Self-tuning of remote electrical tilts based on call traces for coverage and capacity optimization in LTE

Buenestado, V.; Toril, M.; Luna-Ramírez, Salvador; Ruiz-Avilés, J. M.; Mendo, Adriano

doi:10.1109/tvt.2016.2605380

Cited by 56 publications

(51 citation statements)

References 29 publications

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“…In particular, CCO is usually performed by changing antenna bearings [6,19,20,[24][25][26][27][28][29][30] or power settings [11-13, 15, 16]. Strategies to modify antenna bearings include both self-planning [6,19,[24][25][26] and self-optimization methods [20,[27][28][29][30].…”

Section: Related Workmentioning

confidence: 99%

“…simulator implementing a real macrocellular scenario has been developed in MATLAB [30]. The simulator is designed to make the most of available network statistics to model a live macrocellular scenario.…”

Section: Simulation Scenario a DL Static System-level Ltementioning

confidence: 99%

“…PRB utilization ratios are updated at every new loop by estimating the impact of ( ) changes on the radio link spectral efficiency at every cell. The reader is referred to [30] for a more detailed explanation of the simulation tool.…”

Section: Simulation Scenario a DL Static System-level Ltementioning

confidence: 99%

“…A third method is the iterative self-planning algorithm for remote electrical tilt (RET) based on trace files described in [30], denoted as TF-RET (for Trace-based Fuzzy). TF-RET adjusts antenna tilt values instead of base station transmit power.…”

Section: Algorithm Assessmentmentioning

confidence: 99%

See 3 more Smart Citations

Self-Planning of Base Station Transmit Power for Coverage and Capacity Optimization in LTE

Buenestado

Toril

Luna-Ramírez

et al. 2017

Mobile Information Systems

Self Cite

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A computationally efficient self-planning algorithm for adjusting base station transmit power in a LTE system on a cell-by-cell basis is presented. The aim of the algorithm is to improve the overall network spectral efficiency in the downlink by reducing the transmit power of specific cells to eliminate interference problems. The main driver of the algorithm is a new indicator that predicts the impact of changes in the transmit power of individual cells on the overall network Signal to Interference plus Noise Ratio (SINR) for the downlink. Algorithm assessment is carried out over a static system-level simulator implementing a live LTE network scenario. During assessment, the proposed algorithm is compared with a state-of-the-art self-planning algorithm based on the modification of antenna tilt angles. Results show that the proposed algorithm can improve both network coverage and capacity significantly compared to other automatic planning methods.

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Section: Related Workmentioning

confidence: 99%

Section: Simulation Scenario a DL Static System-level Ltementioning

confidence: 99%

Section: Simulation Scenario a DL Static System-level Ltementioning

confidence: 99%

Section: Algorithm Assessmentmentioning

confidence: 99%

See 2 more Smart Citations

Self-Planning of Base Station Transmit Power for Coverage and Capacity Optimization in LTE

Buenestado

Toril

Luna-Ramírez

et al. 2017

Mobile Information Systems

Self Cite

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show abstract

“…In [3], the authors propose a generic framework for improving SON algorithms with big data techniques to meet the requirements of future 5G 2 Mobile Information Systems networks. With a more limited scope, a self-tuning method is proposed for adjusting antenna tilts in a Long Term Evolution (LTE) system on a cell basis based on call traces [12]. Likewise, a review of network data used for self-healing in cellular networks is presented in [13].…”

Section: Introductionmentioning

confidence: 99%

Estimating Spectral Efficiency Curves from Connection Traces in a Live LTE Network

Toril

Acedo-Hernández

Sánchez

et al. 2017

Mobile Information Systems

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In cellular networks, spectral efficiency is a key parameter when designing network infrastructure. Despite the existence of theoretical model for this parameter, experience shows that real spectral efficiency is influenced by multiple factors that greatly vary in space and time and are difficult to characterize. In this paper, an automatic method for deriving the real spectral efficiency curves of a Long Term Evolution (LTE) system on a per-cell basis is proposed. The method is based on a trace processing tool that makes the most of the detailed network performance measurements collected by base stations. The method is conceived as a centralized scheme that can be integrated in commercial network planning tools. Method assessment is carried out with a large dataset of connection traces taken from a live LTE system. Results show that spectral efficiency curves largely differ from cell to cell.

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Self-Organizing Networks

Sun¹,

Li²

2015

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. Real time performance is one of the important features of SON. As one of the most common services, video should be coded with reduced complexity to satisfy real-time transmission. In this paper, fast algorithms for video coding have been discussed. Inter-prediction is an important part in HEVC contributing to compression efficiency but with heavy computational complexity and amount of studies about fast algorithm for inter-prediction have been done. With large amounts of previous works, this paper presents investigation results about previous efforts proposed algorithms according to their decision stage and criteria.

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Self-tuning of remote electrical tilts based on call traces for coverage and capacity optimization in LTE

Cited by 56 publications

References 29 publications

Self-Planning of Base Station Transmit Power for Coverage and Capacity Optimization in LTE

Self-Planning of Base Station Transmit Power for Coverage and Capacity Optimization in LTE

Estimating Spectral Efficiency Curves from Connection Traces in a Live LTE Network

Self-Organizing Networks

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