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Multiobjective optimization of fractional frequency reuse for irregular OFDMA macrocellular deployments

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Abstract

Interference mitigation has been identified as a key challenge for emerging cellular technologies based on Orthogonal Frequency Division Multiple Access, such as Long Term Evolution. In this context, static intercell interference coordination including Fractional Frequency Reuse (FFR) have been adopted by mobile operators as a good alternative to improve the quality of service at cell edges. Nevertheless, recent results made evident the need for additional research efforts as default FFR configurations only offer tradeoffs in which spectral efficiency is severely penalized. Moreover, the performance of such baseline designs has been showed to be poor in realistic cellular deployments featuring irregular cell patterns. This paper solves this problematic by introducing a novel multiobjective optimization framework based on evolutionary algorithms that jointly takes into account system capacity, cell edge performance, and energy consumption. With respect to important reference schemes, the proposed algorithm succeeds in finding FFR configurations achieving gains between 10 and 40 % in terms of system capacity while simultaneously improving cell edge performance up to 70 %.

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Notes

  1. Baseline designs refer to settings in which the operational parameters of FFR (\(S_{\text {TH}}, \alpha \) and \(\beta \)) are uniformly applied to all cells of the network.

  2. The definition and evaluation of the objective functions \(f_{1}\), \(f_{2}\), and \(f_{3}\) is presented in Subsect.  5.4.

  3. Metaheuristics are high level (generic) procedures that can be applied to solve a wide range of optimizations problems [18, 22, 24].

  4. The search space was obtained after an initial trial and error procedure required to localize the region of interest, i.e., \(K\times \beta \times S_{\text {TH}_{\text {dB}}}\) = \(\{3,4\}\times \{0.300,0.325,0.350,\cdots ,0.500\}\times \{-4,-3,\cdots ,5\}\).

  5. Note that 2D profiles are generated by projecting the Pareto Front onto the \(f_1\)-\(f_2\), \(f_1\)-\(f_3\), and \(f_2\)-\(f_3\) planes. They are an alternative representation providing better insights about the tradeoff between each pair of objective functions.

    Fig. 9
    figure 9

    Representations of the Pareto front \(\fancyscript{X}^{\star }\) and reference schemes

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Authors and Affiliations

  1. Department of Communications and Networking (COMNET), School of Electrical Engineering, Aalto University, Espoo, Finland

    David González G.

  2. Department of Signal Theory and Communications, Universitat Politècnica de Catalunya, BarcelonaTech, Barcelona, Spain

    Mario García-Lozano & Silvia Ruiz

  3. King’s College London, London, UK

    María A. Lema

  4. Building Energy Management System (BEMS), Samsung DMC R&D Center, Seoul, South Korea

    Dongseop Lee

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  1. David González G.
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Correspondence to David González G..

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González G., D., García-Lozano, M., Ruiz, S. et al. Multiobjective optimization of fractional frequency reuse for irregular OFDMA macrocellular deployments. Telecommun Syst 61, 659–673 (2016). https://doi.org/10.1007/s11235-015-0060-3

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