SBL-Based Hybrid Precoder/ Combiner Design for Power and Spectrally Efficient Millimeter Wave MIMO Systems
This work proposes a novel sparse Bayesian learning (SBL)-based hybrid precoder/ combiner design scheme for millimeter wave (mmWave) MIMO systems. Towards this end, a multiple measurement vector (MMV) based sparse signal recovery problem is developed that maximizes the mutual information by approxim...
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| Vydané v: | International Conference on Signal Processing and Communications s. 1 - 5 |
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IEEE
01.07.2020
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| ISSN: | 2474-915X |
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| Abstract | This work proposes a novel sparse Bayesian learning (SBL)-based hybrid precoder/ combiner design scheme for millimeter wave (mmWave) MIMO systems. Towards this end, a multiple measurement vector (MMV) based sparse signal recovery problem is developed that maximizes the mutual information by approximating the hybrid precoder to the ideal digital precoder. A unique aspect of the proposed SBL-based scheme is that the resulting hyperparameter estimates can be used to activate the minimum number of RF chains required to approximate the ideal digital precoder/ combiner, thus enabling one to leverage the time-varying multipath profile of the underlying mmWave MIMO channel. This feature coupled with the improved ability of SBL for sparse signal recovery leads to a significantly enhanced power and spectral efficiency of the proposed scheme in comparison to the conventional schemes that activate a fixed number of RF chains and data streams, irrespective of the multipath profile of the mmWave MIMO channel. Simulation results demonstrate the improved efficiency of the proposed scheme in comparison to the existing schemes and also the resulting reduction in the average number of RF chains employed. |
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| AbstractList | This work proposes a novel sparse Bayesian learning (SBL)-based hybrid precoder/ combiner design scheme for millimeter wave (mmWave) MIMO systems. Towards this end, a multiple measurement vector (MMV) based sparse signal recovery problem is developed that maximizes the mutual information by approximating the hybrid precoder to the ideal digital precoder. A unique aspect of the proposed SBL-based scheme is that the resulting hyperparameter estimates can be used to activate the minimum number of RF chains required to approximate the ideal digital precoder/ combiner, thus enabling one to leverage the time-varying multipath profile of the underlying mmWave MIMO channel. This feature coupled with the improved ability of SBL for sparse signal recovery leads to a significantly enhanced power and spectral efficiency of the proposed scheme in comparison to the conventional schemes that activate a fixed number of RF chains and data streams, irrespective of the multipath profile of the mmWave MIMO channel. Simulation results demonstrate the improved efficiency of the proposed scheme in comparison to the existing schemes and also the resulting reduction in the average number of RF chains employed. |
| Author | Ascheid, Gerd Mishra, Amrita Jagannatham, Aditya K. Srivastava, Suraj |
| Author_xml | – sequence: 1 givenname: Suraj surname: Srivastava fullname: Srivastava, Suraj organization: Indian Institute of Technology,Department of Electrical Engineering,Kanpur,India – sequence: 2 givenname: Amrita surname: Mishra fullname: Mishra, Amrita organization: Dr. SPM IIIT-Naya,Department of E&C Engg.,Raipur,India – sequence: 3 givenname: Aditya K. surname: Jagannatham fullname: Jagannatham, Aditya K. organization: Indian Institute of Technology,Department of Electrical Engineering,Kanpur,India – sequence: 4 givenname: Gerd surname: Ascheid fullname: Ascheid, Gerd organization: Institute for Communication Technologies and Embedded Systems, RWTH Aachen University,Germany |
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| Snippet | This work proposes a novel sparse Bayesian learning (SBL)-based hybrid precoder/ combiner design scheme for millimeter wave (mmWave) MIMO systems. Towards this... |
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| Title | SBL-Based Hybrid Precoder/ Combiner Design for Power and Spectrally Efficient Millimeter Wave MIMO Systems |
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