Precoding Algorithms for Massive Multiple-Input, Multiple-Output Wireless Systems

Ahmadian Tehrani, Amir Mehdi

Amir Mehdi Ahmadian Tehrani

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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
Author:: Ahmadian Tehrani, Amir Mehdi
Year:: 2020
Document type:: Dissertation
Faculty/School:: 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 Joint transmission coordinated multipoint (JT CoMP) MIMO-OFDM system is considered with 100 physical resource blocks (PRBs) per time transmission interval (TTI). «
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 pseudo inverse Berechnung bei 100 physical resource blocks (PRBs) pro time transmission interval (TTI) für Joint transmission coordinated multipoint (JT CoMP) massive MIMO-OFDM Systeme. «
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... »
WWW:: https://mediatum.ub.tum.de/?id=1524282
Date of submission:: 27.11.2019
Oral examination:: 15.05.2020
File size:: 5848456 bytes
Pages:: 115
Urn (citeable URL):: https://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:91-diss-20200515-1524282-1-5
Last change:: 16.04.2021
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