Defense Advanced Research Projects Agency (DARPA)’s Post

High signal directivity and sensitivity to blockages make the mmWave base station (BS) discovery a challenging problem in emerging mobile networks. Existing solutions include methods that rely on the exhaustive periodic beam sweeping and thus have high latency and low mmWave cell discovery rate Joint methods where macro-BS determines the mmWave cell for a given user equipment based solely on spatial proximity are prone to Non Line of Sight conditions. Recent AI-based solutions address the above problems but rely on impractical assumption of having complete minimization of drive test (MDT) reports traces at the assisting macro BSs in all areas of interest. Our recent paper published in IEEE Transactions on Vehicular Technology is the first to present an AI-based framework (AISMO) that can utilize very sparse MDT style data to enable NLoS-aware low latency mmWave cell discovery. To evaluate AISMO’s performance in a realistic 5G deployment scenario, we also present a case study where AISMO is used to enable E-UTRAN New-Radio Dual-Connectivity (EN-DC) between macro BS and mmWave small cells. https://lnkd.in/gHq-7Ha3

We are delighted to share that 🎉 our recent paper has been accepted for presentation at the upcoming IEEE MeditCom24 conference, 📝 which will be held in Madrid, Spain, from July 8th to 11th, 2024. The work is authored by myself and Prof. Daniele Tarchi. 🤝 Our research addresses the problem of dependency-aware IoV multitask service offloading over joint air-ground edge networks. 💡 We have proposed a V2X-based computation and communication-efficient multitask offloading approach with several benefits. We are excited about presenting our findings and engaging in discussions about the future of IoV research. 🚗🔬 Alma Mater Studiorum – Università di Bologna CNIT - Consorzio Nazionale Interuniversitario per le Telecomunicazioni #MeditCom24 #IoV #EdgeComputing #V2X

In this interview from #SfN23, Jinny Kim discusses her work developing and using advanced technologies to map synaptic connectivity #mGRASP https://lnkd.in/en9yVn4a

This paper considers the problem of beam alignment in a #cell-#free #massive #MIMO deployment with multiple access points (APs) and multiple user equipments (UEs) simultaneously operating in the same millimeter wave frequency band. Assuming the availability of a control channel at sub-6 GHz frequencies, a protocol is developed that permits estimating, for each UE, the strongest propagation path from each of the surrounding APs, and to perform user-centric association between the UEs and the APs. Estimation of the strongest paths from nearby APs is realized at the UE in a one-phase procedure, during which all the APs simultaneously transmit on pseudo-randomly selected channels with pseudo-random transmit beamformers. ---- Stefano Buzzi, Carmen D'Andrea, Maria Fresia More details can be found at this link: https://lnkd.in/gH-ckMt2

🚀 News from the 6G Frontier! 🚀 We are happy to announce our latest publication in the IEEE Transactions on Wireless Communications! Our paper, "Integrated Sensing and Communications with MIMO-OTFS: ISI/ICI Exploitation and Delay-Doppler Multiplexing," co-authored by Musa Furkan Keskin, Carina Marcus, Olof Eriksson, Alex Alvarado, Joerg Widmer, and Henk Wymeersch, dives deep into the heart of 6G. 🌐 What's Inside? This paper explores integrated sensing and communication (ISAC) utilizing MIMO-OTFS waveforms. Our focus? Enhancing multi-target detection in monostatic sensing scenarios. By optimizing MIMO delay-Doppler multiplexing precoding, we pave the way for advanced searching/discovery and tracking capabilities. 🔧 Breaking New Ground We developed a versatile signal model that precisely captures continuous-valued delays, Dopplers, and angles. Moreover, we tackled the challenges posed by inter-symbol interference (ISI) and inter-carrier interference (ICI). Not just overcoming these hurdles, but turning them to our advantage to boost detection and estimation performance. 💡 Key Takeaways Our extensive results reveal the delicate balance between monostatic sensing and communication, showcasing the profound impact of our designs and algorithms. 🔗 Dive Deeper Check out our paper here and discover how we're pushing the boundaries of 6G technology: https://lnkd.in/d8qA8JBw #6G #WirelessCommunications #MIMO #OTFS #ISAC

This work provides a unified framework for cellular networks that use #full-#duplex massive MIMO with #low-#resolution #ADCs and #DACs. The authors develop an accurate model that accounts for various network irregularities and imperfections, including self-interference from full-duplex systems and quantization error from low-bit converters. They derive the signal-to-quantization-plus-interference-plus-noise ratio (#SQINR) under pilot contamination, LMMSE channel estimation and channel hardening. ---- Elyes Balti More details can be found at this link: https://lnkd.in/g4raWCfa

Glad to share that our research work has been published in IEEE Transactions on Network and Service Management (Impact Factor- 5.3). Thanks to my supervisor, Prof. shankar prakriya, for guidance and suggestions. The motivation for this work is to make underlay networks more spectrally efficient with the use of the NOMA principles for 5G and beyond networks.  Please have a look at what we have done. "Performance of NOMA based Spectrally-Efficient Uplink Underlay Multiuser Networks with Imperfect SIC" in IEEE TNSM. #iitdelhi #research #wirelesscommunications #noma #communications #5G #cognitive_radio #uplink #multiuser #sic https://lnkd.in/dqzmgtE8

Millimeter wave (#mmWave) radars are great at #sensing their surroundings, and can easily detect obstacles, #human #body motion, as well as gestures. Yet, they have limited #coverage and require line of sight of the subject to be sensed. Thus, one would naturally think of covering large and complex spaces with multiple radars. This solves the coverage problem, but requires cumbersome human intervention to calibrate the #radar #network. In our new paper "ORACLE: Occlusion-Resilient and Self-Calibrating mmWave Radar Network for People Tracking," we explain how to solve this issue. We discuss how to automatically exploit the trajectories of people moving freely in the radars’ common fields of view, #fusing the tracking information to obtain a unified tracking among all radars. Radars self-localize very accurately (12cm/0.03° median errors on location and orientation) and track targets also very accurately (no more than 23 cm in our experiments with #multiple #targets). It was a great collaboration between the #MANTA lab @ UniTrento DISI (https://lnkd.in/gusVqC4U with myself and Anish Shastri) and Marco Canil, Jacopo Pegoraro, and Michele Rossi from Dip. di Ingegneria dell'Informazione (DEI) - Dept. Information Engineering / UniPD. Check our early access paper! 👉 https://lnkd.in/dTGSQww5 (Also, thanks a lot to Laura Canil for the great graphical abstract!) [This work received support from the European Commission’s Horizon 2020 Framework Programme under the Marie Skłodowska-Curie Action MINTS (MINTS European Training Network), GA no. 861222.]

A very interesting project I had the chance to prepare the graphical abstract for! Check out the paper to know more about how to obtain unified tracking by fusing the tracking information from different radars.

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