Manual and Automatic Design for UMTS Networks

This paper describes manual and automatic design strategies of UMTS networks. The design aims at adjusting antenna parameters: antenna pattern, tilt and azimuth angles, as well as the common channels' transmitted power to improve the network performance in terms of coverage, capacity, quality of service and service continuity. The manual design strategy is based on an expert system that analyzes different quality criteria of the network and suggests the designer the most effective parameter modifications. The automatic design strategy is based on a Genetic Algorithm that orchestrates the design process. Two optimisation models are considered: the first one uses constant load hypotheses in the network evaluation; the second one takes into account inhomogeneous traffic distribution and utilizes accurate modelling of basic UMTS quantities such as power, load and interference. Detailed examples of network optimization illustrate the effectiveness of the design strategies.     

Dynamic Self-Optimization of the Antenna Tilt for Best Trade-off Between Coverage and Capacity in Mobile Networks

One major factor influencing the coverage and capacity in mobile networks is related to the configuration of the antennas and especially the antenna tilt angle. By utilizing antenna tilt, signal reception within a cell can be improved and interference radiation towards other cells can be effectively reduced, which leads to a higher signal-to-interference-plus-noise ratio received by the users and increased sum data rate in the network. In this work, a method for capacity and coverage optimization using base station antenna electrical tilt in mobile networks is proposed. It has the potential to improve network performance while reducing operational costs and complexity, and to offer better quality of experience for the mobile users. Our solution is based on the application of reinforcement learning and the simulation results show that the algorithm improves significantly the overall data rate of the network, as compared to no antenna tilt optimization. The analysis in this paper focuses on the downlink of the cellular system. For the simulation experiments a multicellular and sectorized mobile network in an urban environment and randomly distributed user terminals are considered. The main contribution in this work is related to the development of a learning algorithm for automated antenna tilting.     

Planning effective cellular mobile radio networks

This paper deals with the automatic selection and configuration of base station sites for mobile cellular networks. An optimization framework based on simulated annealing is used for site selection and for base-station configuration. Realistic path-loss estimates incorporating terrain data are used. The configuration of each base station involves selecting antenna type, power control, azimuth, and tilt. Results are presented for several design scenarios with between 250 and 750 candidate sites and show that the optimization framework can generate network designs with desired characteristics such as high area coverage and high traffic capacity. The work shows that cellular network design problems are tractable for realistic problem instances     

A Rule‐Based Algorithm for Common Pilot Channel and Antenna Tilt Optimization in UMTS FDD Networks

In this paper we address the problem of capacity optimization in a Universal Mobile Telecommunication System (UMTS) radio network. We present an optimization algorithm for finding the best settings of the antenna tilt and common pilot channel power of the base stations. This algorithm is a parametric method, based on a set of rules. We evaluated our optimization technique on a virtual network scenario with 75 cells. For this scenario we show an increase in capacity compared to the initial settings of about 60 percent.     

Coverage planning for optimizing HSDPA performance and?controlling R99 soft handover

Coverage planning is an important engineering task in deploying UMTS networks implementing both high speed downlink packet access (HSDPA) and Release 99 (R99) services. Coverage planning amounts to determining the cell coverage pattern by means of setting the common pilot channel (CPICH) power of the cells. A conventional strategy is to uniformly allocate a proportion of the total power to CPICH. In this paper, we develop mathematical modeling and optimization approaches to bring the benefit of power saving enabled by optimizing non-uniform CPICH to enhance HSDPA performance, while preserving a desired degree of soft handover (SHO) for R99. The study focuses on HSDPA performance at cell edges, where data throughput is typically low. An integer linear programming model is developed for the resulting optimization problem. The model admits optimal or near-optimal planning solutions for relatively small networks. Solution algorithms based on local search and repeated local search are developed. These algorithms are able to perform the optimization for large-scale networks time-efficiently. Experimental results for both synthesized networks as well as instances originating from real planning scenarios demonstrate the benefit of our optimization approach.     

Modelling and planning fixed wireless networks

Abstract  

This paper describes a mathematical model for the automated design of fixed wireless access networks (FWA) through the automatic selection and configuration of base station sites. An optimisation algorithm is presented which generates the fixed wireless access network infrastructure design, and results are presented to illustrate the use of the model and its implementation. Economic measures based on the net present value (NPV) are defined to assess the financial viability of potential network designs. The NPV is used within the mathematical optimization framework to produce cost-effective deployments that maximize economic performance while maintaining technical constraints on the network. The model takes into account time-varying input parameters on CapEx, OpEx, revenues and subscriber requirements to model the dynamic nature of the market. Technical radio constraints taken into account include downlink area coverage, interference, capacity and availability. The model and optimisation framework are illustrated by considering the deployment and configuration of infrastructure for three scenarios representing urban, suburban and rural regions. Experiments illustrating the staged deployment of infrastructure over a number of time periods are also presented.     

Comparison and Extension of Existing 3D Propagation Models with Real-World Effects Based on Ray-Tracing

The next generation of cellular network deployment is heterogeneous and temporally changing in order to follow the coverage and capacity needs. Active Antenna Systems allows fast deployment changes by cell shaping and tilt adaptation which have to be controlled in self-organized manner. However, such kind of automated and flexible network operations require a Self Organizing Network (SON) algorithm that works based on network performance parameters being partly derived from the radio measurements. Thus, appropriate radio propagation models are not only needed for network planning tools but also for simulative lab tests of the developed SON algorithm controlling the flexible deployment changes enabled by Active Antenna Systems. In this paper, an extension of the existing 3D propagation model is proposed in order to incorporate the propagation condition variation effects, not considered so far, by changing antenna beam orientation like antenna tilting or when users are distributed in the third dimension (height) in multi-floor scenarios. Ray tracing based generated propagation maps that show the realistic propagation effect are used as 3D real world reference for investigation and model approval.     

Online CQI‐based optimization using k‐means and machine learning approach under sparse system knowledge

Modern cellular mobile networks are becoming more complicated and too expensive in terms of deployment, operation, and maintenance. Traffic demand in cellular networks typically experiences spatio‐temporal variations because of users' mobility and usage behaviour, which lead some of the cells to get overloaded without fully utilizing network capacity. To tackle these challenges, nowadays, self‐organizing networks (SONs) become an essential feature. This paper offers the development of an optimization framework for SONs based on channel quality indicator (CQI) and loading condition without detail knowledge of the network environment. Since the electrical tilt plays a key role in optimizing both coverage and capacity, the main motive is to ensure efficient network operation by electrical tilt‐based radio frequency (RF) performance optimization using a machine learning approach. This novel methodology shows two‐step optimization algorithms: (a) cluster formation based on handover success rate using k‐means algorithm and (b) reinforcement learning‐based optimization. Simulation and field trial shows that the proposed approach provides better results than the conventional method of prediction using genetic algorithm (GA) and other online approaches.     

多小区毫米波系统中无人机基站飞行姿态优化及性能分析

为了提高多小区毫米波系统中无人机基站覆盖区域内用户的通信质量,本文提出了一种无人机基站的飞行姿态优化方案。该方案首先在无人机基站天线数量趋于无穷大的情况下对吞吐量进行优化,得到最大吞吐量的渐近表达式,然后将吞吐量优化问题进一步细化为天线倾斜角优化问题,最后通过穷举搜索算法来获得使吞吐量最大的天线阵列倾斜角,进一步通过调整天线倾斜角以优化无人机飞行姿态。数值仿真结果表明,所提出的优化方案能够有效提高系统性能,对于多小区无人机毫米波通信系统的性能优化具有理论指导意义。      

基于人工蜂群算法的基站天线方位角与下倾角自优化方法

针对3GPP中提出的SON(self-organizing network,自组织网络)覆盖自优化问题,提出一种基于人工蜂群算法的基站天线方位角与下倾角同时优化方法。首先,基站根据用户设备上报的MR(measurement report,测量报告)数据确定待优化区域,并建立以基站天线对待优化区域的平均增益为目标函数的优化模型;其次,利用人工蜂群算法求解该目标函数,并得到基站天线方位角与下倾角的最优解;最后,将基站天线方位角与下倾角调整至最佳值,实现基站根据用户设备位置的覆盖自优化。通过系统建模、仿真与外场实验,以用户设备接收的RSRP(reference signal receiving power,参考信号接收功率)为指标,利用人工蜂群算法的计算方法较未优化的初始参数提升6.81 dB,较依靠人工经验的判别方法提升4.35 dB。实验结果证明,提出的自优化方法可根据用户位置分布精准及时地对基站天线方位角与下倾角进行调整,提升用户对信号强度的感知。     

Indoor Planning for High Speed Downlink Packet Access in WCDMA Cellular Network

The aim of this paper is to show the special characteristics of the indoor environment related to radio propagation and furthermore to radio network planning. The aspects of the radio network planning are highlighted especially for Wideband Code Division Multiple Access (WCDMA) radio access technology that is used widely in the third generation mobile networks. Moreover, the detailed planning parameters in indoor environment are studied for High Speed Downlink Packet Access (HSDPA) in order to support high throughput data applications in Universal Mobile Telecommunications System (UMTS). The final target of the paper is to compare pico cell, distributed antenna system (DAS), and radiating cable network configurations in indoor environment to provide the optimal radio conditions for the data applications, and thus to serve highest number of mobile users. Several measurement campaigns with different antenna configurations have been conducted in order to study the effect of multi path related parameters, as delay spread of the signal. Also other capacity related parameters as received signal levels, interference, throughput, and transmit power levels have been studied in order to find out the optimal solution for HSDPA in UMTS. The results clearly show that pico cells and distributed antenna system have outstanding performance in indoor propagation channel compared to radiating cable. In sense of signal quality, pico cell performance is slightly better compared to distributed antenna system. However, measurements with HSDPA indicate that practical capacity of DAS outperforms pico cells. The measurements also show that separation of the antennas is a key capacity related parameter when planning WCDMA based indoor systems.     

基于多层感知机模型的天线方位角诊断

作为影响移动通信质量的关键因素,天线方位角的准确性将直接影响网络优化质量。提出一种基于多层感知机的天线方位角诊断方法,将方位角分为12个区间类别,每个类覆盖30°范围,即[0,30°)记为类别0,…,[330°,360°)记为类别11,利用多层感知机算法识别天线方位角的区间,自动识别天线方位角的角度范围,为网络优化(网优)工程师判断实际的网络覆盖问题提供了有效的数据支撑,在核查天线性能方面极大地减少了工作量,降低了人工成本。实验结果表明,该方法能够有效快速判别天线方位角区间类别,识别准确率达到了92.6%,高于随机森林和逻辑回归分类算法的分类准确率。     

WCDMA无线系统的规划和优化

本文介绍了WCDMA的空中接口,提出了系统规划的方案,包括覆盖、容量、频率和码子的规划,同时讨论了WCDMA网络性能中关键的优化和监测指标.     

农村网络结构优化及用户感知提升新思路

农村网络覆盖制式多、频段多,存在MR弱覆盖、越区覆盖、质量差、语音回落和异频切换等诸多问题。本文利用MR、KPI、覆盖远近系数和频段制式进行网络分析;利用MDT、互联网众筹数据进行精准覆盖和用户分布分析;利用爬虫技术获取农村经纬度信息,结合工参、MR进行天馈方位角合理性排查。通过关联传统优化指标,并结合互联网、AI智能算法和大数据分析,大大提升优化效率,稳步提升农村网络覆盖水平和用户感知。     

Optimization of adaptive antenna system parameters in self-organizing LTE networks

In wireless communications the demand for wide range of services is leading to a rapid increase in network performance requirements. Hence, today’s cellular radio technologies are designed to operate closer to Shannon capacity bound which sets the ultimate upper limit for the wireless channel capacity. Yet, good link level performance does not necessarily mean that network resources are used efficiently as the cellular capacity and coverage performance may not be optimal resulting from dynamic conditions in radio network environment such as urbanization, insertion or deletion of base stations, and malfunctioning nodes. Due to the fact that reacting on those inherent problems manually is very expensive and time consuming, automated optimization of cellular coverage and capacity by means of self-optimization of adaptive antenna system parameters could be an attractive solution from the network operator’s point of view. Furthermore, suboptimal antenna parameter selection in long term evolution (LTE) network planning or the reuse of the sites and antenna parameters of a preceding access technology requires optimization of adaptive antenna system parameters. In this article we propose a novel centralized self-optimization approach that can be used for adapting antenna system parameters in order to automatically control network capacity and coverage in a macro-cellular deployment. In the proposed approach we present case-based reasoning (CBR) based self-optimization aided by an exemplary rule-based scheme which is required during the training phase of CBR. Dynamic system level downlink simulator is developed to validate the performance of the proposed approach in a realistic macro-cellular scenario. In performance evaluations the 3rd generation partnership project LTE system framework is assumed and propagation is modeled in three dimensions.     

UMTS radio network planning — maximizing return on investment

This article describes, based on the fundamentals of GSM radio network planning, the process of planning and optimizing UMTS networks. It highlights the key differences to existing 2G technologies and explains why UMTS radio network optimization is so complex that it cannot be done manually any more. This article gives some examples of cost efficient UMTS radio network enhancements in order to maximize future network capacities. It explains how UMTS return on investment is influenced by using advanced methods for radio network planning and optimization.     

一种新的智能性天线方位角计算及小区覆盖分析方法

在移动通信网络中天线方位角和小区覆盖发生偏差是影响移动通信质量的关键因素,传统采用人工测量或路测方式核查,耗时耗力。本文提出了一种新的智能性天线方位角计算及小区覆盖分析方法,该方法基于OMC中大量手机实测数据,计算天线方位角及偏差,从电平分布、采样点分布、干扰分类等多种因素来分析小区覆盖问题,同时基于GIS平台进行地图定位及呈现。该方法相比传统测量方法具有智能性、成本低、精度高的特点,已在实际系统中得到证实。     

Software radio architecture with smart antennas: a tutorial onalgorithms and complexity

There has been considerable interest in using antenna arrays in wireless communication networks to increase the capacity and decrease the cochannel interference. Adaptive beamforming with smart antennas at the receiver increases the carrier-to-interference ratio (CIR) in a wireless link. This paper considers a wireless network with beamforming capabilities at the receiver which allows two or more transmitters to share the same channel to communicate with the base station. The concrete computational complexity and algorithm structure of a base station are considered in terms of a software radio system model, initially with an omnidirectional antenna. The software radio computational model is then expanded to characterize a network with smart antennas. The application of the software radio smart antenna is demonstrated through two examples. First, traffic improvement in a network with a smart antenna is considered, and the implementation of a hand-off algorithm in the software radio is presented. The blocking probabilities of the calls and total carried traffic in the system under different traffic policies are derived. The analytical and numerical results show that adaptive beamforming at the receiver reduces the probability of blocking and forced termination of the calls and increases the total carried traffic in the system. Then, a joint beamforming and power control algorithm is implemented in a software radio smart antenna in a CDMA network. This shows that, by using smart antennas, each user can transmit with much lower power, and therefore the system capacity increases significantly     

Optimal base stations location and configuration for cellular mobile networks

In this paper, we study the problem of base stations location and configuration. Antenna configuration includes number of antennas installed at the base station, the azimuth of each base station, the tilt, height, and transmitted power for each antenna for cellular mobile networks. Towards this end, a mathematical model is formulated using integer programming (IP).The objective of the model is to minimize the cost of the network. The model guarantees that each demand point is covered. A demand point represents a cluster of uniformly distributed multiple users. In addition, the signal-to-interference-plus-noise ratio at each demand point is set at a given threshold value. A none-line-of-site situation is considered while calculating the path loss using COST-231-Walfisch-Ikegami propagation model. To illustrate the capability of the formulated IP model, we use a discretized map of some area with demand points. The IP model is solved using a commercial software, LINGO 12. Possible future research directions are stated in the conclusion.

     

移动通信天线方位角、倾角偏离的自动检测方法和实现

天线方位角、倾角的规划和调整是无线网络优化的重要内容之一,直接影响无线覆盖、网络质量和客户感知。本文提出一种基于工业级高精度传感器的天线方位角、倾角偏离自动检测方法和系统,创新性地改变了天线维护的工作模式,使天线维护由人工、被动的工作方式转变为主动、自发的维护方式,准确实时地检测到方位角、倾角改变,及时采取有效措施解决问题,可作为一种简单方便、直接有效的天线维护和网络优化的技术手段。