The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because o...
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ISBN:
(纸本)9781728131061
The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because of the unit-norm constraint imposed by the use of phase shifters, the optimization of the radio frequency (RF) precoder and combiner becomes a non-convex problem. As a consequence, the algorithm for hybrid precoding and combining design often incurs high complexity. This paper proposes a low-complexity algorithm for hybrid precoding and combining design based on array response vectors. The proposed algorithm considers a decoupled optimization scheme between the RF and baseband domains for the spectral efficiency-maximization problem. In the RF domain, we propose an incremental successive selection method to find a subset of array response vectors from a dictionary, which forms the RF precoding/combining matrices. For the digital domain, we employ singular-value decomposition (SVD) of the low-dimensional effective channel matrix to generate the digital baseband precoder and combiner. Through numerical simulation, we show that the proposed algorithm achieves near-optimal performance with 89.9% - 99.4% complexity reduction compared to the conventional state-of-the-art hybrid precoding and combining algorithm.
Millimetre wave (mmWave) signal is promising for the challenge of bandwidth shortage and can motivate the research on large-scale antenna arrays. In this paper, the authors investigate the hybrid precoding design that...
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Millimetre wave (mmWave) signal is promising for the challenge of bandwidth shortage and can motivate the research on large-scale antenna arrays. In this paper, the authors investigate the hybrid precoding design that combines with a radio frequency (RF) precoder and a digital precoder for multi-user multiple-input single-output (MU-MISO) systems with large-scale antenna arrays. In practical large-scale antenna array systems, the small antenna spacing and the properties of a scattering environment can create a correlation between channel coefficients for separated receive units. Such correlation prejudices the performance of multi-user systems. This study proposes two approaches to reduce the channel correlation by the hybrid precoding structure. The first approach selects some vectors with the smallest influence with each other from all array response vectors to design an angular-based RF precoder. The second approach optimises the singular values characteristic of the virtual channel matrix before digital processing for the RF precoder. Then, the MU-MISO baseband precoding is implemented by reduced RF chains. Numerical results show that they have different performance depending on the environment. The first can achieve better performance when the channel correlation is not too high, while the second is more effective when the channel realisation is terribly ill-conditioned, especially for higher signal-noise ratio (SNR).
The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because o...
详细信息
The hybrid precoding and combining algorithms for mmWave massive multiple-input multiple-output (MIMO) systems must consider the trade-off between the complexity and performance of the system. Unfortunately, because of the unit-norm constraint imposed by the use of phase shifters, the optimization of the radio frequency (RF) precoder and combiner becomes a non-convex problem. As a consequence, the algorithm for hybrid precoding and combining design often incurs high complexity. This paper proposes a dictionary-constrained low-complexity algorithm for hybrid precoding and combining design. The proposed algorithm considers a decoupled optimization scheme between the RF and baseband domains for the spectral efficiency-maximization problem. In the RF domain, we propose an incremental successive selection method to find a subset of array response vectors from a dictionary, which forms the RF precoding/combining matrices. For the digital domain, we employ singular-value decomposition (SVD) of the low-dimensional effective channel matrix to generate the digital baseband precoder and combiner. Through numerical simulation, we show that the proposed algorithm achieves near-optimal performance while providing approximately up to 99 & x0025;complexity reduction compared to the conventional hybrid precoding and combining algorithms.
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