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1. High Dynamic Range mmWave Massive MU-MIMO with Householder Reflections

   V. Palhares; G. Marti; O. Castañeda; C. Studer (October 2023, Asilomar Conference on Signals, Systems, and Computers)

   All-digital massive multiuser (MU) multiple-input multiple-output (MIMO) at millimeter-wave (mmWave) frequencies is a promising technology for next-generation wireless systems. Low-resolution analog-to-digital converters (ADCs) can be utilized to reduce the power consumption of all-digital basestation (BS) designs. However, simultaneously transmitting user equipments (UEs) with vastly different BS-side receive powers either drown weak UEs in quantization noise or saturate the ADCs. To address this issue, we propose high dynamic range (HDR) MIMO, a new paradigm that enables simultaneous reception of strong and weak UEs with low-resolution ADCs. HDR MIMO combines an adaptive analog spatial transform with digital equalization: The spatial transform focuses strong UEs on a subset of ADCs in order to mitigate quantization and saturation artifacts; digital equalization is then used for data detection. We demonstrate the efficacy of HDR MIMO in a massive MU-MIMO mmWave scenario that uses Householder reflections as spatial transform. 

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2. Hybrid Jammer Mitigation for All-Digital mmWave Massive MU-MIMO

   https://doi.org/10.1109/IEEECONF53345.2021.9723334  

   Marti, Gian; Castaneda, Oscar; Jacobsson, Sven; Durisi, Giuseppe; Goldstein, Tom; Studer, Christoph (October 2021, 55th Asilomar Conference on Signals, Systems, and Computers)

   Low-resolution analog-to-digital converters (ADCs) simplify the design of millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) basestations, but increase vulnerability to jamming attacks. As a remedy, we propose HERMIT (short for Hybrid jammER MITigation), a method that combines a hardware-friendly adaptive analog transform with a corresponding digital equalizer: The analog transform removes most of the jammer’s energy prior to data conversion; the digital equalizer suppresses jammer residues while detecting the legitimate transmit data. We provide theoretical results that establish the optimal analog transform as a function of the user equipments’ and the jammer’s channels. Using simulations with mmWave channel models, we demonstrate the superiority of HERMIT compared both to purely digital jammer mitigation as well as to a recent hybrid method that mitigates jammer interference with a nonadaptive analog transform. 

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3. Beam Alignment for the Cell-Free mmWave Massive MU-MIMO Uplink

   https://doi.org/10.1109/SiPS55645.2022.9919259  

   Brun, Jannik; Palhares, Victoria; Marti, Gian; Studer, Christoph (November 2022, IEEE Workshop on Signal Processing Systems (SiPS))

   Millimeter-wave (mmWave) cell-free massive multiuser (MU) multiple-input multiple-output (MIMO) systems combine the large bandwidths available at mmWave frequencies with the improved coverage of cell-free systems. However, to combat the high path loss at mmWave frequencies, user equipments (UEs) must form beams in meaningful directions, i.e., to a nearby access point (AP). At the same time, multiple UEs should avoid transmitting to the same AP to reduce MU interference. We propose an interference-aware method for beam alignment (BA) in the cell-free mmWave massive MU-MIMO uplink. In the considered scenario, the APs perform full digital receive beamforming while the UEs perform analog transmit beamforming. We evaluate our method using realistic mmWave channels from a commercial ray-tracer, showing the superiority of the proposed method over omnidirectional transmission as well as over methods that do not take MU interference into account. 

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4. Resolution-Adaptive All-Digital Spatial Equalization for mmWave Massive MU-MIMO

   https://doi.org/10.1109/SPAWC51858.2021.9593110  

   Castaneda, Oscar; Mirfarshbafan, Seyed Hadi; Ghajari, Shahaboddin; Molnar, Alyosha; Jacobsson, Sven; Durisi, Giuseppe; Studer, Christoph (September 2021, IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

   All-digital basestation (BS) architectures for millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO), which equip each radio-frequency chain with dedicated data converters, have advantages in spectral efficiency, flexibility, and baseband-processing simplicity over hybrid analog-digital solutions. For all-digital architectures to be competitive with hybrid solutions in terms of power consumption, novel signal-processing methods and baseband architectures are necessary. In this paper, we demonstrate that adapting the resolution of the analog-to-digital converters (ADCs) and spatial equalizer of an all-digital system to the communication scenario (e.g., the number of users, modulation scheme, and propagation conditions) enables orders-of-magnitude power savings for realistic mmWave channels. For example, for a 256-BS-antenna 16-user system supporting 1 GHz bandwidth, a traditional baseline architecture designed for a 64-user worst-case scenario would consume 23 W in 28 nm CMOS for the ADC array and the spatial equalizer, whereas a resolution-adaptive architecture is able to reduce the power consumption by 6.7×. 

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5. The Impact of SAR-ADC Mismatch on Quantized Massive MU-MIMO Systems

   J. Guichemerre; C. Studer (October 2023, Conference record Asilomar Conference on Signals Systems Computers)

   Low-resolution analog-to-digital converters (ADCs) in massive multi-user (MU) multiple-input multiple-output (MIMO) wireless systems can significantly reduce the power, cost, and interconnect data rates of infrastructure basestations. Thus, recent research on the theory and algorithm sides has extensively focused on such architectures, but with idealistic quantization models. However, real-world ADCs do not behave like ideal quantizers, and are affected by fabrication mismatches. We analyze the impact of capacitor-array mismatches in successive approximation register (SAR) ADCs, which are widely used in wireless systems. We use Bussgang's decomposition to model the effects of such mismatches, and we analyze their impact on the performance of a single ADC. We then simulate a massive MU-MIMO system to demonstrate that capacitor mismatches should not be ignored, even in basestations that use low-resolution SAR ADCs. 

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