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Original title:
Precoding Algorithms for Massive Multiple-Input, Multiple-Output Wireless Systems 
Translated title:
Precoding Algorithmen für massive Multiple-Input, Multiple-Output drahtlose Systeme 
Year:
2020 
Document type:
Dissertation 
Institution:
Fakultät für Elektrotechnik und Informationstechnik 
Advisor:
Kramer, Gerhard (Prof. Dr.) 
Referee:
Kramer, Gerhard (Prof. Dr.); Kobayashi, Mari (Prof., Ph.D.) 
Language:
en 
Subject group:
ELT Elektrotechnik 
Keywords:
Massive MIMO, 5G, JT CoMP, FLOPs, FDD, Low-complexity Moore-Penrose, Precoding, MIMO-OFDM, computational complexity, SINR 
Translated keywords:
Massive MIMO, 5G, JT CoMP, FLOPs, FDD, Low-complexity Moore-Penrose, Precoding, MIMO-OFDM, Berechnungskomplexität, SINR 
TUM classification:
ELT 500d 
Abstract:
Massive MIMO is a promising candidate technology to meet the ever-increasing wireless throughput demand in 5G mobile networks. To increase the spectral efficiency of orthogonal frequency division multiplexing (OFDM) massive MIMO, coordinated multipoint or cooperative MIMO has been identified as a potential solution. Low-complexity Moore-Penrose inverse precoding gains a factor of 100 in terms of floating point operations (FLOPs) with respect to using the full pseudo inverse calculation when a Jo...    »
 
Translated abstract:
Massive MIMO ist eine vielversprechende Technologie, um die stets wachsende Nachfrage nach drahtlosem Datendurchsatz für 5G Mobilfunknetze zu leisten. Um die spektrale Effizienz von orthogonal frequency division multiplexing (OFDM) massive MIMO zu steigern, wurde coordinated multipoint oder cooperative MIMO als mögliche Lösung identifiziert. Low-complexity Moore-Penrose inverse precoding verringert die Berechnungperformance in floating point operations (FLOPs) um Faktor 100 im Vergleich zu full...    »
 
Oral examination:
15.05.2020 
File size:
5848456 bytes 
Pages:
115 
Last change:
16.04.2021