Design of Network Coding Schemes and RF Energy Transfer in Wireless Communication Networks

This thesis focuses on the design of network coding schemes and radio frequency (RF) energy transfer in wireless communication networks. During the past few years, network coding has attracted significant attention because of its capability to transmit maximum possible information in a network from multiple sources to multiple destinations via a relay. Normally, the destinations are only able to decode the information with sufficient prior knowledge. To enable the destinations to decode the information in the cases with less/no prior knowledge, a pattern of nested codes with multiple interpretations using binary convolutional codes is constructed in a multi-source multi-destination wireless relay network. Then, I reconstruct nested codes with convolutional codes and lattice codes in multi-way relay channels to improve the spectrum efficiency. Moreover, to reduce the high decoding complexity caused by the adopted convolutional codes, a network coded non-binary low-density generator matrix (LDGM) code structure is proposed for a multi-access relay system. Another focus of this thesis is on the design of RF-enabled wireless energy transfer (WET) schemes. Much attention has been attracted by RF-enabled WET technology because of its capability enabling wireless devices to harvest energy from wireless signals for their intended applications. I first configure a power beacon (PB)-assisted wireless-powered communication network (PB-WPCN), which consists of a set of hybrid access point (AP)-source pairs and a PB. Both cooperative and non-cooperative scenarios are considered, based on whether the PB is cooperative with the APs or not. Besides, I develop a new distributed power control scheme for a power splitting-based interference channel (IFC) with simultaneous wireless information and power transfer (SWIPT), where the considered IFC consists of multiple source-destination pairs

Spectrum Sharing in RF-Powered Cognitive Radio Networks using Game Theory

We investigate the spectrum sharing problem of a radio frequency (RF)-powered cognitive radio network, where a multi-antenna secondary user (SU) harvests energy from RF signals radiated by a primary user (PU) to boost its available energy before information transmission. In this paper, we consider that both the PU and SU are rational and self-interested. Based on whether the SU helps forward the PU's information, we develop two different operation modes for the considered network, termed as non-cooperative and cooperative modes. In the non-cooperative mode, the SU harvests energy from the PU and then use its available energy to transmit its own information without generating any interference to the primary link. In the cooperative mode, the PU employs the SU to relay its information by providing monetary incentives and the SU splits its energy for forwarding the PU's information as well as transmitting its own information. Optimization problems are respectively formulated for both operation modes, which constitute a Stackelberg game with the PU as a leader and the SU as a follower. We analyze the Stackelberg game by deriving solutions to the optimization problems and the Stackelberg Equilibrium (SE) is subsequently obtained. Simulation results show that the performance of the Stackelberg game can approach that of the centralized optimization scheme when the distance between the SU and its receiver is large enough.Comment: Presented at PIMRC'1

Relatedness and Compatibility: Semantic Dimensions of the Concept of Privacy in Chinese and English Corpora

This dissertation is a study of how privacy as an ethical concept exists in two languages: Mandarin Chinese and American English. The assumption for this dissertation is that different languages will have their own distinctive expressions and understandings when it comes to privacy. Specifically, I have proposed a cross-genre and cross-language study to include two genres of language corpora for each of the languages: social media posts and news articles. In addition, the language corpora span from 2010 to 2019, which supported an observation of how privacy-related languages may have changed and evolved over the years. I took a mixed-methods approach, by using two computational methods: semantic network analysis (SNA) and structural topic modeling (STM) for processing the natural language corpora. When it comes to labeling and interpreting the results of topic modeling, I relied on external coders for labeling and my own in-depth reading of the topic words as well as original documents to make sense of the meaning of these topics. Last but not least, based on the interpretations of topics, I proposed four semantic dimensions and used these four dimensions to come back to code all the topics to have an overall depiction of the topics across these two languages and two genres. The four semantic dimensions, though were found present in both languages, have revealed unequal presence in the two languages. Specifically, the institution dimension has much more presence in the English language; and in the Chinese language, it is the individual dimension that is frequently seen across topics in both genres. Apart from topics, this different emphasis on these two semantic dimensions (institution and individual) is also reflected through the semantic network analysis of nodes where the nodes with leading centrality scores over the years in these two languages differ. After considering the limitation of the data in this study, I conclude by arguing that overall, it is more cautious and appropriate to understand the incompatibilities by saying the two languages differ by their emphasis on different dimensions. This study is one of the first empirically-grounded intercultural explorations of the concept of privacy. It not only provides an examination of the concept as it is understood at the current time of writing but also reveals that natural language is promising to operationalize intercultural privacy research and comparative privacy research.Doctor of Philosoph

Prepulse Inhibition of Auditory Cortical Responses in the Caudolateral Superior Temporal Gyrus in Macaca mulatta

Prepulse inhibition (PPI) refers to a decreased response to a startling stimulus when another weaker stimulus precedes it. Most PPI studies have focused on the physiological startle reflex and fewer have reported the PPI of cortical responses. We recorded local field potentials (LFPs) in four monkeys and investigated whether the PPI of auditory cortical responses (alpha, beta, and gamma oscillations and evoked potentials) can be demonstrated in the caudolateral belt of the superior temporal gyrus (STGcb). We also investigated whether the presence of a conspecific, which draws attention away from the auditory stimuli, affects the PPI of auditory cortical responses. The PPI paradigm consisted of Pulse-only and Prepulse + Pulse trials that were presented randomly while the monkey was alone (ALONE) and while another monkey was present in the same room (ACCOMP). The LFPs to the Pulse were significantly suppressed by the Prepulse thus, demonstrating PPI of cortical responses in the STGcb. The PPI-related inhibition of the N1 amplitude of the evoked responses and cortical oscillations to the Pulse were not affected by the presence of a conspecific. In contrast, gamma oscillations and the amplitude of the N1 response to Pulse-only were suppressed in the ACCOMP condition compared to the ALONE condition. These findings demonstrate PPI in the monkey STGcb and suggest that the PPI of auditory cortical responses in the monkey STGcb is a pre-attentive inhibitory process that is independent of attentional modulation.Peer reviewe

Functional connectivity of intrinsic cognitive networks during resting state and task performance in preadolescent children

Earlier studies on adults have shown that functional connectivity (FC) of brain networks can vary depending on the brain state and cognitive challenge. Network connectivity has been investigated quite extensively in children in resting state, much less during tasks and is largely unexplored between these brain states. Here we used functional magnetic resonance imaging and independent component analysis to investigate the functional architecture of large-scale brain networks in 16 children (aged 7-11 years, 11 males) and 16 young adults (aged 22-29 years, 10 males) during resting state and visual working memory tasks. We identified the major neurocognitive intrinsic connectivity networks (ICNs) in both groups. Children had stronger FC than adults within the cingulo-opercular network in resting state, during task performance, and after controlling for performance differences. During tasks, children had stronger FC than adults also within the default mode (DMN) and right frontoparietal (rFPN) networks, and between the anterior DMN and the frontopolar network, whereas adults had stronger coupling between the anterior DMN and rFPN. Furthermore, children compared to adults modulated the FC strength regarding the rFPN differently between the brain states. The FC within the anterior DMN correlated with age and performance in children so that the younger they were, the stronger was the FC, and the stronger the FC within this network, the slower they performed the tasks. The group differences in the network connectivity reported here, and the observed correlations with task performance, provide insight into the normative development of the preadolescent brain and link maturation of functional connectivity with improving cognitive performance.Peer reviewe