Dynamic power allocation and discrete wavelet transform techniques in 5G wireless sensor network systems with energy harvesting

Abstract

Energy harvesting wireless networks are one of the most researched topics in this decade. With a radio frequency (RF) energy harvester (EH) embedded, the sensors can operate for extended periods. Thus, providing sustainable solutions for managing massive numbers of sensor nodes (SN). There are different scheduling methods for information decoding (ID) and energy harvesting (EH) in the literature. These scheduling techniques can be classified into time switching (TS) and power splitting (PS). TS alternates between EH and ID on a temporal basis, receiving data just half of the time. In contrast, PS splits the received signal in theory between ID and EH circuitries without regard for the power requirement differences of the two circuitries. This thesis aims to develop an energy harvesting system with a dynamic power allocation transmitter and dynamic power splitting receiver between information decoding and energy harvesting circuitries for WSN to increase the energy harvester output. The presented receiver architecture integrates input signals from several RF sources and divides them between the EH and ID circuits. In addition, by moving the ID load into a separate circuit, the split design enhances the harvestable power at the RF energy harvester. DPA-SWIPT is implemented at the transmitter, where the ES is transmitted using an unmodulated high-power CW signal centred on the carrier frequency, while the IS is transmitted using a low-power signal around the carrier frequency. In TS and PS, the ES is conveyed on a modulated wave, resulting in increased interference with external networks. In contrast, in DPA-SWIPT, the high-power ES is constrained to a narrow band at the carrier frequency, resulting in less interference with bordering networks. Various system parameters were discussed, including the EH circuit's voltage multiplier output and ID data rates. As a result, the split receiver design demonstrated a considerable increase of more than 15 dBm in harvestable power level compared to the combined receiver. Moreover, this thesis also aims to improve the peak to average power ratio (PAPR). Hence, the PAPR of several wavelet methods are investigated, with the wavelet-based modulation technique outperforming fast Fourier transform (FFT) orthogonal frequency division multiplexing (OFDM) substantially where Haar wavelet scored a gain of almost 5dBm. As a result, it is stated that wavelet modulation is an excellent contender for implementation at the SN, where energy efficiency is critical. Ultimately, the increase in the input power level of the EH circuitry coupled with enhancing the energy efficiency of the WSN nodes marks an important milestone toward achieving fully autonomous WSNs.