Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with...
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![Page 1: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/1.jpg)
Understanding Radio Irregularity in Wireless Networks
Torsten Mütze, ETH Zürichjoint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso
![Page 2: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/2.jpg)
Outline
Motivation Network Model Connectivity Interference
![Page 3: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/3.jpg)
Motivation
Ideal:- circular transmission rangePath Loss Model (deterministic)
Connectivity?Capacity?
More realistic:- obstacles in the transmission path- non-isotropic antennasLog-normal Shadowing Model (randomized)
![Page 4: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/4.jpg)
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Network Model (1)
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Network Model (2)Path Loss Model
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Log-normal Shadowing Model
[Hekmat, Mieghem 06; Bettstetter, Hartmann 05; Miorandi, Altman 05; Orriss, Barton 03]
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Radio irregularity is controlled througha single parameter, the shadowing deviation
![Page 6: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/6.jpg)
Connectivity (1)Connectivity: probability of the network graph to be connected
Biased Analysis: Connectivity increase is caused by a higher expected
node degree (=enlarged radio transmission range)How to do a fair comparison between different levels of radio irregularity?
Expected node degree
[Bettstetter, Hartmann 05]
![Page 7: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/7.jpg)
Connectivity (2)Normalization!When increasing , vary thetransmission power p0 as afunction of such that theexpected node degree remainsconstant
[Jonasson 01], [Roy, Tanemura 02]
Why?Edge length distribution
Longer connections help
Surprise: Connectivity increases withirregularity, even under constant nodedegree
![Page 8: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/8.jpg)
Interference limits the throughput capacity of a network [Stüdi, Alonso 06]
Interference (1)
Interferers: smallest set of nodes that must not transmit concurrently to the communication from b to a
signal
interference + noisethreshold
Signal-to-interference-plus-noise ratio model (SINR)
ab
pab
I interferers
non-interferersI
![Page 9: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/9.jpg)
Expected number of interferers for fixed pab
Biased Analysis: Interference increase is caused by a higher cumulated noiseNormalization! Keep the expected cumulated noise constant when varyingExpected number of interferers for fixed pab
Interference (2)Expected cumulated noise
a
Why?Power density function
More nodes with small/largetransmission power (=more non-interferers)
Surprise: Interference decreases with irregularity (under constant expected cumulated noise)
![Page 10: Understanding Radio Irregularity in Wireless Networks Torsten Mütze, ETH Zürich joint work with Patrick Stüdi, Fabian Kuhn and Gustavo Alonso.](https://reader030.fdocuments.us/reader030/viewer/2022032800/56649d405503460f94a19d81/html5/thumbnails/10.jpg)
Summary Studied impact of log-normal shadowing on
connectivity and interference First unbiased analysis: fair comparison between
different levels of radio irregularity Beneficial impact of log-normal shadowing on
both connectivity and interference (improved connectivity, reduced interference)
Existing bounds on connectivity and capacity derived in a circular transmission range model are lower instead of upper bounds
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Thank you!