Abstract
The advancements in the wireless communication industry have revolutionised how societies exchange information. It is foreseen that wireless communication systems' capacity will have to grow by 1,000 folds to accommodate the ever-growing number of wireless users. A part of this capacity enhancement will be made possible via an increase in the number of access points (AP)s, which will increase the number and type of electromagnetic field (EMF) exposure sources in the environment. The World Health Organization (WHO) has classified these EMF radiations as possibly carcinogenic to humans. Therefore, this thesis aims at proposing novel techniques and performing exhaustive analysis to minimise EMF exposure, even well below the limits identified by the regulatory authorities.
This thesis, firstly, provides a detailed survey related to the possible health hazards linked with the EMF exposure and the different metrics that are currently used for evaluating, limiting and mitigating the effects of this type of exposure on the individual user. Based on these EMF exposure metrics assessment, a novel EMF-aware resource allocation scheme for the uplink of power domain non-orthogonal multiple access (PD-NOMA) based systems is proposed, where each user terminal (UT) available in the network is equipped with a single antenna element for the uplink transmission. This scheme uses unsupervised machine learning (ML) technologies to reduce the EMF exposure by a fair margin compared to other existing EMF-aware scheduling schemes while satisfying the required quality of service (QoS).
The presence of multiple antenna elements on a UT opens up opportunities to further reduce the EMF exposure compared to a single antenna element. In order to limit the potential health effect of EMF exposure, UT antennas must comply with EMF regulations, as they are very close to the human body. Therefore, the coupling between the two planar inverted-F antenna (PIFA) elements is substantially manipulated to reduce the specific absorption rate (SAR) to the human head. This work identifies the antenna element requirements to enable the design of context-aware multiple antennas handset to operate at low SAR in talk position and multiple-input multiple-output (MIMO) transmission mode in data mode. Results from this work shown that SAR can be reduced by a factor of three or more compared to a single antenna element when the appropriate settings identified in this work are selected.
Based on the coupling manipulation analysis, a novel context-aware rim antenna design is proposed, which effectively exploits the level of mutual coupling between the antenna elements to reduce the EMF exposure when the UT comes in close contact with the human body. Analysis and results show that an up to 30% reduction in SAR (compared to their baseline value) can be achieved by any 2x2 MIMO rim antenna when using the proposed design.