Paper Info
Title
Low Complexity Moore-Penrose Inverse For Large Comp Areas With Sparse Massive Mimo Channel Matrices
Abstract
Joint transmission coordinated multipoint (JT CoMP) has been identified as a potential differentiator for future 5G radio systems due to its superior interference mitigation capabilities. Further, the combination with massive multiple-input-multiple-output (mMIMO) when a set of fixed grid of beams is used at eNodeB results in sparse overall channel matrices with a relatively low number of relevant channel components, which reduces the feedback overhead for reporting of channel state information (CSI). Although JT CoMP faces several challenges from synchronization to CSI outdating, in this paper the focus will be on complexity reduction of the precoding over large clustered cells utilizing massive MIMO. It will be derived how the typical sparse number of relevant channel components per user equipment can be exploited to reduce the number of floating point operations (FLOPs) by a factor of ten compared to state-of-the-art solutions for the calculation of the Moore Penrose pseudo inverse of the channel matrix.
Year
Venue
Keywords
2016
2016 IEEE 27TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR, AND MOBILE RADIO COMMUNICATIONS (PIMRC)
Moore-Penrose inverse, FLOPs, massive MIMO
Field
DocType
Citations 
Matrix (mathematics),Floating point,Computer science,Communication channel,MIMO,Algorithm,Theoretical computer science,Real-time computing,Reduction (complexity),User equipment,Precoding,Channel state information
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Amir M. Ahmadian100.34
Wolfgang Zirwas200.34
Rakash SivaSiva Ganesan3609.30
Berthold Panzner41969.79