A GEVD Based Interference Alignment Method for Uplink Heterogeneous Network Under imperfect CSIT

The heterogeneous network (HetNet) is a promising technology for deploying the next generation wireless networks. The major issue concerning multi-tier architecture in HetNets is the interference between the users in femtocells and macrocells i.e. cross-tier interference. In this paper, we propose a...

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Vydáno v:TENCON ... IEEE Region Ten Conference s. 835 - 840
Hlavní autoři: Najlah, C. P., Sameer, S. M.
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.10.2019
Témata:
channel state information at the transmitter (CSIT)
Covariance matrices
cross-tier interference
Decoding
Femtocells
Heterogeneous network (HetNet)
Interference
interference alignment (IA)
interference cancellation (IC)
Macrocell networks
MIMO communication
Signal to noise ratio
ISSN:2159-3450
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Popis
Shrnutí:The heterogeneous network (HetNet) is a promising technology for deploying the next generation wireless networks. The major issue concerning multi-tier architecture in HetNets is the interference between the users in femtocells and macrocells i.e. cross-tier interference. In this paper, we propose a generalized eigenvalue decomposition (GEVD) based interference alignment (IA) technique for the uplink of a HetNet under imperfect channel state information at the transmitter (CSIT). The proposed method exploits the stochastic knowledge of error in CSI mismatch to model an approximated channel. By using the approximated channel, we design a robust precoder and decoder to harvest the benefit promised by multi-tier architecture under imperfect CSIT. We perform exhaustive simulation studies to evaluate the performance of the proposed technique in terms of the achieved bit error rate (BER) and sum rate. We compared the proposed method with a prevailing method in the literature known as Max-SINR algorithm and found that it achieves better performance. Further, the proposed method can be applied to realistic scenarios where the channel state information is imperfect.
ISSN:2159-3450
DOI:10.1109/TENCON.2019.8929704