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1. Optimality of the Discrete Fourier Transform for Beamspace Massive MU-MIMO Communication

   https://doi.org/10.1109/ISIT45174.2021.9518255  

   Taner, Sueda ; Studer, Christoph ( July 2021 , IEEE International Symposium on Information Theory)

   null (Ed.)

   Beamspace processing is an emerging technique to reduce baseband complexity in massive multiuser (MU) multipleinput multiple-output (MIMO) communication systems operating at millimeter-wave (mmWave) and terahertz frequencies. The high directionality of wave propagation at such high frequencies ensures that only a small number of transmission paths exist between user equipments and basestation (BS). In order to resolve the sparse nature of wave propagation, beamspace processing traditionally computes a spatial discrete Fourier transform (DFT) across a uniform linear antenna array at the BS where each DFT output is associated with a specific beam. In this paper, we study optimality conditions of the DFT for sparsity-based beamspace processing with idealistic mmWave channel models and realistic channels. To this end, we propose two algorithms that learn unitary beamspace transforms using an l4-norm-based sparsity measure, and we investigate their optimality theoretically and via simulations. 

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2. Blind SNR Estimation and Nonparametric Channel Denoising in Multi-Antenna mmWave Systems

   https://doi.org/10.1109/ICC42927.2021.9500387  

   Gallyas-Sanhueza, Alexandra ; Studer, Christoph ( June 2021 , IEEE International Conference on Communications)

   We propose blind estimators for the average noise power, receive signal power, signal-to-noise ratio (SNR), and mean-square error (MSE), suitable for multi-antenna millimeter wave (mmWave) wireless systems. The proposed estimators can be computed at low complexity and solely rely on beamspace sparsity, i.e., the fact that only a small number of dominant propagation paths exist in typical mmWave channels. Our estimators can be used (i) to quickly track some of the key quantities in multi-antenna mmWave systems while avoiding additional pilot overhead and (ii) to design efficient nonparametric algorithms that require such quantities. We provide a theoretical analysis of the proposed estimators, and we demonstrate their efficacy via synthetic experiments and using a nonparametric channel-vector denoising task with realistic multi-antenna mmWave channels. 

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3. A Resolution-Adaptive 8 mm 2 9.98 Gb/s 39.7 pJ/b 32-Antenna All-Digital Spatial Equalizer for mmWave Massive MU-MIMO in 65nm CMOS

   https://doi.org/10.1109/ESSCIRC53450.2021.9567843  

   Castaneda, Oscar ; Boynton, Zachariah ; Mirfarshbafan, Seyed Hadi ; Huang, Shimin ; Ye, Jamie C. ; Molnar, Alyosha ; Studer, Christoph ( September 2021 , IEEE 47th European Solid State Circuits Conference (ESSCIRC))

   All-digital millimeter-wave (mmWave) massive multi-user multiple-input multiple-output (MU-MIMO) receivers enable extreme data rates but require high power consumption. In order to reduce power consumption, this paper presents the first resolution-adaptive all-digital receiver ASIC that is able to adjust the resolution of the data-converters and baseband-processing engine to the instantaneous communication scenario. The scalable 32-antenna, 65 nm CMOS receiver occupies a total area of 8 mm 2 and integrates analog-to-digital converters (ADCs) with programmable gain and resolution, beamspace channel estimation, and a resolution-adaptive processing-in-memory spatial equalizer. With 6-bit ADC samples and a 4-bit spatial equalizer, our ASIC achieves a throughput of 9.98 Gb/s while being at least 2× more energy-efficient than state-of-the-art designs. 

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4. Sparsity-Adaptive Beamspace Channel Estimation for 1-Bit mmWave Massive MIMO Systems

   https://doi.org/10.1109/SPAWC48557.2020.9154213  

   Gallyas-Sanhueza, Alexandra ; Mirfarshbafan, Seyed Hadi ; Ghods, Ramina ; Studer, Christoph ( May 2020 , IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

   null (Ed.)

   We propose sparsity-adaptive beamspace channel estimation algorithms that improve accuracy for 1-bit data converters in all-digital millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) basestations. Our algorithms include a tuning stage based on Stein's unbiased risk estimate (SURE) that automatically selects optimal denoising parameters depending on the instantaneous channel conditions. Simulation results with line-of-sight (LoS) and non-LoS mmWave massive MIMO channel models show that our algorithms improve channel estimation accuracy with 1-bit measurements in a computationally-efficient manner. 

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5. Millimeter Wave and Sub-Terahertz Spatial Statistical Channel Model for an Indoor Office Building

   Shihao Ju, Yunchou Xing ( December 2021 , IEEE journal on selected areas in communications)

   Abstract—Millimeter-wave (mmWave) and sub-Terahertz (THz) frequencies are expected to play a vital role in 6G wireless systems and beyond due to the vast available bandwidth of many tens of GHz. This paper presents an indoor 3-D spatial statistical channel model for mmWave and sub-THz frequencies based on extensive radio propagation measurements at 28 and 140 GHz conducted in an indoor office environment from 2014 to 2020. Omnidirectional and directional path loss models and channel statistics such as the number of time clusters, cluster delays, and cluster powers were derived from over 15,000 measured power delay profiles. The resulting channel statistics show that the number of time clusters follows a Poisson distribution and the number of subpaths within each cluster follows a composite exponential distribution for both LOS and NLOS environments at 28 and 140 GHz. This paper proposes a unified indoor statistical channel model for mmWave and sub-Terahertz frequencies following the mathematical framework of the previous outdoor NYUSIM channel models. A corresponding indoor channel simulator is developed, which can recreate 3-D omnidirectional, directional, and multiple input multiple output (MIMO) channels for arbitrary mmWave and sub-THz carrier frequency up to 150 GHz, signal bandwidth, and antenna beamwidth. The presented statistical channel model and simulator will guide future air-interface, beamforming, and transceiver designs for 6G and beyond. Index Terms—Millimeter-wave, terahertz, radio propagation, indoor office scenario, channel measurement, channel modeling, channel simulation, NYUSIM, 28 GHz, 140 GHz, 142 GHz, 5G, 6G. 

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