DocumentCode
623862
Title
Channel assignment in dense MC-MR wireless networks: Scaling laws and algorithms
Author
Urgaonkar, Rahul ; Ramanathan, Ram ; Redi, Judith ; Tetteh, William N.
Author_Institution
Network Res. Dept., Raytheon BBN Technol., Cambridge, MA, USA
fYear
2013
fDate
14-19 April 2013
Firstpage
2607
Lastpage
2615
Abstract
We investigate optimal channel assignment algorithms that maximize per node throughput in dense multi-channel multi-radio (MC-MR) wireless networks. Specifically, we consider an MC-MR network where all nodes are within the transmission range of each other. This situation is encountered in many real-life settings such as students in a lecture hall, delegates attending a conference, or soldiers in a battlefield. In this scenario, we show that intelligent assignment of the available channels results in a significantly higher per node throughput. We first propose a class of channel assignment algorithms, parameterized by T (the number of transceivers per node), that can achieve Θ(1/N1/T) per node throughput using Θ(TN1-1/T ) channels. In view of practical constraints on T, we then propose another algorithm that can achieve Θ((1/log2n)2) per node throughput using only two transceivers per node. Finally, we identify a fundamental relationship between the achievable per node throughput, the total number of channels used, and the network size under any strategy. Using analysis and simulations, we show that our algorithms achieve close to optimal performance at different operating points on this curve. Our work has several interesting implications on the optimal network design for dense MC-MR wireless networks.
Keywords
channel allocation; radio networks; radio transceivers; channel assignment; dense multi-channel multi-radio wireless networks; intelligent assignment; optimal network design; transceivers; Algorithm design and analysis; Indexes; Level set; Routing; Throughput; Transceivers; Wireless networks;
fLanguage
English
Publisher
ieee
Conference_Titel
INFOCOM, 2013 Proceedings IEEE
Conference_Location
Turin
ISSN
0743-166X
Print_ISBN
978-1-4673-5944-3
Type
conf
DOI
10.1109/INFCOM.2013.6567068
Filename
6567068
Link To Document