Orthogonal Data Aggregation with Jacobi Pulse Sequences

In this paper a new method for orthogonal data aggregation using Jacobi polynomial pulse sequences is proposed. First, the theory and construction of the sequences is presented. In proof-of-concept simulations we electrically aggregated 4 separate signals with 2 data levels and a data rate of 2 Gbit/s into a single 8 Gbit/s data signal with 16 data levels. Utilizing the Jacobi Polynomial pulse sequences a Q factor improvement of around 10 dB or a bandwidth reduction for the aggregated data signal by a factor of 1.5 could be achieved.

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Published
2025-03-17
DOI
https://doi.org/10.23919/gemic64734.2025.10979086
Primary Topic
Advanced Statistical Methods and Models
Type
article
Field-Weighted Citation Impact
0.00

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article

Orthogonal Data Aggregation with Jacobi Pulse Sequences

Janosch Meier, Paulomi Mandal, Girish Krishnan, Thomas Schneider
Advanced Statistical Methods and Models
article

Orthogonal Data Aggregation with Jacobi Pulse Sequences

Janosch Meier, Paulomi Mandal, Girish Krishnan, Thomas Schneider
article en

Abstract

In this paper a new method for orthogonal data aggregation using Jacobi polynomial pulse sequences is proposed. First, the theory and construction of the sequences is presented. In proof-of-concept simulations we electrically aggregated 4 separate signals with 2 data levels and a data rate of 2 Gbit/s into a single 8 Gbit/s data signal with 16 data levels. Utilizing the Jacobi Polynomial pulse sequences a Q factor improvement of around 10 dB or a bandwidth reduction for the aggregated data signal by a factor of 1.5 could be achieved.

Technische Universität Braunschweig (DE)
Deutsche Forschungsgemeinschaft
Openalex Percentile: Top 90%
Advanced Statistical Methods and Models
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