Self-Organized Coverage and Capacity Optimization for Cellular Mobile Networks

Die zur Erfüllung der zu erwartenden Steigerungen übertragener Datenmengen notwendige größere Heterogenität und steigende Anzahl von Zellen werden in der Zukunft zu einer deutlich höheren Komplexität bei Planung und Optimierung von Funknetzen führen. Zusätzlich erfordern räumliche und zeitliche Änderungen der Lastverteilung eine dynamische Anpassung von Funkabdeckung und -kapazität (Coverage-Capacity-Optimization, CCO). Aktuelle Planungs- und Optimierungsverfahren sind hochgradig von menschlichem Einfluss abhängig, was sie zeitaufwändig und teuer macht. Aus diesen Grnden treffen Ansätze zur besseren Automatisierung des Netzwerkmanagements sowohl in der Industrie, als auch der Forschung auf groes Interesse.Selbstorganisationstechniken (SO) haben das Potential, viele der aktuell durch Menschen gesteuerten Abläufe zu automatisieren. Ihnen wird daher eine zentrale Rolle bei der Realisierung eines einfachen und effizienten Netzwerkmanagements zugeschrieben. Die vorliegende Arbeit befasst sich mit selbstorganisierter Optimierung von Abdeckung und Übertragungskapazität in Funkzellennetzwerken. Der Parameter der Wahl hierfür ist die Antennenneigung. Die zahlreichen vorhandenen Ansätze hierfür befassen sich mit dem Einsatz heuristischer Algorithmen in der Netzwerkplanung. Im Gegensatz dazu betrachtet diese Arbeit den verteilten Einsatz entsprechender Optimierungsverfahren in den betreffenden Netzwerkknoten. Durch diesen Ansatz können zentrale Fehlerquellen (Single Point of Failure) und Skalierbarkeitsprobleme in den kommenden heterogenen Netzwerken mit hoher Knotendichte vermieden werden.Diese Arbeit stellt einen "Fuzzy Q-Learning (FQL)"-basierten Ansatz vor, ein einfaches Maschinenlernverfahren mit einer effektiven Abstraktion kontinuierlicher Eingabeparameter. Das CCO-Problem wird als Multi-Agenten-Lernproblem modelliert, in dem jede Zelle versucht, ihre optimale Handlungsstrategie (d.h. die optimale Anpassung der Antennenneigung) zu lernen. Die entstehende Dynamik der Interaktion mehrerer Agenten macht die Fragestellung interessant. Die Arbeit betrachtet verschiedene Aspekte des Problems, wie beispielsweise den Unterschied zwischen egoistischen und kooperativen Lernverfahren, verteiltem und zentralisiertem Lernen, sowie die Auswirkungen einer gleichzeitigen Modifikation der Antennenneigung auf verschiedenen Knoten und deren Effekt auf die Lerneffizienz.Die Leistungsfähigkeit der betrachteten Verfahren wird mittels eine LTE-Systemsimulators evaluiert. Dabei werden sowohl gleichmäßig verteilte Zellen, als auch Zellen ungleicher Größe betrachtet. Die entwickelten Ansätze werden mit bekannten Lösungen aus der Literatur verglichen. Die Ergebnisse zeigen, dass die vorgeschlagenen Lösungen effektiv auf Änderungen im Netzwerk und der Umgebung reagieren können. Zellen stellen sich selbsttätig schnell auf Ausfälle und Inbetriebnahmen benachbarter Systeme ein und passen ihre Antennenneigung geeignet an um die Gesamtleistung des Netzes zu verbessern. Die vorgestellten Lernverfahren erreichen eine bis zu 30 Prozent verbesserte Leistung als bereits bekannte Ansätze. Die Verbesserungen steigen mit der Netzwerkgröße.The challenging task of cellular network planning and optimization will become more and more complex because of the expected heterogeneity and enormous number of cells required to meet the traffic demands of coming years. Moreover, the spatio-temporal variations in the traffic patterns of cellular networks require their coverage and capacity to be adapted dynamically. The current network planning and optimization procedures are highly manual, which makes them very time consuming and resource inefficient. For these reasons, there is a strong interest in industry and academics alike to enhance the degree of automation in network management. Especially, the idea of Self-Organization (SO) is seen as the key to simplified and efficient cellular network management by automating most of the current manual procedures. In this thesis, we study the self-organized coverage and capacity optimization of cellular mobile networks using antenna tilt adaptations. Although, this problem is widely studied in literature but most of the present work focuses on heuristic algorithms for network planning tool automation. In our study we want to minimize this reliance on these centralized tools and empower the network elements for their own optimization. This way we can avoid the single point of failure and scalability issues in the emerging heterogeneous and densely deployed networks.In this thesis, we focus on Fuzzy Q-Learning (FQL), a machine learning technique that provides a simple learning mechanism and an effective abstraction level for continuous domain variables. We model the coverage-capacity optimization as a multi-agent learning problem where each cell is trying to learn its optimal action policy i.e. the antenna tilt adjustments. The network dynamics and the behavior of multiple learning agents makes it a highly interesting problem. We look into different aspects of this problem like the effect of selfish learning vs. cooperative learning, distributed vs. centralized learning as well as the effect of simultaneous parallel antenna tilt adaptations by multiple agents and its effect on the learning efficiency.We evaluate the performance of the proposed learning schemes using a system level LTE simulator. We test our schemes in regular hexagonal cell deployment as well as in irregular cell deployment. We also compare our results to a relevant learning scheme from literature. The results show that the proposed learning schemes can effectively respond to the network and environmental dynamics in an autonomous way. The cells can quickly respond to the cell outages and deployments and can re-adjust their antenna tilts to improve the overall network performance. Additionally the proposed learning schemes can achieve up to 30 percent better performance than the available scheme from literature and these gains increases with the increasing network size

Self-optimization of pilot power in enterprise femtocells using multi objective heuristic

Deployment of a large number of femtocells to jointly provide coverage in an enterprise environment raises critical challenges especially in future self-organizing networks which rely on plug-and-play techniques for configuration. This paper proposes a multi-objective heuristic based on a genetic algorithm for a centralized self-optimizing network containing a group of UMTS femtocells. In order to optimize the network coverage in terms of handled load, coverage gaps, and overlaps, the algorithm provides a dynamic update of the downlink pilot powers of the deployed femtocells. The results demonstrate that the algorithm can effectively optimize the coverage based on the current statistics of the global traffic distribution and the levels of interference between neighboring femtocells. The algorithm was also compared with the fixed pilot power scheme. The results show over fifty percent reduction in pilot power pollution and a significant enhancement in network performance. Finally, for a given traffic distribution, the solution quality and the efficiency of the described algorithm were evaluated by comparing the results generated by an exhaustive search with the same pilot power configuration

ANALISIS DROP CALL PADA LAYANAN SUARA (VOICE) SISTEM WCDMA BERDASARKAN DATA STATISTIK DAN DRIVE TEST PADA DAERAH DAYEUH KOLOT BANDUNG

ABSTRAK Drop Call pada jaringan UMTS (Universal Mobile Telecommunication System) merupakan pemutusan kanal trafik oleh UE (User Equipment) ataupun Node-B yang disebabkan oleh faktor transmisi atau jaringan dan hal tersebut tidak dikehendaki oleh pelanggan. Pada tugas akhir ini dianalisis penyebab terjadinya drop call serta dilakukan optimasi pada jaringan 3G-UMTS. Daerah penelitian yang dianalisis ialah daerah Dayeuh Kolot, Bandung. Penelitian dilakukan dengan cara pengumpulan data performansi existing baik dari data Statistic serta hasil pengukuran kinerja dengan cara drive test. Drive test dilakukan pada tanggal 8 Mei 2015 pada pukul 16.00 WIB – 17.00 WIB menggunakan software TEMS 8.0 Dari hasil drive test before didapatkan nilai RSCP berada pada bad level, yaitu pada range -93 dbm. Sedangakan nilai Ec/No berada pada bad level, yaitu pada range -18 db. Dari hasil drive test juga ditemukan kasus drop call sebanyak 1 kasus. Analisa yang dilakukan pada penelitian ini meliputi: Coverage analysis, Overshooting analysis. Dan parameter yang diperhitungkan untuk analisis dan optimasi ialah Ec/No, RSCP. Pada penelitian tugas akhir ini didapatkan nilai parameter sebagai berikut RSCP sebesar -93 dBm Ec/No sebesar -18 dB. Hasil analisis dari penelitian ini menunjukan drop call yang terjadi di daerah Dayeuh kolot, Bandung tepatnya pada Jalan Radio Palasari disebabkan oleh coverage problem dan overshooting problem. Drop call terjadi karena cakupan sinyal dari node-B yang kurang baik, indikator coverage problem pada UMTS adalah RSCP. Dimana RSCP yang diperoleh pada saat drive test berada pada level yang buruk yaitu –93 dbm. sedangkan overshoot sendiri merupakan suatu kondisi dimana terdapat sel yang men-serving daerah yang terletak sangat jauh dari koordinatnya. Dikatakan jauh dapat ditinjau berdasarkan daerah yang di cover sel tersebut seharusnya di cover oleh sel yang terletak lebih dekat. Dimana pada kasus drop call ini site Dayeuh Kolot mengalami overshooting problem. Selanjutnya dilakukan optimasi melalui simulasi menggunakan software Atoll. Optimasi yang dilakukan yaitu mengubah coverage area yang dilayani oleh node-B dengan melakukan teknik tilting antenna. Sebelumnya sudut kemiringan antenna pada Site Dayeuh Kolot bernilai v 4º. Sesudah dilakukan tilting diubah menjadi 5º. Dari hasil analisis dan optimasi ini dapat dilihat perubahan yang terjadi pada daerah yang bermasalah tersebut. Kata Kunci: drop call, KPI, coverage problem, overshoot, drive test, 3G-UMT

Interference model and antenna parameters setting effects on 4G-LTE networks coverage

International audienceThe currently emerging Long Term Evolution 4G-LTE cellular networks are based on new technique of transmission called the Orthogonal Frequency Division Multiple Access (OFDMA). This paper shows the interest of robust approach due to the uncertainty of traffic distribution. First, we develop and validate the interference model based on SINR metric for the deployment of the LTE network, and then we use greedy algorithms to show how frequency and tilt parameter settings can impact the coverage performance metric. Two frequency schemes have been compared to validate our model: the frequency reuse 1 scheme whereby the whole available bandwidth is used in each cell/sector and the frequency reuse 3 scheme in which the entire bandwidth is divided into 3 non-overlapping groups and assigned to 3 co-site sectors within each cell

Indoor Planning in Broadband Cellular Radio Networks

The capacity requirements of cellular networks continue to grow. This has forced cellular operators to seek new ways of improving the availability and transmission rate experienced by users. The majority of cellular network data users are located inside buildings, where coverage is difficult to ensure due to high penetration loss. Indoor users also cause high load to outdoor networks, reducing the quality and availability for outdoor users. This has given rise to a growing need for implementing dedicated indoor systems, and further optimizing their performance to provide high capacity. It was estimated that in 2011 there were 5.37 billion mobile subscriptions in 3GPP-supported GSM, UMTS/HSPA and LTE networks, of which 890.7 million were using UMTS/HSPA. Currently, UMTS is the leading standard for providing mobile broadband, although LTE is becoming increasingly popular. The planning of radio networks is well known and documented. However, the planning and optimization of indoor networks has not been widely studied, although clear improvements in both coverage and capacity can be achieved by optimizing cell- and antenna line configuration. This thesis considers the special characteristics of the indoor environment with regard to radio propagation and radio network planning. The aspects of radio network planning are highlighted especially for WCDMA radio access technology. The target is to provide guidelines for indoor radio network planning and optimization using an outdoor-to-indoor repeater or a dedicated indoor system with various antenna and cell configurations. The studies conducted here are intended to provide better understanding of the indoor functionality and planning of WCDMA radio access, and UMTS cellular system including the latest HSPA updates. The studies show that the indoor performance of a high data rate WCDMA system can be improved by increasing the antenna density in the distributed antenna system, or by utilizing uplink diversity reception. It is also shown how system capacity can be further improved by adding more indoor cells to a single building. The inter-cell interference is analyzed, and the limits for cell densification are discussed. The results show that compared to dedicated indoor systems, similar indoor performance can be provided by extending macrocellular coverage inside buildings using an outdoor-to-indoor repeater. However, good performance of repeater implementation needs careful repeater antenna line and parameter configuration. Nevertheless, capacity is in any case borrowed from an outdoor mother cell. Sharing frequencies between outdoor and indoor systems is often necessary due to high capacity demand and limited available frequency band. A co-channel indoor system was measured to affect both uplink and downlink performance of an outdoor cell. In the uplink, a clear increase in uplink intercell interference was observed. Throughput degradation was also measured in downlink, but the affect is limited to the area close to the indoor system. However, the added high capacity of an indoor network usually justifies performance degradation. The results can help mobile operators design their networks to provide better coverage, higher capacity and better quality for indoor users. After taking into account the implementation costs, the results also help operators to reach a techno-economic trade-off between the various deployment options

A survey of self organisation in future cellular networks

This article surveys the literature over the period of the last decade on the emerging field of self organisation as applied to wireless cellular communication networks. Self organisation has been extensively studied and applied in adhoc networks, wireless sensor networks and autonomic computer networks; however in the context of wireless cellular networks, this is the first attempt to put in perspective the various efforts in form of a tutorial/survey. We provide a comprehensive survey of the existing literature, projects and standards in self organising cellular networks. Additionally, we also aim to present a clear understanding of this active research area, identifying a clear taxonomy and guidelines for design of self organising mechanisms. We compare strength and weakness of existing solutions and highlight the key research areas for further development. This paper serves as a guide and a starting point for anyone willing to delve into research on self organisation in wireless cellular communication networks

Auto-tuning of RRM parameters in UMTS networks. Feasibility study.

Due to the intrinsic characteristics of WCDMA and the great number of services offered by UMTS, its radio channel is much more dynamic compared with GERAN systems. The traffic fluctuations and users mobility can cause the impairment of the network performance and of the quality of service (QoS) in certain cells. In the worst case a significant degradation of the QoS may be observed and as a result the operator defined targets are not met. Nowadays UMTS operators have fixed, and usually uniform, settings for their network parameters. This static configuration is not able to adapt automatically to the changes that occur in the network. A fixed parameter setting then gives a non optimal solution for the network optimization process and thus the utilization of the radio interface is not maximized. The goal of the automated tuning is to adjust dynamically these parameters in a continuous way without human intervention, which is only required in definition of the reference QoS. The current PFC aims at validating the feasibility of automated optimization of certain UMTS RRM parameters. The main tasks to be developed by the students are: - Simulator developement (Matlab programmed). A basic static Montecarlo simulator is available as a reference. - Study of UMTS handover algorithm and study of potential parameters to be automatically tuned. - Proposal of algorithm to tune the previously selected parameters, and evaluation of achieved gains. - Study of UMTS CAC algorithm and study of potential parameters to be automatically tuned. Development of first and basic ideas to propose tuning algorithm.The present PFC is located inside the framework of the UMTS networks, and more specifically in the development of new Radio Resource Management (RRM) algorithms capable to maximize the capacity and the performance of the network. In this sense a powerful simulation tool capable to analyze in depth the behavior of the UMTS network under different simulation scenarios has been developed. It has been focused in the study of the main algorithms that manage the allocation of radio resources in UMTS networks: Power Control (PC), Admission Control (AC) and Soft/Softer Handover (SHO). The problem observed in classical SHO strategies is the rigidity of the mechanism, which cannot adapt to variations in the traffic patterns. The improvements on SHO procedures are based on dynamic automated tuning of SHO parameters. A three blocks based functional architecture is described to adapt parameters to service mix dynamics and overcome capacity problems. Several tests have been done over different traffic situations in order to demonstrate the feasibility of the Auto-Tuning System (ATS). The results obtained show a considerable increment in the network capacity. In this sense ATS is considered as an effective pre-congestion-control strategy. Referring now to AC strategies, it is necessary to underline that three new AC algorithms have been implemented: Dynamic AC, Complete Partitioning AC (CP-AC) and Complete Sharing AC (CS-AC) strategies have been developed with the same goal, enhance the capacity of the network. Dynamic AC was proposed to provide flexibility to the current AC algorithm. This strategy is based on the ATS philosophy where a dynamic AC threshold is fixed to the optimum threshold in real time according to the current service mix. On the other hand, CS-AC and CP-AC are complex strategies based on static algorithms where fixed thresholds or load margins were applied in order to note their advantages and drawbacks depending on the users distribution, uniform or mostly close to the cell edge. As a result of this project a scientific publication inside the context of COST european projects has been carried out. In special, is about the COST 2100 ”Pervasive Mobile & Ambient Wireless Communications” and the title of the publication is ”Automatic Tuning of Soft Handover Parameters in UMTS Networks”. The paper was presented in the meeting number 3, held in Duisburg (Germany) between 10th and 12th of September 2007