results clearly show much faster convergence when decision variables were obtained using innovative design principles for specified desired objectives as compared to normal case. Results also show some decision variables can be eliminated by setting it to a fixed value, which leads to simplification of optimization problem as the values of these variables remains constant with respect to the values of objective function.

Study on Coordinated Control of Multi-Distribution Static Var Compensator

2014 ◽  
Vol 672-674 ◽  
pp. 1127-1131
Author(s):  
Ming Jiang Zhang ◽  
Xi Lin Zhang ◽  
Zhen Hao Wang ◽  
Ling Wang
Keyword(s):  
Genetic Algorithm ◽  
Power Quality ◽  
Distribution System ◽  
Optimization Problem ◽  
Coordinated Control ◽  
Parameters Optimization ◽  
Static Var Compensator ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Simulation Results

DFACTS devices can synthetically manage power quality problems. As one of the most DFACTS devices, the coordinated control of multi-distribution static var compensator should be considered. Controllers are separately designed aiming at different functions, that means the controllers are isolated even contradictory. In allusion to the problem that the separately designed DFACTS controllers exist interactions, the paper turns the coordination of the DFACTS controller into multi-objective optimization problem, takes the single-load infinite-bus distribution system with two DSVC as the research object, using the Non-dominated Sorting Genetic Algorithm with elitism approach (NSGA-II) for DFACTS controller parameters optimization, and the simulation results show the effectiveness of the algorithm.

Parameter matching and optimization for power system of range-extended electric vehicle based on requirements

2020 ◽  
Vol 234 (14) ◽  
pp. 3316-3328
Author(s):  
Hanwu Liu ◽  
Yulong Lei ◽  
Yao Fu ◽  
Xingzhong Li
Keyword(s):  
Electric Vehicle ◽  
Performance Indicators ◽  
Optimization Problem ◽  
Transmission System ◽  
Multi Objective Optimization ◽  
Characteristic Parameters ◽  
Swarm Optimization ◽  
Vehicle Performance ◽  
Parameter Matching ◽  
Simulation Results

For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.

Active exploration using a scheme for autonomous allocation of landmarks

Robotica ◽  
2013 ◽  
Vol 32 (5) ◽  
pp. 757-782 ◽  
Author(s):  
Jing Yuan ◽  
Yalou Huang ◽  
Fengchi Sun ◽  
Tong Tao
Keyword(s):  
Optimization Problem ◽  
Polar Regions ◽  
Multi Objective Optimization ◽  
Heuristic Rules ◽  
Redundancy Elimination ◽  
Accurate Localization ◽  
Localization And Mapping ◽  
On Line ◽  
Simulation Results ◽  
Active Exploration

SUMMARYIn this paper, we focus on the unknown environments without artificial landmarks and features, such as disaster situations and polar regions. An approach to active exploration based on an on-line scheme for autonomous allocation of landmarks is proposed. Specifically, the robot carries along with itself some landmarks which are to be allocated during the exploration according to some heuristic rules. The utility of landmark allocation is analyzed and calculated. Then the active exploration is converted into a problem of multi-objective optimization. The objective function includes three weighted terms: the accuracy of localization and mapping, the coverage rate of the unknown environment and the utility of the allocated landmarks. By solving this optimization problem, control inputs of the robot are computed to guarantee that accurate localization, high-quality mapping and complete exploration can be achieved simultaneously. Moreover, supplementation and redundancy elimination of the allocated landmarks are executed to make a complete and non-redundant coverage for the environment. Finally, some landmarks, together with a device for allocating these landmarks, are developed. Both experiment and simulation results are presented to demonstrate the effectiveness of the proposed approach.

Environmental Economic Dispatch Considering Valve Point Effects

2014 ◽  
Vol 513-517 ◽  
pp. 2902-2905
Author(s):  
Gui Li Yuan ◽  
Tong Yu ◽  
Juan Du
Keyword(s):  
Decision Making ◽  
Environmental Economic ◽  
Optimization Problem ◽  
Ideal Point ◽  
Decision Making Process ◽  
Multi Objective Optimization ◽  
Fuel Cost ◽  
Adaptive Immune ◽  
Dynamic Transformation ◽  
Simulation Results

Based on ideal point principle, an economic/environmental dispatch model considering valve point effects was constructed. The model combined optimization and decision-making process of multi-objective optimization problem and its dynamic transformation can be achieved simply by changing the weights of each of the target model. The adaptive immune vaccine algorithm was applied to optimizing the model. Meanwhile, the target expected completion rate was brought up to measure the completion degree of the environmental and economic indicators. The simulation results showed that the method proposed can reduce the pollution of the environment effectively with low fuel cost.

Trade- off Energy and Spectral Efficiency With Multi-Objective Optimization Problem in 5G Massive MIMO System

2021 ◽  
Author(s):  
Adeb Salh ◽  
Lukman Audah ◽  
Qazwan Abdullah ◽  
Norsaliza Abdullah ◽  
Nor Shahida Mohd Shah ◽  
...  
Keyword(s):  
Spectral Efficiency ◽  
Massive Mimo ◽  
Optimization Problem ◽  
Mimo System ◽  
Multi Objective Optimization ◽  
Trade Off ◽  
Multi Objective

scholarly journals Improving Spectral Efficiency in the SCMA Uplink Channel

Mathematics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 651
Author(s):  
Sergio Vidal-Beltrán ◽  
José Luis López-Bonilla
Keyword(s):  
Mobile Communications ◽  
Antenna Arrays ◽  
Spectral Efficiency ◽  
Communication Systems ◽  
Multiple Access ◽  
Machine Intelligence ◽  
Spatial Modulation ◽  
International Telecommunication Union ◽  
Technical Requirements ◽  
Simulation Results

The Third Generation Partnership Project (3GPP) and the International Telecommunication Union (ITU) identified the technical requirements that the fifth generation of mobile communications networks (5G) had to meet; within these parameters are the following: an improved data rate and a greater number of users connected simultaneously. 5G uses non-orthogonal multiple access (NOMA) to increase the number of simultaneously connected users, and by encoding data it is possible to increase the spectral efficiency (SE). In this work, eight codewords are used to transmit three bits simultaneously using Sparse Code Multiple Access (SCMA), and through singular value decomposition (SVD) the Euclidean distance between constellation points is optimized. On the other hand, applications of machine intelligence and machine intelligence in 5G and beyond communication systems are still developing; in this sense, in this work we propose to use machine learning for detecting and decoding the SCMA codewords using neural networks. This paper focuses on the Use Case of enhanced mobile broadband (eMBB), where higher data rates are required, with a large number of users connected and low mobility. The simulation results show that it is possible to transmit three bits simultaneously with a low bit error rate (BER) using SVD-SCMA in the uplink channel. Our simulation results were compared against recent methods that use spatial modulation (SM) and antenna arrays in order to increase spectral efficiency. In adverse Signal-to-Noise Ratio (SNR), our proposal performs better than SM, and antenna arrays are not needed for transmission or reception.

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

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