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Minimum-Energy Cooperative Routing in Wireless Networks with Channel Variations

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Author
Dehghan, Mostafa
Ghaderi, Majid
Goeckel, Dennis
Accessioned
2010-08-05T16:46:10Z
Available
2010-08-05T16:46:10Z
Issued
2010-08-05T16:46:10Z
Other
Cooperative communication, minimum energy routing, variable wireless channels
Subject
Wireless
networks
Type
technical report
Metadata
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Abstract
This paper considers the problem of finding minimum-energy cooperative routes in a wireless network with variable wireless channels. We assume that each node in the network is equipped with a single omnidirectional antenna and, motivated by the large body of physical layer research indicating its potential utility, that multiple nodes are able to coordinate their transmissions at the physical layer in order to take advantage of spatial diversity. Such coordination, however, is intrinsically intertwined with routing decisions, thus motivating the work. We first formulate the energy cost of forming a cooperative link between two nodes based on a two-stage transmission strategy assuming that only statistical knowledge about channels is available. Utilizing the link cost formulation, we show that optimal static routes in a network can be computed by running Dijkstra’s algorithm over an extended network graph created by cooperative links. However, due to the variability of wireless channels, we argue that many-to-one cooperation model in static routing is suboptimal. Hence, we develop an opportunistic routing algorithm based on many-to-many cooperation, and show that optimal routes in a network can be computed by a stochastic version of the Bellman-Ford algorithm. We use static and opportunistic optimal algorithms as baselines to develop heuristic link selection algorithms that are energy efficient while being computationally simpler than the optimal algorithms. We simulate our algorithms and show that while optimal cooperation and link selection can reduce energy consumption by almost an order of magnitude compared to non-cooperative approaches, our simple heuristics perform reasonably well achieving similar energy savings while being computationally efficient as well.
Refereed
No
Corporate
University of Calgary
Faculty
Science
Doi
http://dx.doi.org/10.11575/PRISM/30626
Uri
http://hdl.handle.net/1880/48017
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