Methodology for Multipath-Component Tracking in Millimeter-Wave Channel Modeling

Lai, Chieh-Ping; Sun, Ruoyu; Gentile, Camillo; Papazian, Peter B.; Wang, Jian; Senic, Jelena

doi:10.1109/tap.2018.2888686

Cited by 45 publications

(41 citation statements)

References 25 publications

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“…The MPC extraction framework outlined in this paper is illustrated with a data set provided by NIST [4] corresponding to propagation in a conference room of dimension 10m x 19m x 3m for 20 different TX and RX locations. The first TX and RX location is considered, and a subset of MPCs whose AoDs and AoAs in azimuth are within the range between −90 and +90 degrees (both the TX and RX ULAs facing each other) is utilized.…”

Section: Numerical Resultsmentioning

confidence: 99%

See 1 more Smart Citation

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

Sayeed¹,

Vouras

Gentile

et al. 2020

2020 IEEE Globecom Workshops (GC WKSHPS

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A framework is proposed for developing and evaluating algorithms for extracting multipath propagation components (MPCs) from measurements collected by sounders at millimeter-wave (mmW) frequencies. To focus on algorithmic performance, an idealized model is proposed for the spatial frequency response of the propagation environment measured by a sounder. The input to the sounder model is a pre-determined set of MPC parameters that serve as the "ground truth". A three-dimensional angle-delay (beamspace) representation of the measured spatial frequency response serves as a natural domain for implementing and analyzing MPC extraction algorithms. Metrics for quantifying the error in estimated MPC parameters are introduced. Initial results are presented for a greedy matching pursuit algorithm that performs a least-squares (LS) reconstruction of the MPC path gains within the iterations. The results indicate that the simple greedy-LS algorithm has the ability to extract MPCs over a large dynamic range, and suggest several avenues for further performance improvement through extensions of the greedy-LS algorithm as well as by incorporating features of other algorithms, such as SAGE and RIMAX.

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Section: Numerical Resultsmentioning

confidence: 99%

“…The MPC parameter estimation algorithms are then applied to the spatial frequency response matrix generated by the sounder model. In this work, the "ground truth" MPC parameters used as an input to the sounder model are those provided by NIST using their sophisticated sounders and algorithms [4].…”

Section: Introductionmentioning

confidence: 99%

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

Sayeed¹,

Vouras

Gentile

et al. 2020

2020 IEEE Globecom Workshops (GC WKSHPS

Self Cite

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show abstract

“…Besides the Kuhn-Munkres algorithm, the Hungarian algorithm [129] has been also widely used for the matching problem, where the main difference is that the Hungarian algorithm sets all links as the same weight during the assignment. Based on the Hungarian algorithm, a cluster tracking method for millimeter-wave channels is proposed in [135].…”

Section: Multipath Component/cluster Trackingmentioning

confidence: 99%

Artificial Intelligence Enabled Radio Propagation for Communications—Part I: Channel Characterization and Antenna-Channel Optimization

Huang

et al. 2022

IEEE Trans. Antennas Propagat.

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To provide higher data rates, as well as better coverage, cost efficiency, security, adaptability, and scalability, the 5G and beyond 5G networks are developed with various artificial intelligence techniques. In this two-part paper, we investigate the application of artificial intelligence (AI) and in particular machine learning (ML) to the study of wireless propagation channels. It firstly provides a comprehensive overview of ML for channel characterization and ML-based antenna-channel optimization in this first part, and then it gives a state-of-the-art literature review of channel scenario identification and channel modeling in Part II. Fundamental results and key concepts of ML for communication networks are presented, and widely used ML methods for channel data processing, propagation channel estimation, and characterization are analyzed and compared. A discussion of challenges and future research directions for MLenabled next generation networks of the topics covered in this part rounds off the paper.

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“…The specular paththe strongestof each cluster identified (through the algorithm in [41]) is marked by a square. The ambient scatterers that generated the specular paths were classified through inverse raytracing [42]; the scatterers classified are color-coded against the legend and are also marked in Fig. 1 Although LoS conditions were maintained throughout while recording, the limited 180° azimuth FoV at T and the limited 45° elevation FoV at both T and R acted as to block the channel paths at times.…”

Section: Path Extractionmentioning

confidence: 99%

Markov Multi-Beamtracking on 60 GHz Mobile Channel Measurements

Blandino

Senic

Gentile

et al. 2022

IEEE Open J. Veh. Technol.

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Beamforming training refers to the exhaustive scan over which the transmitter and receiver jointly steer their beams along a predefined set of double-directional angles to determine the beam pairs that coincide with the dominant propagation paths of the channel, for millimeter-wave spatial multiplexing at millimeter-wave. When mobile, training necessitates a high refresh rate to maintain connectivity and so, to reduce overhead, beamtracking algorithms exploit the spatial-temporal consistency of the channel to localize the scan around the beam pairs determined at a previous time. The algorithms' true performance, however, is still unknown since results reported to date are based on oversimplified channel models. In this paper, we propose a novel beamtracking algorithm formulated as a first-order Markov process that supports multiple beam pairs. The algorithm is evaluated through actual channel measurementsnot a channel modelrecorded with our high-precision 3D double-directional 60 GHz channel sounder. The measurement campaign, to our knowledge, is unprecedented: with 10,895 large-scale measurements, spaced 8.8 cm apart on average to emulate continuous motion, over which the mobile receiver traversed a total of 900.2 m. We demonstrate that four beam pairs can be sustained always and that eight pairs can be sustained 57% of the time.

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Methodology for Multipath-Component Tracking in Millimeter-Wave Channel Modeling

Cited by 45 publications

References 25 publications

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

A Framework for Developing Algorithms for Estimating Propagation Parameters from Measurements

Artificial Intelligence Enabled Radio Propagation for Communications—Part I: Channel Characterization and Antenna-Channel Optimization

Markov Multi-Beamtracking on 60 GHz Mobile Channel Measurements

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