Complexity-Reduced Channel Matrix Inversion for MIMO Systems in Time-Varying Channels

Liu, Wei; Choi, Kwonhue; Liu, Huaping

doi:10.1109/vetecs.2010.5493753

Cited by 3 publications

(1 citation statement)

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“…The radiuses { r 1 u , r 2 u , r 3 u } are obtained by simulations in Section 6. During each iteration, UE i k requires

θ ((), M_{ik}^{3})

complex multiplications, and BS j requires

θ ((), N_{j}^{3})

complex multiplications for

1 \leq i, j \leq 3, 1 \leq k \leq K_{i}

…”

Section: Joint Algorithms For Cellular Networkmentioning

confidence: 99%

Inter‐cell interference mitigation based on joint beamforming

Yin

et al. 2014

Int J Communication

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SUMMARYIn cellular networks, global channel state information (CSI) shall be shared among neighboring cells to mitigate various inter-cell interference (ICI). In this paper, we propose that comparable ICI is mitigated while weak ICI is treated as noise. The amount of shared CSI is highly reduced, because of that only the CSI corresponding to comparable ICI is shared among neighboring cells. In the case of single user equipment in each cell, a joint singular value decomposition and interference alignment method is proposed along with the analysis of its approximate sum rate. Some nodes select singular value decomposition method, while others choose interference alignment method. The method at each node is determined by global selection principle or user classification principle. In the case of multiple UEs in each cell, all nodes utilize minimum mean square error method, but ICI is neglected at cell center users.

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“…The radiuses { r 1 u , r 2 u , r 3 u } are obtained by simulations in Section 6. During each iteration, UE i k requires