Washington University in St. Louis
Adaptively Predictive Clustering of Mimo Beamforming Considering Co-Channel Interference in Time Varying Wireless Channel
Abstract
dc:description.abstract<p>There has been significant effort to enhance the capacity of wireless communication channels. For example, results have been reported for MIMO (Multiple Input Multiple Output), spatial and temporal multiplexing, channel diversity, and power and direction controlled beamforming.</p><p>In this research, we discuss issues associated with clustered cells, like the ones we see in today's wireless networks. Specifically, we consider basestations as a set of cooperating agents, i.e., the Coordinated Multi-Point (CoMP) model, each of which can provide spatial and temporal multiplexing to enhance the signal to noise ratio in the wireless channel. Of particular concern in this talk is the performance of the wireless channel near the cell boundaries where a mobile device can receive significant interference from adjacent basestations.</p><p>We propose a method for adaptively clustering basestations to minimize multi-cell interferences. Our method clusters basestations depending on predicted interference patterns among them at the cell boundaries. The proposed method uses autoregressive channel models and the CoMP MIMO beamforming. The proposed method has been verified to improve the channel capacity, especially when there is a limited amount of feedback for the channel. We apply our method to the wireless relay network to increase the coverage of cellular system at cell boundary area.</p>
Degree
thesis:*- Name thesis:degree_name
- Doctor of Philosophy (PhD)
- Level thesis:degree_level
- Dissertation
- Discipline thesis:degree_discipline
- Electrical & Systems Engineering
- Year dc:date.available
- 2011
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Yoon, Uooyeol
- Contributors dc:contributor
-
- Da-Ren Chen
Subjects
dc:subject × 7Rights
dc:rights- Statement dc:rights
-
- I have not registered my thesis with the U.S. Copyright Office, and do not intend to.
- Language dc:language
- English (en)
Identifiers
dc:identifier.*- OAI identifier oai:identifier
- oai:openscholarship.wustl.edu:eng_etds-1107