In future high-capacity wireless systems based on mmWave or massive multiple input multiple output (MIMO), the power consumption of receiver Analog to Digital Converters (ADC) is a concern. Although hybrid or analog systems with fewer ADCs have been proposed, fully digital receivers with many lower resolution ADCs (and lower power) may be a more versatile solution. In this paper, focusing on an uplink scenario, we propose to take the optimization of ADC resolution one step further by enabling variable resolutions in the ADCs that sample the signal received at each antenna. This allows to give more bits to the antennas that capture the strongest incoming signal and fewer bits to the antennas that capture little signal energy and mostly noise. Simulation results show that, depending on the unquantized link SNR, a power saving in the order of 20-80 can be obtained by our variable resolution proposal in comparison with a reference fully digital receiver with a fixed low number of bits in all its ADCs.
DC systems using low-resolution ADCs to reduce power consumption are further analyzed in @cite_3 @cite_19 , showing that a few bits are enough to achieve almost the spectral efficiency (SE) of an unquantized system of the same characteristics. It is possible to use analog switches instead of analog mixers to create a hybrid scheme that samples only the best subset of the antennas of the array to reduce power consumption, as proposed in @cite_18 . In addition to switching the best antennas to high resolution ADCs, it is possible to add 1-bit ADCs to sample the rest of the antennas as in @cite_13 , achieving a large fraction of the capacity of a full-high-resolution architecture.
@cite_19 @cite_18 @cite_13 @cite_3
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The low-resolution analog-to-digital convertor (ADC) is a promising solution to significantly reduce the power consumption of radio frequency circuits in massive multiple-input multiple-output (MIMO) systems. In this letter, we investigate the uplink spectral efficiency (SE) of massive MIMO systems with low-resolution ADCs over Rician fading channels, where both perfect and imperfect channel state information are considered. By modeling the quantization noise of low-resolution ADCs as an additive quantization noise, we derive tractable and exact approximation expressions of the uplink SE of massive MIMO with the typical maximal-ratio combining (MRC) receivers. We also analyze the impact of the ADC resolution, the Rician @math -factor, and the number of antennas on the uplink SE. Our derived results reveal that the use of low-cost and low-resolution ADCs can still achieve satisfying SE in massive MIMO systems. Motivated by the demand for energy-efficient communication solutions in the next generation cellular network, a mixed-ADC architecture for massive multiple-input-multiple-output (MIMO) systems is proposed, which differs from previous works in that herein one-bit analog-to-digital converters (ADCs) partially replace the conventionally assumed high-resolution ADCs. The information-theoretic tool of generalized mutual information (GMI) is exploited to analyze the achievable data rates of the proposed system architecture and an array of analytical results of engineering interest are obtained. For fixed single-input-multiple-output (SIMO) channels, a closed-form expression of the GMI is derived, based on which the linear combiner is optimized. The analysis is then extended to ergodic fading channels, for which tight lower and upper bounds of the GMI are obtained. Impacts of dithering and imperfect channel state information (CSI) are also investigated, and it is shown that dithering can remarkably improve the system performance while imperfect CSI only introduces a marginal rate loss. Finally, the analytical framework is applied to the multiuser access scenario. Numerical results demonstrate that the mixed-ADC architecture with a relatively small number of high-resolution ADCs is able to achieve a large fraction of the channel capacity of conventional architecture, while reduce the energy consumption considerably even compared with antenna selection, for both single-user and multiuser scenarios. With bandwidths on the order of a gigahertz in emerging wireless systems, high-resolution analog-to-digital convertors (ADCs) become a power consumption bottleneck. One solution is to employ low resolution one-bit ADCs. In this paper, we analyze the flat fading multiple-input multiple-output (MIMO) channel with one-bit ADCs. Channel state information is assumed to be known at both the transmitter and receiver. For the multiple-input single-output channel, we derive the exact channel capacity. For the single-input multiple-output and MIMO channel, the capacity at infinite signal-to-noise ratio (SNR) is found. We also derive upper bound at finite SNR, which is tight when the channel has full row rank. In addition, we propose an efficient method to design the input symbols to approach the capacity achieving solution. We incorporate millimeter wave channel characteristics and find the bounds on the infinite SNR capacity. The results show how the number of paths and number of receive antennas impact the capacity. The wide bandwidth and large number of antennas used in millimeter wave systems put a heavy burden on the power consumption at the receiver. In this paper, using an additive quantization noise model, the effect of analog-digital conversion (ADC) resolution and bandwidth on the achievable rate is investigated for a multi-antenna system under a receiver power constraint. Two receiver architectures, analog and digital combining, are compared in terms of performance. Results demonstrate that: (i) For both analog and digital combining, there is a maximum bandwidth beyond which the achievable rate decreases; (ii) Depending on the operating regime of the system, analog combiner may have higher rate but digital combining uses less bandwidth when only ADC power consumption is considered, (iii) digital combining may have higher rate when power consumption of all the components in the receiver front-end are taken into account.