Massive MIMO using low-resolution digital-to-analog converters (DACs) at the base station (BS) is an attractive downlink approach for reducing hardware overhead and for reducing power consumption, but managing the large quantization noise effect is a challenge. Spatial Sigma-Delta modulation is a recently emerged technique for tackling the aforementioned effect. Assuming a uniform linear array at the BS, it works by shaping the quantization noise as high spatial-frequency, or angle, noise. By restricting the user-serving region to be within a smaller angular region, the quantization noise incurred by the users can be effectively reduced. We previously showed that, under the one-bit DAC case, the quantization noise can be satisfactorily contained using a simple first-order Sigma-Delta modulation scheme. In this work we study the potential of spatial Sigma-Delta modulation in the two-bit DAC case and under second-order
modulation. Our empirical results indicate that second-order spatial Sigma-Delta modulation provides better quantization noise suppression.
more »
« less
Spatial Sigma-Delta Modulation for the Massive MIMO Downlink
In massive MIMO, replacing high-resolution ADCs/DACs with low-resolution ones has been deemed as a potential way to significantly reduce the power consumption and hardware costs of massive MIMO implementations. In this context, the challenge lies in how the quantization error effect can be suppressed under low-resolution ADCs/DACs. In this paper we study a spatial sigma-delta (ΣΔ) modulation approach for massive MIMO downlink precoding under one-bit DACs. ΣΔ modulation is a classical signal processing concept for coarse analog-to-digital/digital-to-analog conversion of temporal signals. Fundamentally its idea is to shape the quantization error as high-frequency noise and to avoid using the high-frequency region by oversampling. Assuming a uniform linear array at the base station (BS), we show how ΣΔ modulation can be adapted to the space, or MIMO, case. Essentially, by relating frequency in the temporal case and angle in the spatial case, we develop a spatial ΣΔ modulation solution. By considering sectored array operations we study how the quantization error effect can be reduced, and the effective SNR improved, for zero-forcing (ZF) precoding. Our simulation results show that ZF precoding under spatial ΣΔ modulation performs much better than ZF precoding under direct quantization.
more »
« less
- NSF-PAR ID:
- 10188442
- Date Published:
- Journal Name:
- 53rd Asilomar Conference on Signals, Systems, and Computers
- Page Range / eLocation ID:
- 833 to 837
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Coarsely quantized MIMO signalling methods have gained popularity in the recent developments of massive MIMO as they open up opportunities for massive MIMO implementation using cheap and power-efficient radio-frequency front-ends. This paper presents a new one-bit MIMO precoding approach using spatial Sigma-Delta (∑Δ) modulation. In previous one-bit MIMO precoding research, one mainly focuses on using optimization to tackle the difficult binary signal optimization problem that arise from the precoding design. Our approach attempts a different route. Assuming angular MIMO channels, we apply ∑Δ modulation—a classical concept in analog-to-digital conversion of temporal signals—in space. The resulting ∑Δ precoding approach has two main advantages: First, we no longer need to deal with binary optimization in ∑Δ precoding design. Particularly, the binary signal restriction is replaced by convex signal amplitude constraints. Second, the impact of the quantization error can be well controlled via modulator design and under appropriate operating conditions. Through symbol error probability analysis, we reveal that the very large number of antennas in massive MIMO provides favorable operating conditions for ∑Δ precoding. In addition, we develop a new ∑Δ modulation architecture that is capable of adapting the channel to achieve nearly zero quantization error for a targeted user. Furthermore, we consider multi-user ∑Δ precoding using the zero-forcing and symbol-level precoding schemes. These two ∑Δ precoding schemes perform considerably better than their direct one-bit quantized counterparts, as simulation results show.more » « less
-
In this paper, we focus on the multiuser massive multiple-input single-output (MISO) downlink with low-cost 1-bit digital-to-analog converters (DACs) for PSK modulation, and propose a low-complexity refinement process that is applicable to any existing 1-bit precoding approaches based on the constructive interference (CI) formulation. With the decomposition of the signals along the detection thresholds, we first formulate a simple symbol-scaling method as the performance metric. The low-complexity refinement approach is subsequently introduced, where we aim to improve the introduced symbol-scaling performance metric by modifying the transmit signal on one antenna at a time. Numerical results validate the effectiveness of the proposed refinement method on existing approaches for massive MIMO with 1-bit DACs, and the performance improvements are most significant for the low-complexity quantized zero-forcing (ZF) method.more » « less
-
Millimeter wave (mmW) communications is viewed as the key enabler of 5G cellular networks due to vast spectrum availability that could boost peak rate and capacity. Due to increased propagation loss in mmW band, transceivers with massive antenna array are required to meet a link budget, but their power consumption and cost become limiting factors for commercial systems. Radio designs based on hybrid digital and analog array architectures and the usage of radio frequency (RF) signal processing via phase shifters have emerged as potential solutions to improve radio energy efficiency and deliver performances close to the conventional digital antenna arrays. In this paper, we provide an overview of the state-of-the-art mmW massive antenna array designs and comparison among three array architectures, namely digital array, partially-connected hybrid array (sub-array), and fully-connected hybrid array. The comparison of performance, power, and area for these three architectures is performed for three representative 5G downlink use cases, which cover a range of pre-beamforming signal-to-noise-ratios (SNR) and multiplexing regimes. This is the first study to comprehensively model and quantitatively analyze all design aspects and criteria including: 1) optimal linear precoder, 2) impact of quantization error in digital-to-analog converter (DAC) and phase shifters, 3) RF signal distribution network, 4) power and area estimation based on state-of-the-art mmW circuits including baseband digital precoding, digital signal distribution network, high-speed DACs, oscillators, mixers, phase shifters, RF signal distribution network, and power amplifiers. Our simulation results show that the fully-digital array architecture is the most power and area efficient compared against optimized designs for sub-array and hybrid array architectures. Our analysis shows that digital array architecture benefits greatly from multi-user multiplexing. The analysis also reveals that sub-array architecture performance is limited by reduced beamforming gain due to array partitioning, while the system bottleneck of the fully-connected hybrid architecture is the excessively complicated and power hungry RF signal distribution network.more » « less
-
The uplink performance of a mixed analog-to-digital converter (ADC) massive multiple-input multiple-output (MIMO) architecture with a space-constrained array at the base station (BS) is analyzed. We investigate the effect of spatial correlation and mutual coupling on the spectral efficiency (SE) of the system. First, we analyze to what extent adding a small number of high-resolution ADCs can impact the channel estimation accuracy. Then, we derive a closed-form approximation for the SE. Our analysis demonstrates how a space constraint on a uniform linear array (ULA) can affect the design of a massive MIMO system with low-resolution ADCs. It is shown that by equally spacing a small number of high-resolution ADCs over the array, one can dramatically reduce the performance gap between a system with all low-resolution and all high-resolution ADCs.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/IEEECONF44664.2019.9048918
