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1. Online Millimeter Wave Phased Array Calibration Based on Channel Estimation

   https://doi.org/10.1109/VTS.2019.8758627  

   Moon, Thomas; Gaun, Junfeng; Hassanieh, Haitham (April 2019, 2019 IEEE 37th VLSI Test Symposium (VTS))

   This paper proposes a new over-the-air (OTA) calibration method for millimeter wave phased arrays. Our method leverages the channel estimation process which is a fundamental part of any wireless communication system. By performing the channel estimation while changing the phase of an antenna element, the phase response of the element can be estimated. The relative phase of the phased array can also be obtained by collecting all the estimated phase responses with a shared reference state. Hence, the phase mismatches of the phased array can be resolved. Unlike prior work, our calibration method embraces all the array components such as power-divider, phase shifter, amplifier and antenna and thus, spans the full chain. By overriding channel estimation, our proposed technique does not require any additional circuits for calibration. Furthermore, the calibration can be performed online without the need to pause the communication. We tested our method on an eight element phased array at 24GHz which we designed and fabricated in PCB for verification. The measured beam patterns prove the viability of our proposed method. 

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2. SideSense: Robust Physiological Motion Detection via mmWave Joint Communication and Sensing Systems With Multiple Beams

   https://doi.org/10.1109/TMTT.2025.3589906  

   Ishrak, Mohammad Shadman; Sameera, Jannatun Noor; Yang, Alvin; Pan, Yanjun; Zheng, Yao; Borić-Lubecke, Olga; Lubecke, Victor M (January 2025, IEEE Transactions on Microwave Theory and Techniques)

   A 28-GHz multibeam joint communication and sensing system called SideSense is presented, in which a line-of-sight (LoS) beam is used to maintain reliable communication, while other sensing beams are used to enhance physiological motion detection. SideSense decodes the motion frequency and shape from the channel state information (CSI) by first tuning the gain ratio and phase differences between the LoS communication beam and non-LoS (NLoS) beam to maximize the sensing signal-to-noise ratio (SSNR) without significantly degrading the communication channel capacity (CCC). Analytical results based on a bistatic model are presented to show a gain ratio of around 1 and a phase difference of 90° or 270°, which are ideal for optimizing both SSNR and CCC. Experiments based on an array of phased array (APA) beamformers and orthogonal frequency-division multiplexing (OFDM) waveforms with phantom and human subjects are presented to validate the performance of SideSense. Results show that SideSense can improve SSNR by 84% while reducing CCC by 35%, an acceptable decrease within the normal operational parameters of a millimeter-wave (mmWave) communication system, which would not trigger a link reestablishment procedure, e.g., communication beam realignment. 

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3. Channel Estimation with One-Bit Transceivers in a Rayleigh Environment

   https://doi.org/10.1109/GCWkshps45667.2019.9024647  

   Gao, Kang; Laneman, J. Nicholas; Estes, N. J.; Chisum, Jonathan; Hochwald, Bertrand (December 2019, 2019 IEEE Globecom Workshops (GC Wkshps))

   One-bit transceivers with strongly nonlinear characteristics are being considered for wireless communication because of their low cost and low power consumption. Although each such transceiver can support only a low data rate, multiple such transceivers can be used to obtain an aggregate high data rate. An important part of many communication systems is the process of channel estimation, which is particularly challenging when the estimation process uses these transceivers. The standard analysis of estimation mean-square error versus training length that is available for linear transceivers does not apply with the nonlinearities inherent in one-bit transceivers. We analyze the training requirements in a large- scale system and show that the optimal number of training symbols strongly depends on the number of receivers, and the optimal number of training symbols can be significantly smaller than the number of transmitters. These results contrast sharply with classical results obtained with linear transceivers. 

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4. Tight Approximation of Achievable Rates in RIS-Based Multi-User MIMO Systems Under Channel Estimation Constraints

   https://doi.org/10.1109/OJCOMS.2025.3539229  

   Farghaly, Samar I; Ismail, Mohamed I; Fouda, Mostafa M; Alwakeel, Ahmed S (February 2025, IEEE Open Journal of the Communications Society)

   The rapid and low-power configuration capabilities of Reconfigurable Intelligent Surfaces (RISs) have made them an attractive option for future wireless networks in terms of energy efficiency. They have the ability to greatly increase connection and facilitate low-latency communications. However, because RIS-based systems often have a large number of RIS unit elements and unique hardware constraints, accurate and low-overhead channel estimate remains a crucial challenge. In this study, we offer a channel estimation framework and concentrate on the uplink of a multi-user multiple-input multiple-output (MU-MIMO) communication system driven by RIS. Our primary goal is to enhance the achievable rate and system capacity. We derive a closed-form deterministic expression for the uplink achievable rate under practical scenarios where channel state information (CSI) is not directly known and must be estimated. In contrast to previous studies assuming perfect CSI, our approach incorporates the channel estimation process, leading to a more realistic performance assessment. Extensive simulations validate the tightness of our derived expression compared to the actual achievable rate across various system parameters (with discrepancies typically within 2-5%). The results highlight the significant impact of RIS on system performance enhancement, even with imperfect CSI. Our findings provide crucial insights into the deployment and optimization of RIS-assisted multi-user wireless networks, underscoring their potential for substantial improvements in rate and capacity. 

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5. An Evaluation Platform for Channel Estimation in MIMO Systems

   https://doi.org/10.1109/NAECON58068.2023.10365882  

   Mercado-Perez, Dalyana; Kumar, Venkataramani; Ye, Feng; Hu, Rose Qingyang; Qian, Yi (August 2023, NAECON 2023 - IEEE National Aerospace and Electronics Conference)

   Multiple-input multiple-outputs (MIMO) systems are integral to the implementation of the current fifth-generation (5G) and beyond wireless networks. Accurate channel state information (CSI) is imperative to a MIMO system for its optimal performance. In this work, we develop an end-to-end software evaluation platform for the channel estimation process in a MIMO system. With this platform, different channel estimation and reconstruction processes, as well as precoding methods can be implemented and evaluated. Channel reconstruction error and transmission bit error rate are chosen metrics in the current implementation. Direct channel estimation with the least square method, and CSI feedback methods with compressive sensing and deep-learning approaches are tested to demonstrate the evaluation platform 

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