Constrained pre-equalization accounting for multi-path fading emulated using large RC networks: applications to wireless and photonics communications

Abstract

Multi-path propagation is modelled assuming a multi-layer RC network with randomly allocated resistors and capacitors to represent the transmission medium. Due to frequency-selective attenuation, the waveforms associated with each propagation path incur path-dependent distortion. A pre-equalization procedure that takes into account the capabilities of the transmission source as well as the transmission properties of the medium is developed. The problem is cast within a Mixed Integer Linear Programming optimization framework that uses the developed nominal RC network model, with the excitation waveform customized to optimize signal fidelity from the transmitter to the receiver. The objective is to match a Gaussian pulse input accounting for frequency regions where there would be pronounced fading. Simulations are carried out with different network realizations in order to evaluate the sensitivity of the solution with respect to changes in the transmission medium mimicking the multi-path propagation. The proposed approach is of relevance where equalization techniques are difficult to implement. Applications are discussed within the context of emergent communication modalities across the EM spectrum such as light percolation as well as emergent indoor communications assuming various modulation protocols or UWB schemes as well as within the context of space division multiplexing.

Measurement and control of emergent phenomena emulated by resistive-capacitive networks, using fractional-order internal model control and external adaptive control

“…[30][31][32][33] Furthermore, fractional order circuits are finding their way in many filtering applications, 34,35 as well as in communications. 36,37 As distributed system modeling has evolved, there has also been a surge in new system identification approaches, using state variable filters 38 or using continuous order distributions, 39 and there are specific dedicated tool boxes, 40,41 e.g., FOMCON and modulation functions available to the user. 42 In order to account for emergent responses as encountered in biomedical applications 43 and the associated more complex dynamics 44 or model cyberphysical systems, 45 which incorporate signals in multiple physical domains, new system identification approaches are also under development.…”