A real-time experimentation platform for sub-6 GHz and millimeter-wave MIMO systems

Lacruz, Jesus O.; Ortiz, Rafael Ruiz; Widmer, Joerg

doi:10.1145/3458864.3466868

Cited by 34 publications

(25 citation statements)

References 28 publications

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“…Testbed design. Our implementation is a customization of MIMORPH [42], an open-source project for mmWave experimentation designed around the Xilinx Radio Frequency System on a Chip (RFSoC) board and Sivers' mmWave front-end [43]. Fig.…”

Section: µD Spectrogram Extractionmentioning

confidence: 99%

“…The transmitter implements a loopback memory that feeds the DACs with the I/Q symbols to be transmitted, which are loaded from an external processor. To enable AoD estimation (Section IV-B2), we implement a real-time antenna reconfiguration mechanism through General Purpose Input/Output (GPIO) pulses [42] that allows to sweep through different BPs while transmitting a packet. This feature is important when implementing the in-packet training functionality through TRN training sequences appended to communication packets [44].…”

Section: µD Spectrogram Extractionmentioning

confidence: 99%

See 1 more Smart Citation

SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems

Pegoraro

Lacruz

Rossi

et al. 2022

2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

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Wideband millimeter-wave communication systems can be extended to provide radar-like sensing capabilities on top of data communication, in a cost-effective manner. However, the development of joint communication and sensing technology is hindered by practical challenges, such as occlusions to the line-of-sight path and clock asynchrony between devices. The latter introduces time-varying timing and frequency offsets that prevent the estimation of sensing parameters and, in turn, the use of standard signal processing solutions. Existing approaches cannot be applied to commonly used phased-array receivers, as they build on stringent assumptions about the multipath environment, and are computationally complex. We present JUMP, the first system enabling practical bistatic and asynchronous joint communication and sensing, while achieving accurate target tracking and micro-Doppler extraction in realistic conditions. Our system compensates for the timing offset by exploiting the channel correlation across subsequent packets. Further, it tracks multipath reflections and eliminates frequency offsets by observing the phase of a dynamically-selected static reference path. JUMP has been implemented on a 60 GHz experimental platform, performing extensive evaluations of human motion sensing, including non-line-of-sight scenarios. In our results, JUMP attains comparable tracking performance to a fullduplex monostatic system and similar micro-Doppler quality with respect to a phase-locked bistatic receiver.

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Section: µD Spectrogram Extractionmentioning

confidence: 99%

Section: µD Spectrogram Extractionmentioning

confidence: 99%

SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems

Pegoraro

Lacruz

Rossi

et al. 2022

2022 21st ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)

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“…M-Cube [54] reverse engineers the control path of COTS 60 GHz RF frontends to build mmWave multiarray and MIMO systems with up to 8 antenna arrays. The MI-MORPH platform [19] is an open source FPGA-based multiband system that supports real time operation. Several efforts exist to instrument COTS devices for mmWave experimentation.…”

Section: Related Workmentioning

confidence: 99%

Augmenting mmWave localization accuracy through sub-6 GHz on off-the-shelf devices

Blanco

Mateo

Gringoli

et al. 2022

Proceedings of the 20th Annual International Conference on Mobile Systems, Applications and Services

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Millimeter-wave (mmWave) technology is an important element to increase the throughput and reduce latency of future wireless networks. At the same time, its high bandwidth and highly directional antennas allow for unprecedented accuracy in wireless sensing and localization applications. In this paper, we thoroughly analyze mmWave localization and find that it is either extremely accurate or has a very high error, since there is significant mmWave coverage via reflections and even through walls. As a consequence, sub-6 GHz technology can not only provide (coarse) localization where mmWave is not available, but is also critical to decide among multiple candidate antennas and APs for accurate mmWave localization.Based on these insights, we design a high-accuracy joint mmWave and sub-6 GHz location system. We enable CSI-based angle estimation and FTM-based ranging on off-the-shelf mmWave devices to implement our mechanism and carry out an extensive measurement campaign. Our system is the first to achieve 18 cm median location error with off-the-shelf devices under their normal mode of operation. We further release the location system (and in particular the CSI and FTM functionality) as well as the trace data from the measurement campaign to the research community. CCS CONCEPTS• Networks → Location based services.

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“…We evaluate the performance of the adaptation methods on real over-the-air wireless experiments. We use a recent high-performance mmWave testbed [28], featuring a high-end FPGA board with 2 GHz of bandwidth per channel and 60 GHz SIVERS antennas [29]. This platform allows to transmit the custom constellations generated by the encoder and to store the data to be either trained by the MDN, or extracted for further performance analysis.…”

Section: Autoencoder Adaptation On Real Fpga Tracesmentioning

confidence: 99%

Few-Shot Domain Adaptation For End-to-End Communication

Raghuram¹,

Zeng²,

Martí³

et al. 2021

Preprint

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The problem of domain adaptation conventionally considers the setting where a source domain has plenty of labeled data, and a target domain (with a different data distribution) has plenty of unlabeled data but none or very limited labeled data. In this paper, we address the setting where the target domain has only limited labeled data from a distribution that is expected to change frequently. We first propose a fast and light-weight method for adapting a Gaussian mixture density network (MDN) using only a small set of target domain samples. This method is well-suited for the setting where the distribution of target data changes rapidly (e.g., a wireless channel), making it challenging to collect a large number of samples and retrain. We then apply the proposed MDN adaptation method to the problem of end-of-end learning of a wireless communication autoencoder. A communication autoencoder models the encoder, decoder, and the channel using neural networks, and learns them jointly to minimize the overall decoding error rate. However, the error rate of an autoencoder trained on a particular (source) channel distribution can degrade as the channel distribution changes frequently, not allowing enough time for data collection and retraining of the autoencoder to the target channel distribution. We propose a method for adapting the autoencoder without modifying the encoder and decoder neural networks, and adapting only the MDN model of the channel. The method utilizes feature transformations at the decoder to compensate for changes in the channel distribution, and effectively present to the decoder samples close to the source distribution. Experimental evaluation on simulated datasets and real mmWave wireless channels demonstrate that the proposed methods can quickly adapt the MDN model, and improve or maintain the error rate of the autoencoder under changing channel conditions.

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A real-time experimentation platform for sub-6 GHz and millimeter-wave MIMO systems

Cited by 34 publications

References 28 publications

SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems

SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems

Augmenting mmWave localization accuracy through sub-6 GHz on off-the-shelf devices

Few-Shot Domain Adaptation For End-to-End Communication

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