Millimeter wave wearable communication networks : analytic modeling and MIMO support

Future high-end wearable electronic devices including virtual reality goggles and augmented reality glasses require rates of the order of gigabits-per-second and potentially very low latency. Supporting high data rate wireless connectivity for applications such as uncompressed video streaming among wearable devices in a densely crowded environment is challenging. This is primarily due to bandwidth scarcity when many users operate multiple devices simultaneously. The millimeter wave (mmWave) band has the potential to address this bottleneck, thanks to more spectrum and less interference because of signal blockage at these frequencies. This dissertation addresses key questions that need to be answered before realizing mmWave-based wearables in practice: (i) what are the expected achievable rates in a crowded user environment, with mmWave devices using a given hardware configuration? (ii) how is the wireless connectivity affected in an indoor operation, which is prone to surface reflections? (iii) can multi-stream data transmission, involving large bandwidth communication under hardware constraints be realized? To answer these, tools from stochastic geometry and compressive sensing, and architectures involving hybrid analog/digital multiple-input multiple-output (MIMO) are leveraged. The main contributions of this dissertation are 1) analytical modeling to compute average achievable rates in mmWave wearable networks consisting of finite number of user devices and human blockages, 2) characterizing the impact of reflections and non-isotropic performance of mmWave wearable networks in crowded indoor environments, 3) channel estimation to support MIMO for wideband mmWave wearable devices using hybrid architecture, and 4) designing optimal, but easy-to-implement, precoding/combining strategies in frequency-selective mmWave systems. Both analysis and numerical simulations show how the proposed evaluation methodology and solutions serve to enable mmWave based communication among next generation wearable electronic devices.

Name thesis:degree_name

Doctor of Philosophy

Level thesis:degree_level

Doctoral

Discipline thesis:degree_discipline

Electrical and Computer Engineering

Grantor

The University of Texas at Austin

Year dc:date.issued

2017

Author dc:creator

• Venugopal, Kiran

Advisor dc:contributor.advisor

• Heath, Robert W., Jr, 1973-

Committee members dc:contributor.committeemember

• Baccelli, Francois
• Valenti, Matthew C.
• de Veciana, Gustavo
• Vikalo, Haris

• Millimeter wave communication
• Wearable communication networks
• Indoor communication
• Finite network modeling
• Human body blocking
• Wideband channel estimation
• Hybrid beamformers
• Optimal MIMO precoding and combining

Language dc:language.iso

en

Identifier

doi:10.15781/T2P55DZ7S

OAI identifier oai:identifier

oai:repositories.lib.utexas.edu:2152/62069