Sparsity‐based MIMO interference suppression technique in the presence of imperfect channel state information

Sedghi, Rana; Azghani, Masoumeh

doi:10.1049/iet-com.2019.0420

Cited by 6 publications

(1 citation statement)

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“…In [18], the ZF precoding and block diagonalization (BD) schemes have been used in the MBS and SBS, respectively, to reduce the downlink interference. In [19], the sparse precoding matrix is designed to suppress the interference and improve the energy efficiency in homogeneous networks in the presence of channel estimation error. A signal is called sparse where most of its entries are zero in some domain [20].…”

Section: Introductionmentioning

confidence: 99%

Interference suppression in heterogeneous massive MIMO systems with imperfect CSI

Sedghi

Azghani

2022

Telecommun Syst

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Interference management is of paramount importance in heterogeneous massive mimo networks (HetNet). In this paper, an algorithm has been suggested to suppress the interference in large-MIMO HetNets with imperfect channel state information(CSI). The proposed technique controls both the intra-tier and cross-tier interference of the macrocell as well as the small cells. The intra-tier interference of the macrocell as well as the cross-tier interference have been minimized under maximum transmission power and minimum signal to interference and noise ratio (SINR) constraint. The channel estimation error matrix has also been modeled using the joint sparsity property. The precoding algorithm is thus achieved through the application of semi-definite relaxation and block coordinate descent techniques. The intra-tier interference of the small cells are addressed with the aid of the zero forcing scheme. The proposed method has been validated through various simulations which confirm the superiority of the algorithm over its counterparts.

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Section: Introductionmentioning

confidence: 99%