Multi-objective strategies for automatic cell planning of UMTS networks

Jamaa, S. Ben; Altman, Zwi; Picard, Jean-Marc; Fourestie, B.

doi:10.1109/vetecs.2004.1390710

Cited by 23 publications

(10 citation statements)

References 4 publications

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“…Sophisticated algorithms and heuristics have beed developed to cope with complexity of relevant optimization problems that, generally, belong to the class of NP-hard problems [15], [18]. The approaches in [4], [17] particularly tackle optimization problems that consider multiple KPI objectives. Regarding health risk issues in radio network optimization, it is a quite intuitive and trivial approach to formulate constraints that ensure the signal power level to stay below a certain threshold at critical points.…”

Section: Related Workmentioning

confidence: 99%

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Acceptance as a success factor for planning wireless network infrastructure

Engels

Neunerdt

Mathar

et al. 2011

2011 8th International Symposium on Wireless Communication Systems

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Availability of ubiquitous wireless services is taken for granted by most of the people. Therefore, network operators have to deploy and to operate large radio networks that, particularly, support broadband services and applications. One effect is a growing cell density, i.e., the number of required base stations increases. On the other hand, there are people that are afraid of getting harmed by electromagnetic radiation emitted by base stations or there are people that just dislike the prevalence of base station antennas. Both types of people's attitude refer to the field of user acceptance. A high deficiency in acceptance might lead to public disputes, political disputes, and negative economical consequences. To counteract such trends preventively, we propose a mathematical optimization model that allows for planning wireless network infrastructure with respect to user acceptance. While keeping technical and economical aspects as primarily considered planning criteria, we propose a multi-objective optimization model that takes into account user acceptance as an objective. Numerical results demonstrate effects of this approach compared to application of a conventional planning model.

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Section: Related Workmentioning

confidence: 99%

“…Basically, the considered Key Performance Indices (KPIs) for network deployment and configuration are coverage, capacity, and economical performance [3], [4], [5]. Optimization with respect to more than one of these KPIs generally leads to multi-objective optimization problems [6].…”

Section: Introductionmentioning

confidence: 99%

Acceptance as a success factor for planning wireless network infrastructure

Engels

Neunerdt

Mathar

et al. 2011

2011 8th International Symposium on Wireless Communication Systems

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“…For example, if the network planner wants to maximize the coverage, he will need to deploy more BSs thus, increasing the cost of the network. In their papers, Maple et al [11] and Jamaa et al [12] talk about a multi-objective function in which different objectives are given a certain weight (between 0 and 1). This weighted multi-objective function gives more flexibility to the network planner because he can assign higher (lower) weight to put more (less) emphasis on a given objective.…”

Section: Cell/base Station Planningmentioning

confidence: 99%

Topological planning and design of UMTS mobile networks: a survey

St-Hilaire

2008

Wireless Communications

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In this paper, we present a literature review on the topological planning problem of third generation (3G) cellular networks based on the universal mobile telecommunications system (UMTS) standard. After describing the UMTS architecture, we introduce each subproblem and present major works that have been done. The cell, the access and the core network planning problems have all been considered as well as a more global approach (when more than one subproblems are considered simultaneously). Both planning and expansion algorithms are also included in this review. The goal of this paper is to present and classify the different research works that have been done so that it can be used as a starting point for future research on topological design of UMTS networks.• The optimal number of BSs.• The best location to install the BSs. • The type (or model) of BSs. Fig. 2. UMTS planning subproblems.

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“…In turn, other methodologies such as simulated annealing, genetic algorithms or particle swarm algorithms provide, in general, better solutions at the expense of increasing the computation time and algorithm complexity . Several works that make use of these algorithms for the optimisation of mobile communication networks can be found in the literature . As an example, simulated annealing is used in Siomina et al .…”

Section: Introductionmentioning

confidence: 99%

A multi‐cell multi‐objective self‐optimisation methodology based on genetic algorithms for wireless cellular networks

et al. 2013

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Self-organising networks (SON) are seen as one of the hottest topics in telecommunication network research and development, eagerly awaited by network operators to achieve a reduction in operational expenditures.\ud However, there are still many challenges and dif¿culties when moving from the SON concept to practical implementation. In this context, this paper ¿rst provides a general formulation of the automated optimisation problem and a detailed description of the main challenges and dif¿culties ahead. Then, a generic multi-cell multi-objective self-optimisation methodology based on genetic algorithms is proposed. The proposed framework is formulated in detail for a joint coverage and overlap optimisation problem in a multi-cell scenario. A case study using real measurements of a Universal Mobile Telecommunications System network deployed in a medium-size European city is presented to illustrate the proposed methodology. In the presented\ud case study, the pilot power, antenna tilt and antenna azimuth of the different cells are optimised according to certain cell coverage and cell overlap targets. Results reveal that the genetic-based approach is able to provide optimised solutions that ef¿ciently achieve the desired targets accounting for inter-cell coupling effects.Peer ReviewedPostprint (published version

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Multi-objective strategies for automatic cell planning of UMTS networks

Cited by 23 publications

References 4 publications

Acceptance as a success factor for planning wireless network infrastructure

Acceptance as a success factor for planning wireless network infrastructure

Topological planning and design of UMTS mobile networks: a survey

A multi‐cell multi‐objective self‐optimisation methodology based on genetic algorithms for wireless cellular networks

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