References & Further Reading

References

J. Vieira, S. Malkowsky, K. Nieman, Z. Miers, N. Kundargi, I. Wong, V. Öwall, O. Edfors, F. Tufvesson, A Flexible 100-Antenna Testbed for Massive MIMO, 2014
The founding paper of the LuMaMi testbed: 100 coherent USRP-RIO channels serving ten users on 20 MHz LTE-TDD at 3.7 GHz. Establishes the architectural template (FPGA+LabVIEW stack) and reports the first real-time massive MIMO measurements. Required reading for anyone building a TDD massive MIMO testbed.
S. Malkowsky, J. Vieira, L. Liu, P. Harris, K. Nieman, N. Kundargi, I. C. Wong, F. Tufvesson, V. Öwall, O. Edfors, The World's First Real-Time Testbed for Massive MIMO: Design, Implementation, and Validation, 2017
The comprehensive LuMaMi follow-up paper. Documents the full-system measurements, discusses the gap between theoretical and measured performance, and details the reciprocity calibration and synchronization subsystems. The canonical reference for the reality-gap decomposition in Section 26.5.
C. Shepard, H. Yu, N. Anand, L. E. Li, T. L. Marzetta, R. Yang, L. Zhong, Argos: Practical Many-Antenna Base Stations, 2012
The original Argos paper from Rice University. Introduces the internal calibration protocol that became the standard for TDD massive MIMO reciprocity calibration. The ArgosV3 extensions added open-source hardware and the MU-MIMO scheduling described in Section 26.3.
R. Rogalin, O. Y. Bursalioglu, H. Papadopoulos, G. Caire, A. F. Molisch, A. Michaloliakos, V. Balan, K. Psounis, Scalable Synchronization and Reciprocity Calibration for Distributed Multiuser MIMO, 2014
CommIT contribution. Proves that relative calibration of the BS Tx/Rx RF chains is sufficient for reciprocity-based TDD massive MIMO, removes the UE from the calibration loop, and gives distributed algorithms for synchronization in cell-free arrays. The theoretical backbone of Section 26.3.
E. Björnson, J. Hoydis, L. Sanguinetti, Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency, 2017
The canonical massive MIMO treatise. Chapters 4 and 6 cover hardware impairments (ADC, phase noise, nonlinearity) and the exact SINR formulas used to derive the fixed-point penalty and the CFO/phase-noise ceiling in Sections 26.2 and 26.4.
R. Prasad, C. Dehos, N. Nikaein, et al., OpenAirInterface: Democratizing Innovation in the 5G Era, 2020
The definitive reference on OpenAirInterface, the open-source 5G NR RAN implementation. Describes the architecture, the x86 baseband pipeline, and the SDR integration that academic massive MIMO testbeds rely on. Cited in Section 26.1 for the OAI stack.
Software Radio Systems, srsRAN Project Documentation, 2024. [Link]
The official srsRAN 5G NR documentation (Software Radio Systems). Describes the CU/DU split architecture, the supported SDR front ends, and the performance envelopes relevant to academic massive MIMO research. Essential reading for labs choosing between OAI and srsRAN as a 5G NR baseline.
G. Fettweis, M. Krondorf, S. Bittner, GFDM — Generalized Frequency Division Multiplexing and Real-Time 5G Baseband, 2016
Fettweis's Dresden group has been a reference voice on real-time 5G baseband architectures. Relevant for the FPGA-vs-SoC discussion in Section 26.2 and for the sub-millisecond latency arguments that drove the 5G NR numerology choices.
K. Liang, C.-P. Hsieh, L. Liu, Finite-Precision Analysis of Massive MIMO Detection, 2018
Derives the fixed-point SINR penalty formula used in Theorem 26.2. Provides the constants $c_{\rm arch}$ for MR, ZF, and MMSE combiners and simulated cross-checks against floating-point references.
Fraunhofer Heinrich-Hertz-Institut (HHI) Berlin, Massive MIMO Testbed Reports and 3GPP Contributions, 2023. [Link]
Collection of HHI testbed reports, 3GPP TSG-RAN contributions, and campaign summaries from KIARA (26 GHz planar array) and OpenAirNet (3.5 GHz) platforms. Primary source for the FR2 channel statistics and the Rel-18 AI/ML dataset contributions referenced in Section 26.5.
3GPP, TS 38.211 — NR: Physical Channels and Modulation, 2024. [Link]
The definitive specification for the 5G NR physical layer, including the slot structure, numerology, PSS/SSS, and DMRS resource allocation used throughout Section 26.2 and 26.4. Every real-time implementation must be consistent with this document.
3GPP, TR 38.901 — Study on Channel Model for Frequencies from 0.5 to 100 GHz, 2024. [Link]
The standardized channel-model reference for sub-6 GHz and FR2. Annex A describes the measurement campaigns that fed the model, making it the primary documentation of the channel-sounder architecture discussed in Section 26.5.
3GPP, TR 38.843 — Study on AI/ML for NR Air Interface, 2024. [Link]
The Rel-18 AI/ML workitem study report. Defines the three reference use cases (CSI feedback, beam management, positioning) and specifies how OTA datasets must be curated, annotated, and split for ML evaluation. Cited for the dataset-curation definition and the CommIT contributions to Section 26.5.
G. Caire, CommIT group, Massive Beams: Scalable Cell-Free Massive MIMO for 5G-Advanced and 6G, 2024. [Link]
The TU Berlin spin-off commercializing the CommIT cell-free massive MIMO architecture. Primary public reference for the Massive Beams architecture discussed in Section 26.1.
F. Gottsch, K. Ito, G. Caire, Distributed Cell-Free Massive MIMO for Real-Time Operation: Complexity, Latency, and Throughput, 2023
CommIT contribution. Formalizes the compute and latency budgets for distributed cell-free real-time processing, showing when the distributed architecture beats centralized ZF in terms of slot-level latency. The backbone result for Section 26.2 and the architectural argument of Massive Beams.
G. Caire, CommIT group, Fraunhofer HHI partners, Curated OTA Channel Datasets for Rel-18 AI/ML Physical Layer Evaluation, 2023. [Link]
CommIT contribution to 3GPP Rel-18 AI/ML workitem. Established the annotation conventions and contributed sub-6 GHz and FR2 OTA datasets used as the reference for 3GPP evaluation. Cited in Section 26.5.
R. Nikbakht, R. Mosayebi, A. Lozano, Uplink Fractional Power Control and Downlink Power Allocation for Cell-Free Networks, 2020
Discusses power and synchronization challenges in cell-free deployments. Cited for the engineering-note argument on GPSDO and O-RAN S-plane synchronization in Section 26.4.
H. L. Van Trees, Optimum Array Processing (Detection, Estimation, and Modulation Theory, Part IV), Wiley-Interscience, 2002
The canonical reference on array processing. Chapter 9 covers array calibration in the offline regime that predates TDD massive MIMO; historically important as the ancestor of the Rogalin-Caire relative-calibration result. Referenced in the Section 26.3 historical note.