Enabling 5G Technologies

The increasing demand for connectivity and broadband wireless access is leading to the fifth generation (5G) of cellular networks. The overall scope of 5G is greater in client width and diversity than in previous generations, requiring substantial changes to network topologies and air interfaces. This divergence from existing network designs is prompting a massive growth in research, with the U.S. government alone investing $400 million in advanced wireless technologies. 5G is projected to enable the connectivity of 20 billion devices by 2020, and dominate such areas as vehicular networking and the Internet of Things. However, many challenges exist to enable large scale deployment and general adoption of the cellular industries. In this dissertation, we propose three new additions to the literature to further the progression 5G development. These additions approach 5G from top down and bottom up perspectives considering interference modeling and physical layer prototyping. Heterogeneous deployments are considered from a purely analytical perspective, modeling co-channel interference between and among both macrocell and femtocell tiers. We further enhance these models with parameterized directional antennas and integrate them into a novel mixed point process study of the network. At the air interface, we examine Software-Defined Radio (SDR) development of physical link level simulations. First, we introduce a new algorithm acceleration framework for MATLAB, enabling real-time and concurrent applications. Extensible beyond SDR alone, this dataflow framework can provide application speedup for stream-based or data dependent processing. Furthermore, using SDRs we develop a localization testbed for dense deployments of 5G smallcells. Providing real-time tracking of targets using foundational direction of arrival estimation techniques, including a new OFDM based correlation implementation

Implementation and Analysis of Spectral Subtraction and Signal Separation in Deterministic Wide-Band Anti-Jamming Scenarios

With the increasing volume of wireless traffic that military operations require, the likelihood of transmissions interfering with each other is steadily growing to the point that new techniques need to be employed. Furthermore, to combat remotely operated improvised explosive devices, many ground convoys transmit high-power broadband jamming signals, which block both hostile as well as friendly communications. These wide-band jamming fields pose a serious technical challenge to existing anti-jamming solutions that are currently employed by the Navy and Marine Corps. This thesis examines the feasibility of removing such deterministic jammers from the spectral environment, enabling friendly communications. Anti-jamming solutions in self-jamming environments are rarely considered in the literature, principally due to the non-traditional nature of such jamming techniques. As a result, a combination of approaches are examined which include: Antenna Subset Selection, Spectral Subtraction, and Source Separation. These are combined to reduce environmental interference for reliable transmissions. Specific operational conditions are considered and evaluated, primarily to define the limitations and utility of such a system. A final prototype was constructed using a collection of USRP software defined radios, providing solid conclusions of the overall system performance

A Green Approach to a Multi-Protocol Wireless Communications Network

The goal of this project is to increase the battery life of mobile wireless devices. This is achieved by having the wireless device select between two wireless protocols, ZigBee and Wi-Fi, based on transmission energy and bandwidth requirements. Using the concepts of sensing and adaptation from cognitive radio, the system monitors the bandwidth and selects the lowest power intensive wireless protocol while still maintaining an acceptable quality of service for the desired task

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio