Abstract | ||
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The performance of wireless networks depends critically on their spatial configuration, because received signal power and interference depend critically on the distances between numerous transmitters and receivers. This is particularly true in emerging network paradigms that may include femtocells, hotspots, relays, white space harvesters, and meshing approaches, which are often overlaid with traditional cellular networks. These heterogeneous approaches to providing high-capacity network access are characterized by randomly located nodes, irregularly deployed infrastructure, and uncertain spatial configurations due to factors like mobility and unplanned user-installed access points. This major shift is just beginning, and it requires new design approaches that are robust to spatial randomness, just as wireless links have long been designed to be robust to fading. The objective of this article is to illustrate the power of spatial models and analytical techniques in the design of wireless networks, and to provide an entry-level tutorial. |
Year | DOI | Venue |
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2010 | 10.1109/MCOM.2010.5621983 | IEEE Communications Magazine |
Keywords | Field | DocType |
spatial model,signal power,wireless network,network paradigm,new design approach,spatial modeling,wireless link,uncertain spatial,traditional cellular network,spatial configuration,high-capacity network access,signal to noise ratio,signal interference,femtocells,modeling,mobility,interference,hotspots,cellular networks,transmitters,ad hoc networks,cellular network,wireless networks | Wireless network,White spaces,Wireless,Computer science,Fading,Computer network,Cellular network,Wireless ad hoc network,Wi-Fi array,Access network,Distributed computing | Journal |
Volume | Issue | ISSN |
48 | 11 | 0163-6804 |
Citations | PageRank | References |
186 | 10.63 | 15 |
Authors | ||
5 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jeffrey G. Andrews | 1 | 18102 | 1115.64 |
Radha Krishna Ganti | 2 | 3411 | 206.50 |
Martin Haenggi | 3 | 4480 | 292.10 |
Nihar Jindal | 4 | 4714 | 482.24 |
Steven Weber | 5 | 724 | 53.55 |