Efficient Subchannel Allocation Based on Clustered Interference Alignment in Ultra-Dense Femtocell N

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In this paper, we exploit clustered interference alignment(IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access(OFDMA) based femtocell networks, which notably improves the spectral efficiency as well as addresses the feasibility issue of IA. Our problem is formulated as a combinatorial optimization problem which is NP-hard. To avoid obtaining its optimal solution by exhaustive search, we propose a two-phases efficient solution with low-complexity. The first phase groups all the femtocell user equipments(FUEs) into disjoint clusters, and the second phase allocates subchannels to the formed clusters where IA is performed. By doing this, the intra-cluster and inter-cluster interferences are mitigated by clustered IA and subchannel allocation in ultra-dense femtocell networks, respectively.Also, low-complexity algorithm is proposed to solve the corresponding sub-problem in each phase. Simulation results demonstrate that the proposed scheme not only outperforms other related schemes, but also provides a close performance to the optimal solution. In this paper, we exploit clustered interference alignment (IA) for efficient subchannel allocation in ultra-dense orthogonal frequency division multiplexing access (OFDMA) based femtocell networks, which notably improves the spectral efficiency as well as addresses the feasibility issue of IA. Our problem is formulated as a combinatorial optimization problem by exhaustive search, we propose a two-phases efficient solution with low-complexity. The first phase groups all the femtocell user equipments (FUEs) into disjoint clusters, and the second phase allocates subchannels to the formed clusters where IA is performed. By doing this, the intra-cluster and inter-cluster interferences are mitigated by clustered IA and subchannel allocations in ultra-dense femtocell networks, respectively. Also, low -complexity algorithm is proposed to solve the corresponding sub-problem in each phase. Simulation results demonstrate that the proposed schem e not only outperforms other related schemes, but also provides a close performance to the optimal solution.
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