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1. Joint Channel Estimation and Localization for Cooperative Millimeter Wave Systems

   https://doi.org/10.1109/SPAWC48557.2020.9154215  

   Yang, Xi; Wen, Chao-Kai; Jin, Shi; Swindlehurst, A. Lee; Zhang, Jing (May 2020, Proc. 2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

   null (Ed.)

   Localization is one of the most interesting topics related to the promising millimeter wave (mmWave) technology. In this paper, we investigate joint channel estimation and localization for a cooperative mmWave system with several receivers. Due to the strong line-of-sight path common to mmWave channels, one can localize the position of the user by exploiting the signal's angle-of-arrival (AoA). Leveraging a variational Bayesian approach, we obtain soft information about the AoA for each receiver. We then use the soft AoA information and geometrical constraints to localize the position of the user and further improve the channel estimation performance. Numerical results show that the proposed algorithm has centimeter-level localization accuracy for an outdoor scene. In addition, the proposed algorithm provides 1-3 dB of gain for channel estimation by exploiting the correlation among the receiver channels depending on the availability of prior information about the path loss model. 

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2. RFSoC-FPGA Realization of a Code-Multiplexed Digital Receiver (CMDR) Using 1-ADC/Quad-Channel

   https://doi.org/10.1109/JMW.2023.3320712  

   Ullah, Kefayet; Venkatakrishnan, Satheesh Bojja; Volakis, John L (January 2024, IEEE Journal of Microwaves)

   A 4-channel code-multiplexed digital receiver is presented for multiple-input-multiple-output (MIMO) applications targeting 5G millimeter-wave (mm-Wave) communications. The receiver employs a code-multiplexing (CM) topology where multiple channels are encoded with unique orthogonal Walsh­ Hadamard codes and multiplexed into a single-channel for digitization. This approach overcomes the bottleneck of hardware complexity, cost, and power consumption in traditional multiplexing topologies by employing a single wideband analog-to-digital converter (ADC) to serve several channels. The article presents an end-to-end testbed to demonstrate the effectiveness of the proposed Code-Multiplexed Digital Receiver (CMDR) that consists of l ) ultrawideband (UWB) tightly-coupled dipole array (TCDA), 2) a custom-designed encoder circuit board (ECB), and 3) a Radio-Frequency System-on-Chip (RFSoC) field­ programmable gate array (FPGA) for encoding and decoding. The code sequences were generated at a maximum clock frequency of 400 MHz. Extensive experimental measurements were performed and test results were validated using performance metrics such as normalized mean square error (NMSE) and adjacent channel interference (ACI). Test results showed ACI of >20 dB, NMSE = -24.592 dB and little or no degradation in signal-to-noise ratio (SNR). To the best of our knowledge, this is the highest clock frequency and ACI value for hardware validation of channel multiplexing scheme reported in the literature. 

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3. Bayesian Iterative Channel Estimation and Turbo Equalization for Multiple-Input–Multiple-Output Underwater Acoustic Communications

   https://doi.org/10.1109/JOE.2019.2956299  

   Qin, Xiangzhao; Qu, Fengzhong; Zheng, Yahong Rosa (July 2020, IEEE Journal of Oceanic Engineering)

   This article investigates a robust receiver scheme for a single carrier, multiple-input–multiple-output (MIMO) underwater acoustic (UWA) communications, which uses the sparse Bayesian learning algorithm for iterative channel estimation embedded in Turbo equalization (TEQ). We derive a block-wise sparse Bayesian learning framework modeling the spatial correlation of the MIMO UWA channels, where a more robust expectation–maximization algorithm is proposed for updating the joint estimates of channel impulse response, residual noise, and channel covariance matrix. By exploiting the spatially correlated sparsity of MIMO UWA channels and the second-order a priori channel statistics from the training sequence, the proposed Bayesian channel estimator enjoys not only relatively low complexity but also more stable control of the hyperparameters that determine the channel sparsity and recovery accuracy. Moreover, this article proposes a low complexity space-time soft decision feedback equalizer (ST-SDFE) with successive soft interference cancellation. Evaluated by the undersea 2008 Surface Processes and Acoustic Communications Experiment, the improved sparse Bayesian learning channel estimation algorithm outperforms the conventional Bayesian algorithms in terms of the robustness and complexity, while enjoying better estimation accuracy than the orthogonal matching pursuit and the improved proportionate normalized least mean squares algorithms. We have also verified that the proposed ST-SDFE TEQ significantly outperforms the low-complexity minimum mean square error TEQ in terms of the bit error rate and error propagation. 

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4. A hybrid observer for linear systems under delayed sporadic measurements

   https://doi.org/10.1002/rnc.7213  

   Guarro, Marcello; Ferrante, Francesco; Sanfelice, Ricardo G (July 2024, International Journal of Robust and Nonlinear Control)

   This paper proposes a hybrid observer for state estimation over a network. The network provides delayed measurements of the output of the plant at time instants that are not necessarily periodic and are accompanied by timestamps provided by a clock that synchronizes with the clock of the observer in finite time. The proposed observer, along with the plant and communication network, are modeled by a hybrid dynamical system that has two timers, a logic variable, and two memory states to capture the mechanisms involved in the events associated with sampling and arrival of information, as well as the logic in the estimation algorithm. The hybrid model also includes a generic clock synchronization scheme to cope with a mismatch between the clocks at the plant and the observer. Convergence properties of the estimation error of the system are shown analytically and supported by numerical examples. 

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5. Channel Feedback Based on AoD-Adaptive Subspace Codebook in FDD Massive MIMO Systems

   https://doi.org/10.1109/TCOMM.2018.2849755  

   Shen, Wenqian; Dai, Linglong; Shim, Byonghyo; Wang, Zhaocheng; Heath, Robert W. (January 2018, IEEE Transactions on Communications)

   Channel feedback is essential in frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems. Unfortunately, prior work on multiuser MIMO has shown that the feedback overhead scales linearly with the number of base station (BS) antennas, which is large in massive MIMO systems. To reduce the feedback overhead, we propose an angle-of-departure (AoD) adaptive subspace codebook for channel feedback in FDD massive MIMO systems. Our key insight is to leverage the observation that path AoDs vary more slowly than the path gains. Within the angle coherence time, by utilizing the constant AoD information, the proposed AoDadaptive subspace codebook is able to quantize the channel vector in a more accurate way. From the performance analysis, we show that the feedback overhead of the proposed codebook only scales linearly with a small number of dominant (path) AoDs instead of the large number of BS antennas. Moreover, we compare the proposed quantized feedback technique using the AoD-adaptive subspace codebook with a comparable analog feedback method. Extensive simulations show that the proposed AoD-adaptive subspace codebook achieves good channel feedback quality, while requiring low overhead. 

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