Abstract
This paper is concerned with a multi-cell downlink (DL) massive multiple-input multiple-output (MIMO) system operating over spatially correlated Rician fading channels. We not only consider estimating channel state information (CSI) at the base station (BS), but also adopt beamforming training (BT) to obtain CSI at the users. With maximum-ratio transmission (MRT) or zero-forcing (ZF) employed at the BS to process the transmit signals, the paper derives closed-form expressions of the sum spectral efficiency for both cases: with and without BT. Based on the obtained closed-form expressions, we investigate the effect of the DL pilot length on the system performance for MRT and ZF precoding and with or without BT. Moreover, when the DL pilot length falls within different ranges, we find out whether using BT leads to better system performance. To address the energy efficiency (EE) maximization problem under the constraints of a given sum spectral efficiency and a maximum total DL transmit power, we transform the problem into a geometric program (GP), which can be solved more efficiently. In particular, we develop one iterative power allocation algorithm for the system with BT scheme. Simulation and numerical results demonstrate that the proposed power allocation algorithm can improve the system EE. Numerical results also show that when the BS uses MRT precoding, the sum spectral efficiency in the high signal-to-noise ratio (SNR) region is much improved with BT.
Highlights
Multiple-input multiple-output (MIMO) systems equipped with a very large number of antennas, commonly referred to as massive MIMO, or large-scale MIMO, have been recognized as an important technology for current and future generations of wireless communications
For the multi-cell DL massive MIMO system operating over spatially correlated Rician fading channels, when the base station (BS) uses maximum-ratio transmission (MRT) or ZF precoding to process DL transmission of data and pilots, we derive closed-form expressions of the sum spectral efficiency for both cases, with and without beamforming training (BT)
For the multi-cell DL massive MIMO system with BT scheme, we develop an optimal power allocation algorithm for assigning DL transmit power in order to maximize the EE for a desired sum spectral efficiency and a given total maximum DL transmit power
Summary
Multiple-input multiple-output (MIMO) systems equipped with a very large number of antennas, commonly referred to as massive MIMO, or large-scale MIMO, have been recognized as an important technology for current and future generations of wireless communications. For a distributed large-scale MIMO system operating over Rayleigh fading channels, references [16], [17] investigate the benefits of BT scheme and study how the number of antennas and the length of coherence interval affect the spectral efficiency of this system. While the works in [13]–[15] and [23]–[26] mainly focus on studying the system’s spectral efficiency and do not consider EE, our paper investigates the EE optimization problem for a multicell massive MIMO system over spatially correlated Rician fading channels with BT scheme. For the multi-cell DL massive MIMO system operating over spatially correlated Rician fading channels, when the BS uses MRT or ZF precoding to process DL transmission of data and pilots, we derive closed-form expressions of the sum spectral efficiency for both cases, with and without BT. We have hiln ∼ CN hiln, Riln , where hiln describes the LOS component and Riln is a positive semidefinite covariance matrix representing the spatial correlation characteristics of the NLOS component
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