Abstract
This paper proposes a new user grouping algorithm and three-dimensional (3D) angular-based hybrid precoding (AB-HP) scheme for massive multi-user multiple-input multiple-output (MU-MIMO) systems using uniform rectangular arrays (URA). At first, the users clustered in multiple spots are efficiently grouped according to the proposed user grouping algorithm, which only utilizes the user angle-of-departure (AoD) information and does not require prior knowledge of the number of user groups. By employing the AoD support of the user groups, the RF-beamformer of AB-HP is designed to reduce the inter-group interference, the channel state information (CSI) overhead, and the number of RF chains. Then, the digital baseband precoder of AB-HP is constructed via regularized zero-forcing (RZF) using the effective channel seen from baseband to simultaneously serve the users clustered in multiple groups, by considering three approaches: joint-group-processing (JGP), per-group-processing (PGP) and common-group-processing (CGP). For each approach, the signal-to-interference-plus-noise ratio (SINR) expressions as well as their tight deterministic approximations are derived. To further reduce the number of RF chains, we also propose a new transfer block design, which reduces the number of RF chains down to the number of independent data streams without penalizing the sum-rate performance. Illustrative results reveal that the proposed AB-HP schemes with the relaxed CSI estimation overhead and reduced hardware cost/complexity can closely approach to the sum-rate performance of the single-stage fully-digital precoding (FDP). Furthermore, AB-HP has considerably higher energy efficiency performance compared to FDP due to the reduced number of RF chains. We show through simulation that the proposed AB-HP can offer significantly better performance than existing HP techniques. The computational complexity of AB-HP is also analyzed.
Highlights
Massive multiple-input multiple-output (MIMO) is one of the key technologies for the generation wireless communication systems [3]–[6]
CONTRIBUTIONS AND ORGANIZATION In this paper, a new user grouping algorithm and 3D angular-based hybrid precoding (HP) (AB-HP) technique is proposed for massive multi-user MIMO (MU-MIMO) systems, where the base station (BS) is equipped with uniform rectangular array (URA) and users are clustered in non-overlapping geographical regions
In order to fully exploit all paths while reducing the number of radio frequency (RF) chains, we propose a new transfer block architecture illustrated in Figure 4, which only requires NRF,g = Kg RF chains for each user group without affecting the sum-rate performance
Summary
Massive multiple-input multiple-output (MIMO) is one of the key technologies for the generation wireless communication systems [3]–[6]. [17] investigates HP design for the multi-carrier massive MIMO systems employing orthogonal frequency division multiple access transmission and proposes further reduction in hardware cost/complexity by decreasing the number of RF chains to the rank of FDP while achieving the similar sum-rate performance. Afterwards, [28] proposes a HP scheme for uniform circular arrays (UCA), where the RF beamformer using the phase mode transformation technique does not require any channel knowledge and it reduces the CSI overhead as well as the number of RF chains by transforming a large-size UCA into a reduced-size virtual ULA. B. CONTRIBUTIONS AND ORGANIZATION In this paper, a new user grouping algorithm and 3D angular-based HP (AB-HP) technique is proposed for massive MU-MIMO systems, where the BS is equipped with URA and users are clustered in non-overlapping geographical regions. We use x ∼ CN (0, σ ) when x is a complex Gaussian random variable with zero-mean and variance σ
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