Theses and Dissertations from UMD
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Item Radio Analytics for Indoor Localization and Vital Sign Monitoring(2017) Chen, Chen; Liu, K. J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Radio technology has been widely used for high-speed wireless communications. In the near future, radio technology would provide sensing capabilities to enable a diversified indoor applications in the era of Internet of Things (IoT). This is because that the electromagnetic (EM) wave, emitted from the transmitter propagates through multipath before arriving at the receiver, is varied by the environmental perturbations. Such variations in EM waves reveal important environmental changes useful for IoT applications. Thus, in IoT networks, radios are not only the ubiquitous communication interfaces but also exhibit augmented sensing potential. Despite the wide variety of IoT devices, most of them are equipped with WiFi which is a very mature and cost-effective connectivity solution and has evolved significantly ever since its standardization. Meanwhile, as people are spending more and more time indoors, most indoor spaces have been already equipped with WiFi infrastructures, which makes the IoT devices empowered by WiFi to blend into the existing WiFi infrastructures without efforts. Therefore, it is highly valuable to adopt radio analytics to analyze the WiFi radio signals to facilitate key IoT applications. In this dissertation, we explore the viability of using WiFi for two important IoT applications: indoor localization and vital sign monitoring. In the first part, we propose two indoor localization systems (IPSs) leveraging the time-reversal (TR) technique on off-the-shelf WiFi devices. The proposed IPSs utilize the location-specific features, i.e., the channel frequency response (CFR), which is a fine-grained information readily available on off-the-shelf devices that depicts the propagation of EM waves from the transmitter to different locations. The proposed IPSs consist of an offline phase which collects CFRs from locations-of-interest, and an online phase which compares the instantaneous CFRs with those captured in the offline phase. To calculate the similarities among locations, the TR focusing effect is evaluated quantitively between each pair of CFRs associated with these locations using the TR resonating strength (TRRS). Realizing that the bandwidth limit on mainstream WiFi devices could lead to location ambiguity, we exploit two diversities inherent in WiFi devices, i.e., frequency diversity and spatial diversity, to expand the effective bandwidth. Extensive experiments show a localization accuracy of 1 to 2 centimeters even under strong non-line-of-sight (NLOS) conditions as well as enhanced robustness against environmental dynamics. In the second part, we investigate the feasibility of high accuracy vital sign monitoring using CFRs. First of all, we present a highly accurate breathing monitoring system. Realizing that breathing injects tiny but periodic signals into the WiFi signal, we project the CFR time series onto the TRRS feature space to amplify such CFR perturbations. Integrated with machine learning techniques, the proposed scheme could distinguish breathing rates associated with different people. In addition, it could detect the presence of breathing and count the number of people. The performance is demonstrated by extensive experiments in multiple environments. Secondly, we present a lightweight vital sign monitoring solution with a much reduced computational complexity. Moreover, we supplement the proposed vital sign monitoring system with a finite state machine (FSM) to remedy the impact of motions on the monitoring performance. Extensive experimental results demonstrate the excellent performance of both breathing monitoring schemes.Item JOINT ENERGY BEAMFORMING AND TIME ASSIGNMENT FOR COOPERATIVE WIRELESS POWERED NETWORKS(2016) Chen, Chen; Qu, Gang; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Wireless power transfer (WPT) and radio frequency (RF)-based energy har- vesting arouses a new wireless network paradigm termed as wireless powered com- munication network (WPCN), where some energy-constrained nodes are enabled to harvest energy from the RF signals transferred by other energy-sufficient nodes to support the communication operations in the network, which brings a promising approach for future energy-constrained wireless network design. In this paper, we focus on the optimal WPCN design. We consider a net- work composed of two communication groups, where the first group has sufficient power supply but no available bandwidth, and the second group has licensed band- width but very limited power to perform required information transmission. For such a system, we introduce the power and bandwidth cooperation between the two groups so that both group can accomplish their expected information delivering tasks. Multiple antennas are employed at the hybrid access point (H-AP) to en- hance both energy and information transfer efficiency and the cooperative relaying is employed to help the power-limited group to enhance its information transmission throughput. Compared with existing works, cooperative relaying, time assignment, power allocation, and energy beamforming are jointly designed in a single system. Firstly, we propose a cooperative transmission protocol for the considered system, where group 1 transmits some power to group 2 to help group 2 with information transmission and then group 2 gives some bandwidth to group 1 in return. Sec- ondly, to explore the information transmission performance limit of the system, we formulate two optimization problems to maximize the system weighted sum rate by jointly optimizing the time assignment, power allocation, and energy beamforming under two different power constraints, i.e., the fixed power constraint and the aver- age power constraint, respectively. In order to make the cooperation between the two groups meaningful and guarantee the quality of service (QoS) requirements of both groups, the minimal required data rates of the two groups are considered as constraints for the optimal system design. As both problems are non-convex and have no known solutions, we solve it by using proper variable substitutions and the semi-definite relaxation (SDR). We theoretically prove that our proposed solution method can guarantee to find the global optimal solution. Thirdly, consider that the WPCN has promising application potentials in future energy-constrained net- works, e.g., wireless sensor network (WSN), wireless body area network (WBAN) and Internet of Things (IoT), where the power consumption is very critical. We investigate the minimal power consumption optimal design for the considered co- operation WPCN. For this, we formulate an optimization problem to minimize the total consumed power by jointly optimizing the time assignment, power allocation, and energy beamforming under required data rate constraints. As the problem is also non-convex and has no known solutions, we solve it by using some variable substitutions and the SDR method. We also theoretically prove that our proposed solution method for the minimal power consumption design guarantees the global optimal solution. Extensive experimental results are provided to discuss the system performance behaviors, which provide some useful insights for future WPCN design. It shows that the average power constrained system achieves higher weighted sum rate than the fixed power constrained system. Besides, it also shows that in such a WPCN, relay should be placed closer to the multi-antenna H-AP to achieve higher weighted sum rate and consume lower total power.