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### Browsing by Author "Dehghan, Mostafa"

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- ItemOpen AccessCooperative Diversity Routing in Wireless Networks(2009-10-07T16:01:56Z) Dehghan, Mostafa; Ghaderi, Majid; Goeckel, Dennis
Show more In this paper, we explore physical layer cooperative communication in order to design network layer routing algorithms that are energy efficient. We assume each node in the network is equipped with a single omnidirectional antenna and that multiple nodes are able to coordinate their transmissions in order to take advantage of spatial diversity to save energy. Specifically, we consider cooperative diversity at physical layer and multi-hop routing at network layer, and formulate minimum energy routing as a joint optimization of the transmission power at the physical layer and the link selection at the network layer. We then show that as the network becomes larger, finding optimal cooperative routes becomes computationally intractable. As such, we develop a number of heuristic routing algorithms that have polynomial computational complexity, and yet achieve significant energy savings. Simulation results are also presented, which indicate that the proposed algorithms based on optimal power allocation significantly outperform existing algorithms based on equal power allocation, by more than 60% in some simulated scenarios.Show more - ItemOpen AccessEnergy Efficient Cooperative Routing in Wireless Networks(2009-06-05T19:45:20Z) Dehghan, Mostafa; Ghaderi, Majid
Show more In this paper, we explore physical layer cooperative communication in order to design network layer routing algorithms that are energy efficient. We assume each node in the network is equipped with a single omnidirectional antenna and that multiple nodes are able to coordinate their transmissions in order to take advantage of spatial diversity to save energy. Specifically, we consider cooperative MIMO at physical layer and multi-hop routing at network layer, and formulate minimum energy routing as a joint optimization of the transmission power at the physical layer and the link selection at the network layer. Using dynamic programming, we compute the energy consumption of the optimal cooperative routing in different network scenarios, which shows energy savings of up to 55%, compared with the optimal non-cooperative routing. As the network becomes larger, however, finding optimal routes becomes computationally intractable as the complexity of the dynamic programming approach increases as O(22n), where n is the number of nodes in the network. As such, we develop two greedy routing algorithms that have complexity of O(n2), and yet achieve significant energy savings. Simulation results indicate that the proposed greedy algorithms perform almost as good as the optimal algorithm and achieve energy savings of more than 50% in the simulated scenarios.Show more - ItemOpen AccessMinimum-Energy Cooperative Routing in Wireless Networks with Channel Variations(2010-08-05T16:46:10Z) Dehghan, Mostafa; Ghaderi, Majid; Goeckel, Dennis
Show more 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.Show more