Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/628536
Title: Precoding Design for Single-RF Massive MIMO Systems: A Large System Analysis
Authors: Houssem Sifaou;Abla Kammoun;Mohamed-Slim Alouini
subject: single RF transmitter|peak-to-average power ratio (PAPR)|random matrix theory|Massive MIMO
Year: 2016
Publisher: IEEE
Abstract: This letter revisits a recently proposed precoding design for massive multiple-input multiple-output (MIMO) systems that is based on the use of an instantaneous total power constraint. The main advantages of this technique lie in its suitability to the recently proposed single radio frequency MIMO transmitter coupled with a very-high power efficiency. Such features have been proven using simulations for uncorrelated channels. Based on tools from random matrix theory, we propose in this letter to analyze the performance of this precoder for more involved channels accounting for spatial correlation. The obtained expressions are then optimized in order to maximize the signal-to-interference-plus-noise ratio (SINR). Simulation results are provided in order to illustrate the performance of the optimized precoder in terms of peak-to-average power ratio and SINR.
URI: http://localhost/handle/Hannan/158034
http://localhost/handle/Hannan/628536
ISSN: 2162-2337
2162-2345
volume: 5
issue: 6
Appears in Collections:2016

Files in This Item:
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Title: Precoding Design for Single-RF Massive MIMO Systems: A Large System Analysis
Authors: Houssem Sifaou;Abla Kammoun;Mohamed-Slim Alouini
subject: single RF transmitter|peak-to-average power ratio (PAPR)|random matrix theory|Massive MIMO
Year: 2016
Publisher: IEEE
Abstract: This letter revisits a recently proposed precoding design for massive multiple-input multiple-output (MIMO) systems that is based on the use of an instantaneous total power constraint. The main advantages of this technique lie in its suitability to the recently proposed single radio frequency MIMO transmitter coupled with a very-high power efficiency. Such features have been proven using simulations for uncorrelated channels. Based on tools from random matrix theory, we propose in this letter to analyze the performance of this precoder for more involved channels accounting for spatial correlation. The obtained expressions are then optimized in order to maximize the signal-to-interference-plus-noise ratio (SINR). Simulation results are provided in order to illustrate the performance of the optimized precoder in terms of peak-to-average power ratio and SINR.
URI: http://localhost/handle/Hannan/158034
http://localhost/handle/Hannan/628536
ISSN: 2162-2337
2162-2345
volume: 5
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7553448.pdf411.54 kBAdobe PDFThumbnail
Preview File
Title: Precoding Design for Single-RF Massive MIMO Systems: A Large System Analysis
Authors: Houssem Sifaou;Abla Kammoun;Mohamed-Slim Alouini
subject: single RF transmitter|peak-to-average power ratio (PAPR)|random matrix theory|Massive MIMO
Year: 2016
Publisher: IEEE
Abstract: This letter revisits a recently proposed precoding design for massive multiple-input multiple-output (MIMO) systems that is based on the use of an instantaneous total power constraint. The main advantages of this technique lie in its suitability to the recently proposed single radio frequency MIMO transmitter coupled with a very-high power efficiency. Such features have been proven using simulations for uncorrelated channels. Based on tools from random matrix theory, we propose in this letter to analyze the performance of this precoder for more involved channels accounting for spatial correlation. The obtained expressions are then optimized in order to maximize the signal-to-interference-plus-noise ratio (SINR). Simulation results are provided in order to illustrate the performance of the optimized precoder in terms of peak-to-average power ratio and SINR.
URI: http://localhost/handle/Hannan/158034
http://localhost/handle/Hannan/628536
ISSN: 2162-2337
2162-2345
volume: 5
issue: 6
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7553448.pdf411.54 kBAdobe PDFThumbnail
Preview File