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Wireless Networks
Published in: Wireless Networks 6/2014

01-08-2014

A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments

A multiobjective strategy suitable for Self-Optimizing Networks

Authors: David González G., Mario García-Lozano, Silvia Ruiz, Dong Seop Lee

Published in: Wireless Networks | Issue 6/2014

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Abstract

The explosive growth of cellular networks makes their deployment and maintenance more and more complex, time consuming, and expensive. Self-Organizing Networks have been recognized as a promising way to alleviate this problem by minimizing human intervention in such processes. This paper introduces a novel multiobjective framework, based on evolutionary optimization, aiming at improving network performance and users Quality of Service. By tuning the transmitted power at each cell, average intercell interference levels are minimized. The design of the proposed scheme is feasible for distributed implementations in Long Term Evolution (LTE) and LTE-Advanced networks and its operation is compatible with current specifications. The framework is able to provide effective network-specific optimization and obtained results show that gains in terms of network capacity and cell edge performance are 5 and 10 %, respectively. Energy savings always accompanied such enhancements with reductions up to 35 %.
previous article Improving mobile network performance with two queueing buffer allocations of priority-based queueing scheme
next article Fractionally spaced equalizer based on dynamically varying modulus algorithm for spectrally efficient channel compensation in SC-FDMA based systems

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Footnotes
1
Although typically joint optimization of several parameters results in higher gains, the associated complexity or computational cost results in feasibility issues.
 
2
The framework proposed in this article is partially based on the scheme originally presented in [37].
 
3
In LTE, Reference Signals (RS) are embedded into the system bandwidth to allow channel estimation/equalization and synchronization, see [38] and [39].
 
4
A solution \({\mathbf{x}}_{1}\) is preferred to (dominates in the Pareto sense) another solution \({\mathbf{x}}_{2}, ({\mathbf{x}}_{1}\succ{\mathbf{x}}_{2})\), if \({\mathbf{x}}_{1}\) is better than \({\mathbf{x}}_{2}\) in at least one criterion and no worse in the remaining ones.
 
5
In LTE, a Resource Block (RB) is composed of a set of 12 contiguous subcarriers [38].
 
6
If particular spatial traffic distributions are required to be considered, the extension of the proposed multiobjective framework is straightforward by weighting different zones of the coverage area. This can be done by assigning different probabilities to individual pixels instead of assuming that every pixel has the same probability. Therefore, f 1 and f 2 would be computed according to the general definition of the expected value.
 
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Metadata
Title
A metaheuristic-based downlink power allocation for LTE/LTE-A cellular deployments
A multiobjective strategy suitable for Self-Optimizing Networks
Authors
David González G.
Mario García-Lozano
Silvia Ruiz
Dong Seop Lee
Publication date
01-08-2014
Publisher
Springer US
Published in
Wireless Networks / Issue 6/2014
Print ISSN: 1022-0038
Electronic ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-013-0659-9

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