Achievable Rates for Full-Duplex Massive MIMO Systems With Low-Resolution ADCs/DACs

This paper investigates the uplink and downlink achievable rates of full-duplex (FD) massive multi-input-multi-output (MIMO) systems in which low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs) are employed and maximum ratio combining/maximum ratio transmission processing are adopted. Then, employing an additive quantization noise model, we derive approximate expressions of the uplink and downlink achievable rates, in which the effect of the quantization error, the loop interference, and the inter-user interference is considered. The theoretical results show that using proper power scaling law and more antennas can eliminate the interference and the noise. Furthermore, under the fixed number of antennas, the uplink and downlink approximate achievable rates will become a constant, as the number of quantization bits tends to infinity. Increasing the resolution of ADCs/DACs will limitedly improve the system performance but cause excessive overhead and power consumption, so adopting low-resolution ADCs/DACs in FD massive MIMO systems is sensible

Multipair Massive MIMO Relaying Systems with One-Bit ADCs and DACs

This paper considers a multipair amplify-and-forward massive MIMO relaying system with one-bit ADCs and one-bit DACs at the relay. The channel state information is estimated via pilot training, and then utilized by the relay to perform simple maximum-ratio combining/maximum-ratio transmission processing. Leveraging on the Bussgang decomposition, an exact achievable rate is derived for the system with correlated quantization noise. Based on this, a closed-form asymptotic approximation for the achievable rate is presented, thereby enabling efficient evaluation of the impact of key parameters on the system performance. Furthermore, power scaling laws are characterized to study the potential energy efficiency associated with deploying massive one-bit antenna arrays at the relay. In addition, a power allocation strategy is designed to compensate for the rate degradation caused by the coarse quantization. Our results suggest that the quality of the channel estimates depends on the specific orthogonal pilot sequences that are used, contrary to unquantized systems where any set of orthogonal pilot sequences gives the same result. Moreover, the sum rate gap between the double-quantized relay system and an ideal non-quantized system is a moderate factor of $4/\pi^2$ in the low power regime.Comment: 14 pages, 10 figures, submitted to IEEE Trans. Signal Processin

Performance Evaluation of Hybrid Precoder Design for Multi-User Massive MIMO Systems with Low-Resolution ADCs/DACs

This paper presents a comprehensive analysis and design of a hybrid precoding system tailored for mmWave multi-user massive MIMO systems in both downlink and uplink scenarios. The proposed system employs a two-stage precoding approach, incorporating UQ and NUQ techniques, along with low-resolution DACs in downlink and ADCs in uplink to address hardware limitations. The system considers Zero Forcing and Minimum Mean Square Error algorithms as digital precoding methods for the uplink scenario, while exploring the impact of different DAC resolutions on system performance. Extensive simulations reveal that the proposed system surpasses conventional analog beamforming methods, particularly in multi-user scenarios involving inter-user interference. In downlink, the system demonstrates a trade-off between SE and EE, achieving higher Energy Efficiency with NUQ. In uplink, NUQ and UQ converters exhibit similar performance trends regardless of the chosen combiner algorithm. The proposed system attains enhanced Spectral and Energy Efficiency while maintaining reduced complexity and overhead. The study significantly contributes to the advancement of efficient and effective mmWave multi-user massive MIMO systems by providing a thorough analysis of various quantization schemes and precoding techniques. The findings of this research are expected to aid in the optimization of 5G and beyond technologies, particularly in high-density deployment scenarios

UAV-Enabled Multi-Pair Massive MIMO-NOMA Relay Systems With Low-Resolution ADCs/DACs

In this article, we consider an unmanned aerial vehicle (UAV)-enabled massive multiple-input multiple-out (MIMO) non-orthogonal multiple access (NOMA) full-duplex (FD) two-way relay (TWR) system with low-resolution analog-to-digital converters/digital-to-analog converters (ADCs/DACs), where the UAV provide services for multi-pair ground users (GUs). By employing maximum ratio combining/maximum ratio transmission (MRC/MRT), the approximate closed-form expressions for sum spectrum/energy efficiency (SE/EE) with imperfect channel state information (CSI), imperfect successive interference cancellation (SIC) and quantization noise are derived. To evaluate the effects of the parameters on system performance, the asymptotic analysis and the power scaling laws are further provided. Finally, an optimization scheme is proposed to maximize the SE of the considered system. The numerical results verify the accuracy of theoretical analysis and show that the interference and noise can be effectively eliminated by deploying large-scale antennas and applying proper power scaling law. We also demonstrate that the proposed system can obtain better SE by adjusting the height of the UAV. Moreover, the system performance is related to the ADCs/DACs quantization bits, where the SE saturation values increase by increasing number of quantization bits, while the EE first increases and then decreases. Finally, the SE/EE trade-off at low precision ADCs/DACs can be achieved by choosing the appropriate number of quantization bits, and the trade-off region grows as Rician factor increases

Achievable rates for full-duplex massive MIMO systems with low-resolution ADCs/DACs under imperfect CSI environment

We investigate the uplink and downlink achievable rates of full-duplex (FD) massive multi-input multi-output (MIMO) systems with low-resolution analog-digital converters/digital-to-analog converters (ADCs/DACs), where maximum ratio combining/maximum ratio transmission (MRC/MRT) processing are adopted and imperfect channel state information (CSI) is assumed. In this paper, the quantization noise is encapsulated as an additive quantization noise model (AQNM). Then, employing the minimum mean-square error (MMSE) channel estimator, approximate expressions of the uplink and downlink achievable rates are derived, based on the analysis of the quantization error, loop interference (LI), and the inter-user interference (IUI). It is shown that the interference and noise can be eliminated by applying power scaling law properly and increasing the number of antennas. Moreover, given the number of antennas, it is found that the uplink and downlink approximate achievable rates will converge to a constant when the number of quantization bit tends to infinity. Therefore, the system performance that can be improved by increasing ADC/DAC resolution is limited, implying that it is reasonable to adopt low-resolution ADCs/DACs in FD massive MIMO systems

Optimization of Massive Full-Dimensional MIMO for Positioning and Communication

Massive Full-Dimensional multiple-input multiple-output (FD-MIMO) base stations (BSs) have the potential to bring multiplexing and coverage gains by means of three-dimensional (3D) beamforming. Key technical challenges for their deployment include the presence of limited-resolution front ends and the acquisition of channel state information (CSI) at the BSs. This paper investigates the use of FD-MIMO BSs to provide simultaneously high-rate data communication and mobile 3D positioning in the downlink. The analysis concentrates on the problem of beamforming design by accounting for imperfect CSI acquisition via Time Division Duplex (TDD)-based training and for the finite resolution of analog-to-digital converter (ADC) and digital-to-analog converter (DAC) at the BSs. Both \textit{unstructured beamforming} and a low-complexity \textit{Kronecker beamforming} solution are considered, where for the latter the beamforming vectors are decomposed into separate azimuth and elevation components. The proposed algorithmic solutions are based on Bussgang theorem, rank-relaxation and successive convex approximation (SCA) methods. Comprehensive numerical results demonstrate that the proposed schemes can effectively cater to both data communication and positioning services, providing only minor performance degradations as compared to the more conventional cases in which either function is implemented. Moreover, the proposed low-complexity Kronecker beamforming solutions are seen to guarantee a limited performance loss in the presence of a large number of BS antennas.Comment: 30 pages, 6 figure