Title
Managing Hardware Impairments in Hybrid Millimeter Wave Mimo Systems: A Dictionary Learning-Based Approach
Abstract
Compressed sensing-based strategies have been derived in prior work to reduce training overhead when estimating the high dimensional millimeter wave MIMO channel. These techniques rely on a channel model based on a sparsifying dictionary which does not account for hardware impairments such as calibration errors, mutual coupling effects, or manufacturing errors in the inter-spacing between the array elements. In this paper, we propose a learning strategy for the sparsifying dictionary that considers a channel model with hardware impairments, embedding these effects into the dictionary itself. This way, a sparser representation of the channel can be obtained even when considering realistic implementations of the antenna array and the radio frequency chains. Numerical simulations with different system configurations and parameters of the hardware impairments, show the effectiveness of the proposed dictionary learning algorithm for channel estimation at millimeter wave frequencies with hybrid MIMO architectures.
Year
DOI
Venue
2019
10.1109/IEEECONF44664.2019.9049078
2019 53rd Asilomar Conference on Signals, Systems, and Computers
Keywords
DocType
ISSN
hardware impairments,hybrid millimeter wave Mimo systems,dictionary learning-based approach,compressed sensing-based strategies,high dimensional millimeter wave MIMO channel,channel model,sparsifying dictionary,calibration errors,mutual coupling effects,learning strategy,dictionary learning algorithm,channel estimation,millimeter wave frequencies,hybrid MIMO architectures
Conference
1058-6393
ISBN
Citations 
PageRank 
978-1-7281-4301-9
0
0.34
References 
Authors
5
3
Name
Order
Citations
PageRank
Joan Palacios1225.09
Nuria González Prelcic2111455.80
Jörg Widmer33924328.38