Cooperative transmission techniques for ad hoc and wireless sensor networks are known to increase the network lifetime. Indeed, the improved spatial diversity allows a more efficient energy usage. Under the Rayleigh fading assumption, the selection of cooperative partners is typically based on the knowledge of the average channel power. However, Rayleigh fading is not a suitable model in a large number of practical scenarios, in particular for indoor-to-outdoor applications. In these scenarios additional information of the fading distribution is needed for partner selection. The main focus of this work is to provide an analytical framework to evaluate the impact of the fading statistics on partner selection algorithms. A distributed multi-link channel model is derived from indoor-to-indoor and indoor-to-outdoor channel measurements in order to simulate practical scenarios where the proposed analytical framework is tested. Finally, we introduce a novel partner selection strategy that exploits the distributed knowledge of the effect
Impact of Fading Statistics on Partner Selection in Indoor-to-Outdoor Cooperative Networks
SAVAZZI, STEFANO;NICOLI, MONICA BARBARA;
2010-01-01
Abstract
Cooperative transmission techniques for ad hoc and wireless sensor networks are known to increase the network lifetime. Indeed, the improved spatial diversity allows a more efficient energy usage. Under the Rayleigh fading assumption, the selection of cooperative partners is typically based on the knowledge of the average channel power. However, Rayleigh fading is not a suitable model in a large number of practical scenarios, in particular for indoor-to-outdoor applications. In these scenarios additional information of the fading distribution is needed for partner selection. The main focus of this work is to provide an analytical framework to evaluate the impact of the fading statistics on partner selection algorithms. A distributed multi-link channel model is derived from indoor-to-indoor and indoor-to-outdoor channel measurements in order to simulate practical scenarios where the proposed analytical framework is tested. Finally, we introduce a novel partner selection strategy that exploits the distributed knowledge of the effectFile | Dimensione | Formato | |
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