Capacity Analysis of One-Bit Quantized MIMO Systems With Transmitter Channel State Information

By Jianhua Mo, Robert W. Heath. IEEE Transactions on Signal Processing, 2014

420 citations recorded by the source corpus.

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.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/49a35aeb575ae655f76842509e1e9e83cbbec1fb

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Citations in the corpus

Modeling and Analyzing Millimeter Wave Cellular Systems (2016, background): “in the full-resolution ADCs may be a challenge at mmWave, [101] and [104] proposed using low-resolution ADCs.”
A Tutorial on Environment-Aware Communications via Channel Knowledge Map for 6G (2023, background): “As more severe quantization errors are resulted, low-resolution ADCs would require more advanced signal processing techniques to recover the performance loss.”
Channel Estimation in Broadband Millimeter Wave MIMO Systems With Few-Bit ADCs (2016, methodology): “The perfect-CSIT case was studied in our previous work [11], where constellation design methods were proposed to maximize the achievable rate.”
A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead (2016, background): “The paper [145], as an instance, presents an analysis of the spectral efﬁciency of single-carrier and OFDM transmission in massive MIMO systems that use one-bit analog-to-digital converters (ADCs), while a capacity analysis of one-bit quantized MIMO systems with transmitter CSI is reported in [146].”
Bayes-Optimal Joint Channel-and-Data Estimation for Massive MIMO With Low-Precision ADCs (2015, background): “The use of coarse quantization greatly reduces the number of effective measurements, and therefore the acquisition of CSIR becomes more challenging in the quantized MIMO systems than in its unquantized counterpart.”
Uplink Performance of Wideband Massive MIMO With One-Bit ADCs (2016, background): “Results in [5] indicate that the capacity of quantized MIMO channels grows faster with the number of receive antennas at high signal-tonoise ratio (SNR) than the rate of the linear combiners.”
Millimeter Wave Communications for Future Mobile Networks (2017, background): “However, due to the severe quantization effect of low-resolution ADCs, the capacity of this architecture is usually limited in the high SNR region [133] In addition, the nonlinearity of the quantization also imposes new challenges on the signal processing designs.”
Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems (2016, background): “One-bit ADCs do not require automatic gain control and linear amplifiers, and hence the corresponding radio frequency (RF) chains can be implemented with very low cost and power consumption [17], [18].”
An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems (2015, background): “Steering the beams is not trivial, especially when a communication link has not yet been established.”
Near Maximum-Likelihood Detector and Channel Estimator for Uplink Multiuser Massive MIMO Systems With One-Bit ADCs (2015, methodology): “Note that the classical combinatorial geometry results were also exploited in [17] to bound the high SNR”
One-Bit OFDM Receivers via Deep Learning (2018, background): “However, one-bit ADCs fundamentally have poor performance at medium and high SNRs [7], [8] or for the case of few receive antennas.”