scholarly journals Three-dimensional aerial base station location for sudden traffic with deep reinforcement learning in 5G mmWave networks

2020 ◽  
Vol 16 (5) ◽  
pp. 155014772092637
Author(s):  
Peng Yu ◽  
Jianli Guo ◽  
Yonghua Huo ◽  
Xiujuan Shi ◽  
Jiahui Wu ◽  
...  
Keyword(s):  
Spectral Efficiency ◽  
Optimization Model ◽  
Large Scale ◽  
Learning Experience ◽  
Three Dimensional ◽  
Base Station ◽  
Base Stations ◽  
Line Of Sight ◽  
Network Access ◽  
Training Process

Data volume demand has increased dramatically due to huge user device increasement along with the development of cellular networks. And macrocell in 5G networks may encounter sudden traffic due to dense users caused by sports or celebration activities. To resolve such temporal hotspot, additional network access point has become a new solution for it, and unmanned aerial vehicle equipped with base stations is taken as an effective solution for coverage and capacity improvement. How to plan the best three-dimensional location of the aerial base station according to the users’ business needs and service scenarios is a key issue to be solved. In this article, first, aiming at maximizing the spectral efficiency and considering the effects of line-of-sight and non-line-of-sight path loss for 5G mmWave networks, a mathematical optimization model for the location planning of the aerial base station is proposed. For this model, the model definition and training process of deep Q-learning are constructed, and through the large-scale pre-learning experience of different user layouts in the training process to gain experience, finally improve the timeliness of the training process. Through the simulation results, it points out that the optimization model can achieve more than 90% of the theoretical maximum spectral efficiency with acceptable service quality.

Spectral Efficiency Self-Optimization through Dynamic User Clustering and Beam Steering

2016 ◽  
pp. 137-155
Author(s):  
Md Salik Parwez ◽  
Hasan Farooq ◽  
Ali Imran ◽  
Hazem Refai
Keyword(s):  
Spectral Efficiency ◽  
Large Scale ◽  
Optimization Problem ◽  
Focal Point ◽  
Beam Steering ◽  
Clustering Algorithms ◽  
Performance Comparison ◽  
Base Stations ◽  
User Clustering ◽  
A Cell

This paper presents a novel scheme for spectral efficiency (SE) optimization through clustering of users. By clustering users with respect to their geographical concentration we propose a solution for dynamic steering of antenna beam, i.e., antenna azimuth and tilt optimization with respect to the most focal point in a cell that would maximize overall SE in the system. The proposed framework thus introduces the notion of elastic cells that can be potential component of 5G networks. The proposed scheme decomposes large-scale system-wide optimization problem into small-scale local sub-problems and thus provides a low complexity solution for dynamic system wide optimization. Every sub-problem involves clustering of users to determine focal point of the cell for given user distribution in time and space, and determining new values of azimuth and tilt that would optimize the overall system SE performance. To this end, we propose three user clustering algorithms to transform a given user distribution into the focal points that can be used in optimization; the first is based on received signal to interference ratio (SIR) at the user; the second is based on received signal level (RSL) at the user; the third and final one is based on relative distances of users from the base stations. We also formulate and solve an optimization problem to determine optimal radii of clusters. The performances of proposed algorithms are evaluated through system level simulations. Performance comparison against benchmark where no elastic cell deployed, shows that a gain in spectral efficiency of up to 25% is possible depending upon user distribution in a cell.

scholarly journals Joint Trajectory and Scheduling Optimization for The Mobile UAV Aerial Base Station: A Fairness Version

2019 ◽  
Vol 9 (15) ◽  
pp. 3101
Author(s):  
Yancheng Chen ◽  
Ning Li ◽  
Xijian Zhong ◽  
Wei Xie
Keyword(s):  
Ant Colony Algorithm ◽  
Network Capacity ◽  
Base Station ◽  
Base Stations ◽  
Line Of Sight ◽  
Optimization Approach ◽  
Coupling Relationship ◽  
High Flexibility ◽  
Intractable Problem ◽  
Relationship Of

Recently, unmanned aerial vehicles (UAVs) have been widely studied in the communication area to work as aerial base stations, due to the high probability of line of sight (LoS) and high flexibility. However, few works consider fairness for the users, which is one of the most important metrics for a network. In this paper, in order to maximize network capacity with the consideration of fairness, trajectory and scheduling of the mobile UAV aerial base station are jointly optimized. Firstly, the problem of maximizing network capacity with the consideration of fairness is formulated. On account of the coupling relationship of trajectory and scheduling, an alternate iteration approach that contains ant colony algorithm and genetic algorithm are then proposed to solve this intractable problem. Finally, the simulation results demonstrate the fairness enhance of the network and the validity and effectiveness of the proposed optimization approach.

scholarly journals Enhanced Transmit-Antenna Selection Schemes for Multiuser Massive MIMO Systems

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Byung-Jin Lee ◽  
Sang-Lim Ju ◽  
Nam-il Kim ◽  
Kyung-Seok Kim
Keyword(s):  
Computational Complexity ◽  
Radio Frequency ◽  
Spectral Efficiency ◽  
Massive Mimo ◽  
Mimo Systems ◽  
Antenna Selection ◽  
Base Station ◽  
Base Stations ◽  
Transmit Antenna Selection ◽  
Selection Scheme

Massive multiple-input multiple-output (MIMO) systems are a core technology designed to achieve the performance objectives defined for 5G wireless communications. They achieve high spectral efficiency, reliability, and diversity gain. However, the many radio frequency chains required in base stations equipped with a high number of transmit antennas imply high hardware costs and computational complexity. Therefore, in this paper, we investigate the use of a transmit-antenna selection scheme, with which the number of required radio frequency chains in the base station can be reduced. This paper proposes two efficient transmit-antenna selection (TAS) schemes designed to consider a trade-off between performance and computational complexity in massive MIMO systems. The spectral efficiency and computational complexity of the proposed schemes are analyzed and compared with existing TAS schemes, showing that the proposed algorithms increase the TAS performance and can be used in practical systems. Additionally, the obtained results enable a better understanding of how TAS affects massive MIMO systems.

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 Green Base Station using WSN

2019 ◽  
Vol 9 (2) ◽  
pp. 3660-3665
Keyword(s):  
Large Scale ◽  
Power Saving ◽  
Mobile Network ◽  
Base Station ◽  
Base Stations ◽  
Diesel Generator ◽  
Successful Operation ◽  
Night Time ◽  
Communication Services ◽  
Reduction Of Co2

Since the number of mobile users has been increased, there comes a number of new mobile operators. This accounts for the increased installation of towers. A critical mobile network consume 40-50MW (approx.) and a diesel generator consume 1MG (approx.) of diesel per day. Also a base station requires greater amount of power employed for its working in which some of its internal applications like light, coolant systems say air conditioning, fans etc., uses the major part of the power utilized. This intensifies the burning of coal which emits carbon dioxide into the atmosphere. At times the number of users for a base station may be very less especially during night time, consuming the power unnecessarily. Our approach is to reduce the intake of power by the base stations during unwanted time. This can be done by establishing communication between the adjacent towers to intimate the unused tower to remain idle or active based on the requirement. Also this approach conveys the measures taken to reduce the power consumed by the internal applications of the base station. The entire setup is under the surveillance of personal computer thereby creating an energy efficient mobile infrastructure with power saving, reduction of CO2 emission which in turn reduces global warming and successful operation of large scale mobile communication services.

scholarly journals New framework for interference and energy analysis of soft frequency reuse in 5G networks

2020 ◽  
Vol 9 (5) ◽  
pp. 1941-1949
Author(s):  
Achonu Adejo ◽  
Osbert Asaka ◽  
Habeeb Bello- Salau ◽  
Caroline Alenoghena
Keyword(s):  
Cellular Networks ◽  
Spectral Efficiency ◽  
Network Performance ◽  
Base Station ◽  
Frequency Reuse ◽  
Base Stations ◽  
System Capacity ◽  
Management Technique ◽  
5G Networks ◽  
Soft Frequency Reuse

Cellular networks are expanding massively due to high data requirements from mobile devices. This has motivated base station densification as an essential requirement for the 5G network. The implication is obvious benefits in enhanced system capacity, but also increased challenges in terms of interference. One important interference management technique which has been widely adopted in cellular networks is frequency reuse. In this article, an analysis is presented based on network interference and energy expended by base stations in downlink communication when Soft frequency reuse (SFR) is deployed. A framework is presented that captures the bandwidth overlaps in SFR across base station assignments, computes the interference probabilities arising and derives new performance equations which are verified using simulations. Results show an improvement of over previous SFR implementations that do not consider the interference probabilities. Thus, a more in-depth and accurate modelling of SFR in 5G networks is achieved. Furthermore, the downlink power allocation is investigated as against other parameters like the center ratio and edge bandwidth. The result shows that signal-to-interference-noise ratio (SINR) and spectral efficiency give different performance under energy consideration. A framework is developed on how to tune a base station to achieve desired network performance in user SINR or cell spectral efficiency depending on the operator’s preference.

scholarly journals Comparison of high-latitude line-of-sight ozone column density with derived ozone fields and the effects of horizontal inhomogeneity

2006 ◽  
Vol 6 (7) ◽  
pp. 1843-1852 ◽  
Author(s):  
W. H. Swartz ◽  
J.-H. Yee ◽  
C. E. Randall ◽  
R. E. Shetter ◽  
E. V. Browell ◽  
...  
Keyword(s):  
High Latitude ◽  
Large Scale ◽  
Three Dimensional ◽  
Spatial Inhomogeneity ◽  
Line Of Sight ◽  
Validation Experiment ◽  
Rms Error ◽  
Horizontal Inhomogeneity ◽  
Column Ozone ◽  
Ozone Column

Abstract. Extensive ozone measurements were made during the second SAGE III Ozone Loss and Validation Experiment (SOLVE II). We compare high-latitude line-of-sight (LOS) slant column ozone measurements from the NASA DC-8 to ozone simulated by forward integration of measurement-derived ozone fields constructed both with and without the assumption of horizontal homogeneity. The average bias and rms error of the simulations assuming homogeneity are relatively small (−6 and 10%, respectively) in comparison to the LOS measurements. The comparison improves significantly (−2% bias; 8% rms error) using forward integrations of three-dimensional proxy ozone fields reconstructed from potential vorticity-O3 correlations. The comparisons provide additional verification of the proxy fields and quantify the influence of large-scale ozone inhomogeneity. The spatial inhomogeneity of the atmosphere is a source of error in the retrieval of trace gas vertical profiles and column abundance from LOS measurements, as well as a complicating factor in intercomparisons that include LOS measurements at large solar zenith angles.

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.

scholarly journals Using PSO Algorithm to Compensate Power Loss Due to the Aeroelastic Effect of the Wind Turbine Blade

Processes ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 633 ◽  
Author(s):  
Ying Zhao ◽  
Caicai Liao ◽  
Zhiwen Qin ◽  
Ke Yang
Keyword(s):  
Wind Speed ◽  
Optimization Model ◽  
Iteration Method ◽  
Power Loss ◽  
Large Scale ◽  
Three Dimensional ◽  
Pso Algorithm ◽  
Thrust Coefficient ◽  
Wind Speeds ◽  
Three Dimensional Finite Element

Power loss due to the aeroelastic effect of the blade is becoming an important problem of large-scale blade design. Prior work has already employed the pretwisting method to deal with this problem and obtained some good results at reference wind speed. The aim of this study was to compensate for the power loss for all of the wind speeds by using the pretwisting method. Therefore, we developed an aeroelastic coupling optimization model, which takes the pretwist angles along the blade as free variables, the maximum AEP (annual energy production) as the optimal object, and the smooth of the twist distribution as one of the constraint conditions. In this optimization model, a PSO (particle swarm optimization) algorithm is used and combined with the BEM-3DFEM (blade element momentum—three-dimensional finite element method) model. Then, the optimization model was compared with an iteration method, which was recently developed by another study and can well compensate the power loss at reference wind speed. By a design test, we found that the power loss can be reduced by pretwisting the origin blade, whether using the optimization model or the iteration method. Moreover, the optimization model has better ability than the iteration method to compensate the power loss with lower thrust coefficient while keeping the twist distribution smooth.

scholarly journals Smartphone Shadow Matching for Better Cross-street GNSS Positioning in Urban Environments

2014 ◽  
Vol 68 (3) ◽  
pp. 411-433 ◽  
Author(s):  
Lei Wang ◽  
Paul D Groves ◽  
Marek K Ziebart
Keyword(s):  
Large Scale ◽  
Signal To Noise Ratio ◽  
Three Dimensional ◽  
Satellite System ◽  
Urban Environments ◽  
Line Of Sight ◽  
Measured Signal ◽  
Gnss Positioning ◽  
Global Navigation Satellite ◽  
Dense Urban Environment

Global Navigation Satellite System (GNSS) shadow matching is a new positioning technique that determines position by comparing the measured signal availability and strength with predictions made using a three-dimensional (3D) city model. It complements conventional GNSS positioning and can significantly improve cross-street positioning accuracy in dense urban environments. This paper describes how shadow matching has been adapted to work on an Android smartphone and presents the first comprehensive performance assessment of smartphone GNSS shadow matching. Using GPS and GLONASS data recorded at 20 locations within central London, it is shown that shadow matching significantly outperforms conventional GNSS positioning in the cross-street direction. The success rate for obtaining a cross-street position accuracy within 5 m, enabling the correct side of a street to be determined, was 54·50% using shadow matching, compared to 24·77% for the conventional GNSS position. The likely performance of four-constellation shadow matching is predicted, the feasibility of a large-scale implementation of shadow matching is assessed, and some methods for improving performance are proposed. A further contribution is a signal-to-noise ratio analysis of the direct line-of-sight and non-line-of-sight signals received on a smartphone in a dense urban environment.

Sign in / Sign up

Export Citation Format

Share Document