Title
Channel Estimation and Training Design for Hybrid Analog-Digital Multi-Carrier Single-User Massive MIMO Systems
Abstract
In this paper we study the channel estimation problem for a CP-OFDM based hybrid analog-digital massive MIMO system. In contrast to a conventional MIMO system, two additional constraints need to be fulfilled. First, the analog precoding is achieved using only a phase shift network, which imposes constant modulus constraints on the elements of the RF precoding and decoding matrices. Second, there is just one common equivalent RF precoding or decoding matrix for all subcarriers. These constraints lead to a challenging channel estimation task that includes the training design. To estimate the channel at the receiver, a least squares (LS) method and a compressed sensing (CS) method with a single-stage or a two-stage design are introduced. Compared to the single-stage designs, the two-stage designs have a lower computational complexity. Sufficient conditions for a unique channel estimation are derived for both methods. Simulation results show that the CS method provides more accurate channel estimates than the LS method under mild conditions.
Year
Venue
Field
2016
WSA 2016; 20th International ITG Workshop on Smart Antennas
Least squares,3G MIMO,Computer science,MIMO,Communication channel,Algorithm,Decoding methods,Precoding,Compressed sensing,Computational complexity theory
DocType
ISBN
Citations 
Conference
978-3-8007-4177-9
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Jianshu Zhang111313.21
Ivan Podkurkov211.02
Martin Haardt33531311.32
Adel Nadeev412.04