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We propose a 28.5-GHz channel sounder that switches through all antennas of multiple dual-polarized 8 × 8 phased arrays at the transmitter and receiver and performs beamforming in postprocessing through digital weights to synthesize a sweepable beam. To our knowledge, we are the first to implement-what we refer to as-switched beamforming with phased arrays for millimeter-wave channel sounding, realized through highly stable Rubidium clocks and local oscillators coupled with precision over-the-air calibration techniques developed in house. By circumventing the time-consuming programming of analog weights that is associated with analog beamforming-what phased arrays are designed for-we can sweep a 3-D double-omnidirectional dual-polarized channel in just 1.3 ms, for real-time sounding. By in turn circumventing the coarse precision of analog weights, we can synthesize ideal beam patterns thanks to the effectively infinite precision of digital weights, enabling fine weight calibration for the nonidealities of the system hardware and fine weight tapering for sidelobe suppression. This translates to average estimation errors of 0.47° in 3-D double-directional angle, 0.48 dB in co-polarized path gain, and 0.18 ns in delay, as substantiated by field measurements.
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We reduced the parameters of the Quasi-Deterministic channel propagation model, recently adopted by the IEEE 802.11ay task group for next-generation Wi-Fi at millimeter-wave (mmWave), from measurements collected in an urban environment with our 28 GHz switched-array channel sounder. In the process-as a novel contribution-we extended the clustering of channel rays from the conventional delay and angle domains to the location domain of the receiver, over which the measurements were collected. By comparing channel realizations from the model to realizations from a leading commercial ray-tracer, we demonstrated that the model effects no detriment to accuracy while maintaining the benefit of significantly reduced complexity.
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High-gain narrow-beam antennas or beamformed antenna arrays will likely be used in millimeter-wave (mmWave) bands and 5G to mitigate the high path loss. Since many multipath components may be excluded by the narrow beam, the mmWave radio channel (consisting of the transmit antenna, the propagation channels, and the receive antenna) strongly depends on the beamwidth, orientation, and shape of the narrow beam. In this article, a procedure is proposed to measure and model the channels vs. synthetic beamwidth. Based on experimental data collected at 60 GHz in an indoor hallway/lobby scenario, the results show that the number of multipath components and the delay dispersion of the channel are significantly reduced by the narrow beams. In addition, the path loss can be decreased by more than 20 dB with an optimized beam-center orientation. The impact of the study on future 5G mmWave system design is discussed, including frequency reuse, antenna design, receiver design, equalization, and link budget.
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Millimeter-wave transceivers will feature massive phased-array antennas whose pencilbeams can be steered toward the angle of arrival of the propagation path having the maximum power, exploiting their high gain to compensate for the greater path loss witnessed in the upper spectrum. For this reason, maximum-power path-loss models, in contrast to conventional ones based on the integrated power from an omnidirectional antenna, may be more relevant. Yet to our knowledge, they do not appear in the literature save for one reference. In this paper, we compare both model types at 83.5 GHz for four indoor environments typical of hotspot deployments in line-of-sight (LOS) and non-LOS conditions up to a range of 160 m. To fit the models, we conducted a measurement campaign with over 3000 different transmitter-receiver configurations using a custom-designed channel sounder capable of extracting the delay and 3-D angle of arrival of the received paths with super-resolution. The models are supported by a detailed analysis of the propagation mechanisms of direct transmission, reflection, and knife-edge diffraction to shed light on their interplay in the E-band regime.
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Efficient design of integrated sensing and communication systems can minimize signaling overhead by reducing the size and/or rate of feedback in reporting channel state information (CSI). To minimize the signaling overhead when performing sensing operations at the transmitter, this paper proposes a procedure to reduce the feedback rate. We consider a threshold-based sensing measurement and reporting procedure, such that the CSI is transmitted only if the channel variation exceeds a threshold. However, quantifying the channel variation, determining the threshold, and recovering sensing information with a lower feedback rate are still open problems. In this paper, we first quantify the channel variation by considering several metrics including the Euclidean distance, time-reversal resonating strength, and frequency-reversal resonating strength. We then design an algorithm to adaptively select a threshold, minimizing the feedback rate, while guaranteeing sufficient sensing accuracy by reconstructing high-quality signatures of human movement. To improve sensing accuracy with irregular channel measurements, we further propose two reconstruction schemes, which can be easily employed at the transmitter in case there is no feedback available from the receiver. Finally, the sensing performance of our scheme is extensively evaluated through real and synthetic channel measurements, considering channel estimation and synchronization errors. Our results show that the amount of feedback can be reduced by 50% while maintaining good sensing performance in terms of range and velocity estimations. Moreover, in contrast to other schemes, we show that the Euclidean distance metric is better able to capture various human movements with high channel variation values.
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The design of integrated sensing and communication (ISAC) systems has drawn recent attention for its capacity to solve a number of challenges. Indeed, ISAC can enable numerous benefits, such as the sharing of spectrum resources, hardware, and software, and improving the interoperability of sensing and communication. In this article, we seek to provide a thorough investigation of ISAC. We begin by reviewing the paradigms of sensing-centric design, communication-centric design, and co-design of sensing and communication. We then explore the enabling techniques that are viable for ISAC (i.e., transmit waveform design, environment modeling, sensing source, signal processing, and data processing). We also present some emergent smart-world applications that could benefit from ISAC. Furthermore, we describe some prominent tools used to collect sensing data and publicly available sensing data sets for research and development, as well as some standardization efforts. Finally, we highlight some challenges and new areas of research in ISAC, providing a helpful reference for ISAC researchers and practitioners, as well as the broader research and industry communities.
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Tracking an object in a sequence of images can fail due to partial occlusion or clutter. Robustness to occlusion can be increased by tracking the object as a set of "parts" such that not all of these are occluded at the same time. However, successful implementation of this idea hinges upon finding a suitable set of parts. In this paper we propose a novel segmentation, specifically designed to improve robustness against occlusion in the context of tracking. The main result shows that tracking the parts resulting from this segmentation outperforms both tracking parts obtained through traditional segmentations, and tracking the entire target. Additional results include a statistical analysis of the correlation between features of a part and tracking error, and identifying a cost function that exhibits a high degree of correlation with the tracking error.