Low-Latency Massive MIMO Design over Practical Channels
type: CreativeWork
description: With the emerging time-critical applications, low-latency communication is the focus of the next-generation wireless network, which is labeled as 5G. One of the key enabling technologies of 5G is massive MIMO or base-stations with tens to hundreds of antennas. In this thesis, I design cross-layer transmission control for massive MIMO and demonstrate that high throughput can be achieved at less than 1 ms latency. The latency minimizing transmission control design requires the correct understanding and abstraction of the physical radio propagation. To understand the unique propagation properties of massive MIMO, I measure the wireless channel in-the-wild with RiceArgos platform. Surprisingly, I find that geolocational far-away user channels can still be of high correlation even for the base-station with 64 antennas. More specifically, the mutual channel correlation between close-by users does not reduce with array size beyond 20. Using spatial signal processing and modeling, I pinpoint the root cause of the observed user correlation to be the overlapped angle-of-departures. Furthermore, I propose new channel models to capture the measured user channel correlation and then derive the achievable rates in closed-form for zero-forcing and conjugate based systems in the large-array asymptotic regime. The measured high user correlation is in direct conflict with the current point-to-point based channel models, where user channels are assumed to be independent. Therefore, my measurement findings and analysis collectively demonstrate the need for new multiuser channel modeling and open doors for better multiuser system designs. To understand the structure of the latency-optimal control, I perform cross-layer optimizations for single-user massive MIMO systems. I first present a Markov decision process based algorithm which computes the latency-optimal control at the cost of high computational complexity. To reduce complexity, I propose a low-complexity deterministic transmissi…
abstract: With the emerging time-critical applications, low-latency communication is the focus of the next-generation wireless network, which is labeled as 5G. One of the key enabling technologies of 5G is massive MIMO or base-stations with tens to hundreds of antennas. In this thesis, I design cross-layer transmission control for massive MIMO and demonstrate that high throughput can be achieved at less than 1 ms latency. The latency minimizing transmission control design requires the correct understanding and abstraction of the physical radio propagation. To understand the unique propagation properties of massive MIMO, I measure the wireless channel in-the-wild with RiceArgos platform. Surprisingly, I find that geolocational far-away user channels can still be of high correlation even for the base-station with 64 antennas. More specifically, the mutual channel correlation between close-by users does not reduce with array size beyond 20. Using spatial signal processing and modeling, I pinpoint the root cause of the observed user correlation to be the overlapped angle-of-departures. Furthermore, I propose new channel models to capture the measured user channel correlation and then derive the achievable rates in closed-form for zero-forcing and conjugate based systems in the large-array asymptotic regime. The measured high user correlation is in direct conflict with the current point-to-point based channel models, where user channels are assumed to be independent. Therefore, my measurement findings and analysis collectively demonstrate the need for new multiuser channel modeling and open doors for better multiuser system designs. To understand the structure of the latency-optimal control, I perform cross-layer optimizations for single-user massive MIMO systems. I first present a Markov decision process based algorithm which computes the latency-optimal control at the cost of high computational complexity. To reduce complexity, I propose a low-complexity deterministic transmissi…
author: Du, Xu
language: eng
keywords: Low-Latency, Delay, MIMO, 5G, QoS, Array, Massive MIMO, Channel Model, Cross-Layer Control
date published: 2019-08-26
date modified: 2026-07-24T04:10:17Z
provider: Rice University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Rice University

PropertyValue
property ID: Handle
value: https://hdl.handle.net/1911/106284