Hybrid Precoding with Adaptive Sub-connected Architecture for mmWave Massive MIMO Systems
| Autor: | Xiaoyu Bai, Fulai Liu, Huajing Liu, Huiyang Shi, Ruiyan Du |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
021103 operations research
Computer science MIMO 0211 other engineering and technologies 0202 electrical engineering electronic engineering information engineering 020206 networking & telecommunications 02 engineering and technology Spectral efficiency Topology Precoding Communication channel Efficient energy use |
| Zdroj: | PIMRC |
| DOI: | 10.1109/pimrc48278.2020.9217223 |
| Popis: | Hybrid precoding is considered as a promising candidate technology for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. Conventional hybrid precoder with fixed fully-connected or sub-connected (SC) architectures often requires lots of phase shifters (PSs) with considerable power consumption. To address the challenge, this paper firstly presents an adaptive SC (ASC) hybrid precoding architecture, which dynamically divides the antennas elements into several subsets according to the channel environments, and each subset is connected to all RF chains with a small number of PSs. Owing to the flexible division and much fewer PSs, the proposed ASC architecture is expected to achieve a high spectral efficiency with lower power consumption in comparison to the conventional SC architecture. Afterwards, an alternative optimization hybrid precoding algorithm is proposed based on the ASC architecture. The proposed algorithm optimizes the switch precoding matrix via enumerations, and then an elegant diagonal loading factor is derived to reformulate the objective function of the PS precoding matrix as a positive semidefinite quadratic form, so that the PS precoding matrix can be derived easily. Simulation results show that the proposed hybrid precoding architecture and algorithm can remarkably improve the energy efficiency when maintaining a high spectral efficiency compared with the conventional counterpart. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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