scholarly journals Modified Least Squares Algorithm for Three-Dimensional Target Location Based on Wireless Communication Base Stations

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Zhaohui Zhang ◽  
Jing Li ◽  
Qian Liu
Keyword(s):  
Wireless Communication ◽  
Least Squares ◽  
Clustering Algorithm ◽  
Target Location ◽  
Three Dimensional ◽  
Base Station ◽  
Base Stations ◽  
Selection Strategy ◽  
Time Of Arrival ◽  
Radio Signals

The observed values of time of arrival (TOA) for the radio signals between the target and the wireless communication base stations are mainly affected by signal non-line-of-sight (NLOS) propagation in target location. TOA with NLOS makes a lot of signal noises and propagation delays, that is, location errors. For the first time, this paper focuses on the problem of modifying the Z-axis location coordinates in three-dimensional (3D) target location. A novel algorithm is proposed by establishing the modified least squares 3D location model for the accurate target location. Meanwhile, an optimal base station selection strategy is proposed by using the spectral clustering algorithm, which is based on the spatial distribution of the base stations. Compared with the existing algorithms, the proposed algorithm in this paper has better performance on the accurate target 3D location in real scenes, which has a high value of practical application. The simulations illustrate that the location error of the proposed algorithm is smaller than those of other existing algorithms based on the same simulation data and conditions.

scholarly journals Power-Efficient Wireless Coverage Using Minimum Number of UAVs

Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 223
Author(s):  
Ahmad Sawalmeh ◽  
Noor Shamsiah Othman ◽  
Guanxiong Liu ◽  
Abdallah Khreishah ◽  
Ali Alenezi ◽  
...  
Keyword(s):  
Clustering Algorithm ◽  
Circle Packing ◽  
Three Dimensional ◽  
Base Stations ◽  
Transmit Power ◽  
Power Efficient ◽  
User Coverage ◽  
Minimum Number ◽  
Wireless Coverage ◽  
Placement Algorithms

Unmanned aerial vehicles (UAVs) can be deployed as backup aerial base stations due to cellular outage either during or post natural disaster. In this paper, an approach involving multi-UAV three-dimensional (3D) deployment with power-efficient planning was proposed with the objective of minimizing the number of UAVs used to provide wireless coverage to all outdoor and indoor users that minimizes the required UAV transmit power and satisfies users’ required data rate. More specifically, the proposed algorithm iteratively invoked a clustering algorithm and an efficient UAV 3D placement algorithm, which aimed for maximum wireless coverage using the minimum number of UAVs while minimizing the required UAV transmit power. Two scenarios where users are uniformly and non-uniformly distributed were considered. The proposed algorithm that employed a Particle Swarm Optimization (PSO)-based clustering algorithm resulted in a lower number of UAVs needed to serve all users compared with that when a K-means clustering algorithm was employed. Furthermore, the proposed algorithm that iteratively invoked a PSO-based clustering algorithm and PSO-based efficient UAV 3D placement algorithms reduced the execution time by a factor of ≈1/17 and ≈1/79, respectively, compared to that when the Genetic Algorithm (GA)-based and Artificial Bees Colony (ABC)-based efficient UAV 3D placement algorithms were employed. For the uniform distribution scenario, it was observed that the proposed algorithm required six UAVs to ensure 100% user coverage, whilst the benchmarker algorithm that utilized Circle Packing Theory (CPT) required five UAVs but at the expense of 67% of coverage density.

scholarly journals 3D Localization Algorithm Based on Linear Regression and Least Squares in NLOS Environments

2018 ◽  
Vol 11 (4) ◽  
pp. 1
Author(s):  
Jiang Li ◽  
Zhang Lei
Keyword(s):  
Linear Regression ◽  
Three Dimensional ◽  
Least Square Method ◽  
Mobile Terminal ◽  
Base Station ◽  
Least Square ◽  
Time Of Arrival ◽  
Localization Algorithm ◽  
Positional Accuracy ◽  
The Relationship

Based on the positive bias property of the time of arrival(TOA) measurement error caused by the non-line-of-sight(NLOS) propagation, a simple and effective three dimensional(3D) geometrical localization algorithm was proposed, the algorithm needs no prior knowledge of time delay distribution of TOA, and only linear regression was used to estimate the parameters of the relationship between the NLOS distance error and the true distance, thus, the approximate real distance between mobile terminal (MT) and base station (BS) was reduced, then, the 3D geometric localization of mobile terminal was carried out by the least square method. The experimental results shows the effectiveness of the algorithm, and the positional accuracy is far higher than the required accuracy by E-911 in NLOS environments.

scholarly journals Semi-Autonomous Coordinate Configuration Technology of Base Stations in Indoor Positioning System Based on UWB

Electronics ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 33
Author(s):  
Xiaofei Yang ◽  
Jun Wang ◽  
Hui Ye ◽  
Jianzhen Li
Keyword(s):  
Large Scale ◽  
Target Location ◽  
Wide Band ◽  
Indoor Positioning ◽  
Base Station ◽  
Base Stations ◽  
Positioning System ◽  
Linear Network ◽  
Gps System ◽  
Indoor Positioning System

In the global positioning system (GPS) denied environment, an indoor positioning system based on ultra-wide band (UWB) technology has been utilized for target location and navigation. It can provide a more accurate positioning measurement than those based on received signal strength (RSS). Although promising, it suffers from some shortcomings that base stations should be preinstalled to obtain reference coordinate information, just as navigation satellites in the GPS system. In order to improve the positioning accuracy, a large number of base stations should be preinstalled and assigned coordinates in the large-scale network. However, the coordinate setup process of the base stations is cumbersome, time consuming, and laborious. For a class of linear network topology, a semi-autonomous coordinate configuration technology of base stations is designed, which refers to three conceptions of segmentation, virtual triangle, and bidirectional calculation. It consists of two stages in every segment: Forward and backward. In the forward stage, it utilizes the manual coordinate setup method to deal with the foremost two base stations, and then the remaining base stations autonomously calculate their coordinates by building the virtual triangle train. In the backward stage, the reverse operation is performed, but the foremost two base stations of the next segment should be used as the head. In the last segment, the last two base stations should be used as the head. Integrating forward and backward data, the base stations could improve their location accuracy. It is shown that our algorithm is feasible and practical in simulation results and can dramatically reduce the system configuration time. In addition, the error and maximum base station number for one segment caused by our algorithm are discussed theoretically.

scholarly journals Intercell Interference Coordination through Limited Feedback

2010 ◽  
Vol 2010 ◽  
pp. 1-7 ◽  
Author(s):  
Lingjia Liu ◽  
Jianzhong (Charlie) Zhang ◽  
Jae-Chon Yu ◽  
Juho Lee
Keyword(s):  
Wireless Communication ◽  
Communication Networks ◽  
Limited Feedback ◽  
Base Station ◽  
Base Stations ◽  
System Level ◽  
Wireless Communication Networks ◽  
Interference Coordination ◽  
Average Cell ◽  
Intercell Interference

We consider the applications of multicell transmission schemes to the downlink of future wireless communication networks. A multicell multiple-input multiple output-(MIMOs) based scheme with limited coordination among neighboring base stations (BSs) is proposed to effectively combat the intercell interference by taking advantage of the degreesoffreedom in the spatial domain. In this scheme, mobile users are required to feedback channel-related information to both serving base station and interfering base station. Furthermore, a chordal distance-based compression scheme is introduced to reduce the feedback overhead. The performance of the proposed scheme is investigated through theoretical analysis as well as system level simulations. Both results suggest that the so-called “intercell interference coordination through limited feedback” scheme is a very good candidate for improving the cell-edge user throughput as well as the average cell throughput of the future wireless communication networks.

Research and Improvement about LEACH Algorithm for Wireless Sensor Networks

2014 ◽  
Vol 599-601 ◽  
pp. 1954-1959
Author(s):  
Tao Liu ◽  
Sui Min Jia
Keyword(s):  
Clustering Algorithm ◽  
Cluster Head ◽  
Premature Death ◽  
Base Station ◽  
Base Stations ◽  
Wireless Sensor ◽  
Cluster Number ◽  
Local Data ◽  
Distance Threshold ◽  
Energy Distance

In Wireless Sensor Network (WSN), unreasonable node clustering algorithm will inevitably lead to premature death, unawareness of regional information.To address problems of traditional LEACH algorithm, An improved LEACH multi-hop routing algorithm based on Energy Distance Threshold (EDT) is presented. It mainly improves from aspects of cluster number, cluster head selection and inter-cluster communication. The improved clustering hierarchy algorithm considers the nodes Energy Distance Threshold as an important factor in selection then chooses the best cluster head within the area. The selection of cluster head is based on re-select manner, which dynamically and effectively select cluster heads by control cluster number and combing with EDT. After cluster head completes local data fusion and processing, it look for adjacent cluster head as next hop closer to base station with larger EDT if the head is far away from station. The next hop repeats above process till the base station is arrived. Such manner of multi-hop among clusters enables communication among clusters and base stations so as to avoid direct communication between head and station. The method reduces energy consumption and also balances energy. Simulation results show the improved LEACH algorithm has higher energy utilizing rate, and it helps prolong network’s lifetime.

scholarly journals A Synthesizable VHDL Model of the Exact Solution for Three-dimensional Hyperbolic Positioning System

VLSI Design ◽  
2002 ◽  
Vol 15 (2) ◽  
pp. 507-520 ◽  
Author(s):  
Ralph Bucher ◽  
D. Misra
Keyword(s):  
Exact Solution ◽  
Three Dimensional ◽  
Base Station ◽  
Time Of Arrival ◽  
Positioning System ◽  
Worst Case ◽  
Accuracy And Precision ◽  
A Cell ◽  
Bit Vector ◽  
Hyperbolic Positioning

This paper presents a synthesizable VHDL model of a three-dimensional hyperbolic positioning system algorithm. The algorithm obtains an exact solution for the three-dimensional location of a mobile given the locations of four fixed stations (like a global positioning system [GPS] satellite or a base station in a cell) and the signal time of arrival (TOA) from the mobile to each station. The detailed derivation of the steps required in the algorithm is presented. A VHDL model of the algorithm was implemented and simulated using the IEEE numeric_std package. Signals were described by a 32-bit vector. Simulation results predict location of the mobile is off by 1 m for best case and off by 36 m for worst case. A C + + program using real numbers was used as a benchmark for the accuracy and precision of the VHDL model. The model can be easily synthesized for low power hardware implementation.

scholarly journals Predictive Wireless Channel Modeling of MmWave Bands Using Machine Learning

Electronics ◽  
2021 ◽  
Vol 10 (24) ◽  
pp. 3114
Author(s):  
Abdallah Mobark Aldosary ◽  
Saud Alhajaj Aldossari ◽  
Kwang-Cheng Chen ◽  
Ehab Mahmoud Mohamed ◽  
Ahmed Al-Saman
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Wireless Communication ◽  
Random Forests ◽  
Communication Systems ◽  
Channel Modeling ◽  
Base Station ◽  
Wireless Channel ◽  
Base Stations ◽  
Data Driven

The exploitation of higher millimeter wave (MmWave) is promising for wireless communication systems. The goals of machine learning (ML) and its subcategories of deep learning beyond 5G (B5G) is to learn from the data and make a prediction or a decision other than relying on the classical procedures to enhance the wireless design. The new wireless generation should be proactive and predictive to avoid the previous drawbacks in the existing wireless generations to meet the 5G target services pillars. One of the aspects of Ultra-Reliable Low Latency Communications (URLLC) is moving the data processing tasks to the cellular base stations. With the rapid usage of wireless communications devices, base stations are required to execute and make decisions to ensure communication reliability. In this paper, an efficient new methodology using ML is applied to assist base stations in predicting the frequency bands and the path loss based on a data-driven approach. The ML algorithms that are used and compared are Multilelayers Perceptrons (MLP) as a neural networks branch and Random Forests. Systems that consume different bands such as base stations in telecommunications with uplink and downlink transmissions and other internet of things (IoT) devices need an urgent response between devices to alter bands to maintain the requirements of the new radios (NR). Thus, ML techniques are needed to learn and assist a base station to fluctuate between different bands based on a data-driven system. Then, to testify the proposed idea, we compare the analysis with other deep learning methods. Furthermore, to validate the proposed models, we applied these techniques to different case studies to ensure the success of the proposed works. To enhance the accuracy of supervised data learning, we modified the random forests by combining an unsupervised algorithm to the learning process. Eventually, the superiority of ML towards wireless communication demonstrated great accuracy at 90.24%.

Research on Resource Allocation based on Clustering in Femtocell Networks

2017 ◽  
Vol 7 (1) ◽  
pp. 138
Author(s):  
Ding Kai ◽  
Liu Zhanjun ◽  
Zhou Shiyan ◽  
Ran Weiyi ◽  
Li Wei
Keyword(s):  
Resource Allocation ◽  
Clustering Algorithm ◽  
Average Rate ◽  
Fitness Function ◽  
Base Station ◽  
Base Stations ◽  
Conflict Graph ◽  
Search Range ◽  
Femtocell Networks ◽  
Resource Allocation Algorithm

<p>Aiming at the problem that existing femtocell base station searching the optimal clustering scheme based on the clustering resource allocation algorithm is complex. we propose that building an conflict graph and adjacency matrix before clustering to calculate the number of clusters needed for FBS group by using the adaptive clustering heuristic algorithm. We follow maximization the sum of the FBS distances in the cluster and group the femtocell base stations to narrow the search range to reduce the computational complexity. In order to achieve different business types service, based on the above clustering algorithm, this paper proposes a new method that using the weighted energy efficiency, which including the user interruption and the network spectral efficiency as a fitness function of the power control scheme to solve the problem. The simulation results show that the same rate requirement reduces the complexity, while the same complexity increases the user's average rate.</p>

scholarly journals Improved 3-D Indoor Positioning Based on Particle Swarm Optimization and the Chan Method

Information ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 208
Author(s):  
Shanshan Chen ◽  
Zhicai Shi ◽  
Fei Wu ◽  
Changzhi Wang ◽  
Jin Liu ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Computational Complexity ◽  
Large Scale ◽  
Particle Swarm ◽  
Base Station ◽  
Base Stations ◽  
Time Of Arrival ◽  
Swarm Optimization ◽  
Positioning Accuracy ◽  
Initial Location

Time of arrival (TOA) measurement is a promising method for target positioning based on a set of nodes with known positions, with high accuracy and low computational complexity. However, most positioning methods based on TOA (such as least squares estimation, maximum-likelihood, and Chan, etc.) cannot provide desirable accuracy while maintaining high computational efficiency in the case of a non-line of sight (NLOS) path between base stations and user terminals. Therefore, in this paper, we proposed a creative 3-D positioning system based on particle swarm optimization (PSO) and an improved Chan algorithm to greatly improve the positioning accuracy while decreasing the computation time. In the system, PSO is used to estimate the initial location of the target, which can effectively eliminate the NLOS error. Based on the initial location, the improved Chan algorithm performs iterative computations quickly to obtain the final exact location of the target. In addition, the proposed methods will have computational benefits in dealing with the large-scale base station positioning problems while has highly positioning accuracy and lower computational complexity. The experimental results demonstrated that our algorithm has the best time efficiency and good practicability among stat-of-the-art algorithms.

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