Analysis and Optimization for Downlink Cell-Free Massive MIMO System with Mixed DACs

Abstract

This paper concentrates on the rate analysis and optimization for a downlink cell-free massive multi-input multi-output (MIMO) system with mixed digital-to-analog converters (DACs), where some of the access points (APs) use perfect-resolution DACs, while the others exploit low-resolution DACs to reduce hardware cost and power consumption. By using the additive quantization noise model (AQNM) and conjugate beamforming receiver, a tight closed-form rate expression is derived based on the standard minimum mean square error (MMSE) channel estimate technique. With the derived result, the effects of the number of APs, the downlink transmitted power, the number of DAC bits, and the proportion of the perfect DACs in the mixed-DAC architecture are conducted. We find that the achievable sum rate can be improved by increasing the proportion of the perfect DACs and deploying more APs. Besides, when the DAC resolution arrives at 5-bit, the system performance will invariably approach the case of perfect DACs, which indicates that we can use 5-bit DACs to substitute the perfect DACs. Thus, it can greatly reduce system hardware cost and power consumption. Finally, the weighted max–min power allocation scheme is proposed to guarantee that the users with high priority have a higher rate, while the others are served with the same rate. The simulation results prove the proposed scheme can be effectively solved by the bisection algorithm.

Analysis one‐bit DAC for MU massive MIMO downlink via efficient autoencoder based deep learning

“…Where n q ∼  (0, 𝜎 2 n q ) is AWGN, 𝜌 = P∕𝜉 p and 𝛼 q denotes a linear gain shown in Table 1 below (for b > 5, generally, the quantization factor can be estimated by 𝛼 q ≈ 𝜋 √ 3 2 2 −2b ) [15,28]. At this stage, the signal received by users can be interpreted as…”

“…Applying Equation (), and according to AQNM [27], the quantization operation on the signal received by the users can be expressed as follows $$$$\begin{eqnarray} {\bf y}= \sqrt {\mathcal {{\bf P}}} {\bf H} (\alpha _q {\bf s} +{\bf n}_q)+ {\bf n} =\sqrt {\rho } {\bf H} \alpha _q{\bf P}{\bf x}+\sqrt {\mathcal {{\bf P}}} {\bf H} {\bf n}_q +{\bf n}\nonumber\\ \end{eqnarray}$$$$Where $${\bf n}_q \sim \mathcal {CN}(0,\sigma _{n_q}^2)$$ is AWGN, $$\rho ={\mathcal {\bf P}} / {\xi }_p$$ and $$\alpha _q$$ denotes a linear gain shown in Table 1 below (for $$b > 5$$, generally, the quantization factor can be estimated by $$\alpha _q \approx \frac{\pi \sqrt {3}}{2} 2^{-2b}$$) [15, 28].…”

“…These studies highlight the substantial reduction in power consumption and hardware costs achievable with mixed (DAC/ADC) architectures for mMIMO systems. Furthermore, investigations in [15,16] delved into the performance of a downlink system featuring a mixed DAC architecture, connecting some antennas to low-resolution (2-3 bit) DACs and others to high-resolution (5-bit) DACs. Notably, these systems maintained high DAC resolution.…”

Performance of digital predistorter in system with analogue to digital converter

“…[36] that is used to model the quantised signal mathematically. In recent studies [37–40] AQNM has been applied to study the quantised signal with an arbitrary number of ADC bits. In AQNM, we denote the ADC output that corresponds to input z by $$z_{q}$$ as shown in Figure 1, i.e.…”

Deep Learning-Based Channel Estimation for mmWave Massive MIMO Systems in Mixed-ADC Architecture

“…However, low-resolution ADCs are prone to severe non-linear distortion, which inevitably causes several problems, including high pilot overhead for channel estimation [ 10 ], the system performance loss and signal detection [ 11 ]. In order to balance the cost and performance of the system, a mmWave massive MIMO system with a mixed ADC architecture was proposed in [ 12 , 13 ], which replaces the low-resolution ADCs with the partial high-resolution ADCs on the original basis. As reported in [ 14 ], channel estimation in a mixed-resolution ADC architecture is easier to process than in a pure low-resolution ADC system.…”