Multi-hop wireless transmission, where radios forward the message of other radios, is becoming popular both in cellular as well as sensor networks.
This research is concerned with the statistical modeling of multi-hop wireless networks that do cooperative transmission (CT). CT is a physical layer wireless
communication scheme in which spatially separated wireless nodes collaborate to form a virtual array antenna for the
purpose of increased reliability. The dissertation has two major parts. The first part addresses a special form of CT known as the Opportunistic Large Array (OLA). The second part addresses the signal-to-noise ratio (SNR) estimation for the purpose of recruiting nodes for CT.
In an OLA transmission, the nodes from one level transmit the message signal concurrently without any coordination with each other, thereby producing transmit diversity. The receiving layer of nodes receives the message signal and repeats the process using the decode-and-forward cooperative protocol. The key contribution of this research is to model the transmissions that hop from one layer of nodes to another under the effects of channel variations, carrier frequency offsets, and path loss. It has been shown for a one-dimensional network that the successive transmission process can be modeled as a quasi-stationary Markov chain in discrete time. By studying various properties of the Markov chain, the system parameters, for instance, the transmit power of relays and distance between them can be optimized. This optimization is used to improve the performance of the system in terms of maximum throughput, range extensions, and minimum delays while delivering the data to the destination node using the multi-hop wireless communication system.
A major problem for network sustainability, especially in battery-assisted networks, is that the batteries are drained pretty quickly during the operation of the network. However, in dense sensor networks, this problem can be alleviated by using a subset of nodes which take part in CT, thereby saving the network energy. SNR is an important parameter in determining which nodes to participate in CT. The more distant nodes from the source having least SNR are most suitable to transmit the message to next level. However, practical real-time SNR estimators are required to do this job. Therefore, another key contribution of this research is the design of optimal SNR estimators for synchronized as well as non-synchronized receivers, which can work with both the symbol-by-symbol Rayleigh fading channels as well as slow flat fading channels in a wireless medium.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/42799 |
| Date | 18 October 2011 |
| Creators | Hassan, Syed Ali |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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