In this two-part paper, information-theoretic capacity scaling laws are analyzed in an underwater acoustic network with n regularly located nodes on a square, in which both bandwidth and received signal power can be limited significantly. Parts I and II deal with an extended network of unit node density and a dense network of unit area, respectively. In both cases, a narrow-band model is assumed where the carrier frequency is allowed to scale as a function of n, which is shown to be crucial for achieving the order optimality in multi-hop (MH) mechanisms. We first characterize an attenuation parameter that depends on the frequency scaling as well as the transmission distance. Upper and lower bounds on the capacity scaling are then derived. In Part I, we show that the upper bound on capacity for extended networks is inversely proportional to the attenuation parameter, thus resulting in a highly power-limited network. Interestingly, it is shown that the upper bound is intrinsically related to the attenuation parameter but not the spreading factor. Furthermore, we propose an achievable communication scheme based on the nearest-neighbor MH transmission, which is suitable due to the low propagation speed of acoustic channel, and show that it is order-optimal for all operating regimes of extended networks. Finally, these scaling results are extended to the case of random node deployments providing fundamental limits to more complex scenarios of extended underwater networks.
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Acknowledgments This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A1044151), by the Air Force Office of Scientific Research (AFOSR) under award No. 016974-002, by the National Science Foundation under grant No. 501731, and by the ONR grant No. 599257. This material in this paper was presented in part at the IEEE International Symposium on Information Theory, Austin, TX, June 2010.
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Electrical and Electronic Engineering