Signal design for wideband multi-functional wireless systems
File(s)
Author(s)
Zhang, Yumeng
Type
Thesis
Abstract
Wideband signals have found advantages in various wireless systems, i.e., communications, sensing and wireless power transfer (WPT), as well as their integration. This thesis explores the applications of wideband signals, by accounting for realistic system properties that are often overlooked in the existing literature, and by pushing the integration further considering a multi-functional sensing, communications and powering system to achieve higher spectrum efficiency.
First, we investigate the optimal wideband signal in WPT, adaptive to the channel state information and accounting for both the high power amplifier (HPA)'s non-linearity at the transmitter and the energy harvester (EH)’s non-linearity at the receiver. The consequential optimal wideband signal achieves the highest end-to-end power harvesting efficiency in WPT, which addresses previous literature's negligence on either HPA's or EH's non-linearities.
Second, we progress to wideband signal design for dual-function radar and communications, with a particular focus on orthogonal frequency division multiplexing (OFDM) signals. To visualize the random-deterministic trade-off between communication and radar functionalities, we design the input distribution of OFDM symbols to optimize the radar performance constrained by communication achievable rates -- defined as the DFRC performance region. The signal design also accounts for the practical OFDM on-grid range-velocity radar estimator, whose feature has been dismissed for waveform design. The proposed input distribution effectively enlarges the performance region of DFRC, compared with existing literature.
Third, we propose an integrated sensing, communication and powering (ISCAP) system, where an OFDM signal is designed and transmitted to power a sensor, communicate with an information decoder and sense a point target simultaneously. We optimize the OFDM signal's input distribution, whose performance significantly surpasses the corresponding coexisting scenario where independent signals serve their respective functionalities in a power-splitting way.
First, we investigate the optimal wideband signal in WPT, adaptive to the channel state information and accounting for both the high power amplifier (HPA)'s non-linearity at the transmitter and the energy harvester (EH)’s non-linearity at the receiver. The consequential optimal wideband signal achieves the highest end-to-end power harvesting efficiency in WPT, which addresses previous literature's negligence on either HPA's or EH's non-linearities.
Second, we progress to wideband signal design for dual-function radar and communications, with a particular focus on orthogonal frequency division multiplexing (OFDM) signals. To visualize the random-deterministic trade-off between communication and radar functionalities, we design the input distribution of OFDM symbols to optimize the radar performance constrained by communication achievable rates -- defined as the DFRC performance region. The signal design also accounts for the practical OFDM on-grid range-velocity radar estimator, whose feature has been dismissed for waveform design. The proposed input distribution effectively enlarges the performance region of DFRC, compared with existing literature.
Third, we propose an integrated sensing, communication and powering (ISCAP) system, where an OFDM signal is designed and transmitted to power a sensor, communicate with an information decoder and sense a point target simultaneously. We optimize the OFDM signal's input distribution, whose performance significantly surpasses the corresponding coexisting scenario where independent signals serve their respective functionalities in a power-splitting way.
Version
Open Access
Date Issued
2024-05-31
Date Awarded
01/09/2024
License URL
Advisor
Clerckx, Bruno
Publisher Department
Electrical and Electronic Engineering
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)