研究目的
To implement a parallel framework for hybrid precoding in fast-fading environments and propose a low-complexity algorithm for hybrid precoding in multi-carrier single-user systems using OFDM, focusing on partially connected structures with per-RF chain power constraints.
研究成果
The proposed hybrid precoding algorithm offers a low-complexity, parallelizable solution for partially connected structures in mmWave massive MIMO OFDM systems, with practical per-RF chain power constraints. It demonstrates significant run-time advantages over existing schemes, making it suitable for fast-fading environments. However, spectral efficiency is compromised at high SNR, and increasing antennas without increasing RF chains degrades performance.
研究不足
The study is limited to single-user systems and does not extend to multi-user scenarios. The spectral efficiency is suboptimal at high SNR due to per-RF chain power constraints. The algorithm's performance degrades with increasing number of antennas without proportional increase in RF chains.
1:Experimental Design and Method Selection:
The study employs a hybrid precoding approach combining digital and analog precoding for massive MIMO systems. The methodology includes a parallel framework to address fast-fading environments and a low-complexity algorithm for OFDM systems.
2:Sample Selection and Data Sources:
The study uses simulated channel models, including the Saleh-Valenzuela model, NYU channel model, and 3GPP Clustered Delay Line model, to evaluate the proposed algorithm.
3:List of Experimental Equipment and Materials:
The study involves simulations on a machine with Intel(R) Xeon(R) CPU E5-2630 v2 running at 2.6GHz (24CPUs).
4:6GHz (24CPUs).
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: The proposed algorithm involves solving magnitude and phase subproblems independently, with simulations conducted over 1000 independent channel realizations.
5:Data Analysis Methods:
Performance is evaluated based on spectral efficiency, power allocation, and run-time, comparing the proposed algorithm with existing schemes.
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