arXiv subjects

Anzhong Hu

Publications and source records attributed to Anzhong Hu.

4 recordsLinked to original sources

arXiv2026

Distributed Massive MIMO with 1-Bit Radio-over-Fiber Fronthaul: Uplink Spectral Efficiency and Power Control

We analyze the uplink spectral efficiency achievable in a distributed multiple-input multiple-output (D-MIMO) architecture employing a 1-bit radio-over-fiber fronthaul. This architecture eliminates the need for local oscillators at the access points, hence enabling coherent-phase transmission without costly over-the-air synchronization. With this fronthaul architecture, the uplink signal at the central processing unit is a dithered, oversampled, and 1-bit quantized version of the passband signal received at the access points. This makes some of the conventional spectral-efficiency expressions used in the D-MIMO literature not directly applicable for two key reasons: the nonlinearity of the input-output relation and the practical unavailability of minimum mean square error (MMSE) channel estimates. To address this issue, we propose novel achievable-rate expressions that do not require MMSE channel estimates and rely on the Bussgang decomposition to linearize the input-output relation. We use these expressions to determine the optimal signal-to-dither ratio (SDR) that maximizes the achievable rates in both single- and multiuser scenarios and to assess the impact of oversampling. We then use one of the proposed achievable-rate expressions to investigate the max-min fairness problem when the access points cannot maintain the optimal SDR because of limitations in their dynamic range.

eess.SP↗

arXiv2024

EVM Analysis of Distributed Massive MIMO with 1-Bit Radio-Over-Fiber Fronthaul

We analyze the uplink performance of a distributed massive multiple-input multiple-output (MIMO) architecture in which the remotely located access points (APs) are connected to a central processing unit via a fiber-optical fronthaul carrying a dithered and 1-bit quantized version of the received radio-frequency (RF) signal. The innovative feature of the proposed architecture is that no down-conversion is performed at the APs. This eliminates the need to equip the APs with local oscillators, which may be difficult to synchronize. Under the assumption that a constraint is imposed on the amount of data that can be exchanged across the fiber-optical fronthaul, we investigate the tradeoff between spatial oversampling, defined in terms of the total number of APs, and temporal oversampling, defined in terms of the oversampling factor selected at the central processing unit, to facilitate the recovery of the transmitted signal from 1-bit samples of the RF received signal. Using the so-called error-vector magnitude (EVM) as performance metric, we shed light on the optimal design of the dither signal, and quantify, for a given number of APs, the minimum fronthaul rate required for our proposed distributed massive MIMO architecture to outperform a standard co-located massive MIMO architecture in terms of EVM.

cs.IT↗

arXiv2014

An ESPRIT-Based Approach for 2-D Localization of Incoherently Distributed Sources in Massive MIMO Systems

In this paper, an approach of estimating signal parameters via rotational invariance technique (ESPRIT) is proposed for two-dimensional (2-D) localization of incoherently distributed (ID) sources in large-scale/massive multiple-input multiple-output (MIMO) systems. The traditional ESPRIT-based methods are valid only for one-dimensional (1-D) localization of the ID sources. By contrast, in the proposed approach the signal subspace is constructed for estimating the nominal azimuth and elevation direction-of-arrivals and the angular spreads. The proposed estimator enjoys closed-form expressions and hence it bypasses the searching over the entire feasible field. Therefore, it imposes significantly lower computational complexity than the conventional 2-D estimation approaches. Our analysis shows that the estimation performance of the proposed approach improves when the large-scale/massive MIMO systems are employed. The approximate Cramér-Rao bound of the proposed estimator for the 2-D localization is also derived. Numerical results demonstrate that albeit the proposed estimation method is comparable with the traditional 2-D estimators in terms of performance, it benefits from a remarkably lower computational complexity.

cs.IT↗

arXiv2014

Low-Complexity Transmission Mode Selection in MU-MIMO Systems

We propose a low-complexity transmission strategy in multi-user multiple-input multiple-output downlink systems. The adaptive strategy adjusts the precoding methods, denoted as the transmission mode, to improve the system sum rates while maintaining the number of simultaneously served users. Three linear precoding transmission modes are discussed, i.e., the block diagonalization zero-forcing, the cooperative zero-forcing (CZF), and the cooperative matched-filter (CMF). Considering both the number of data streams and the multiple-antenna configuration of users, we modify the common CZF and CMF modes by allocating data streams. Then, the transmission mode is selected between the modified ones according to the asymptotic sum rate analyses. As instantaneous channel state information is not needed for the mode selection, the computational complexity is significantly reduced. Numerical simulations confirm our analyses and demonstrate that the proposed scheme achieves substantial performance gains with very low computational complexity.

cs.IT↗