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Improving Performance of Remote TCP in Cognitive Radio Networks

Authors
Yang, HyunCho, SungraePark, Chang Yun
Issue Date
Sep-2012
Publisher
KSII-KOR SOC INTERNET INFORMATION
Keywords
TCP; Congestion control; cognitive radio networks
Citation
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS, v.6, no.9, pp 2323 - 2340
Pages
18
Journal Title
KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS
Volume
6
Number
9
Start Page
2323
End Page
2340
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/20158
DOI
10.3837/tiis.2012.09.020
ISSN
1976-7277
1976-7277
Abstract
Recent advances in cognitive radio technology have drawn immense attention to higher layer protocols above medium access control, such as transmission control protocol (TCP). Most proposals to improve the TCP performance in cognitive radio (CR) networks have assumed that either all nodes are in CR networks or the TCP sender side is in CR links. In those proposals, lower layer information such as the CR link status could be easily exploited to adjust the congestion window and improve throughput. In this paper, we consider a TCP network in which the TCP sender is located remotely over the Internet while the TCP receiver is connected by a CR link. This topology is more realistic than the earlier proposals, but the lower layer information cannot be exploited. Under this assumption, we propose an enhanced TCP protocol for CR networks called TCP for cognitive radio (TCP-CR) to improve the existing TCP by (1) detection of primary user (PU) interference by a remote sender without support from lower layers, (2) delayed congestion control (DCC) based on PU detection when the retransmission timeout (RTO) expires, and (3) exploitation of two separate scales of the congestion window adapted for PU activity. Performance evaluation demonstrated that the proposed TCP-CR achieves up to 255% improvement of the end-to-end throughput. Furthermore, we verified that the proposed TCP does not deteriorate the fairness of existing TCP flows and does not cause congestions.
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Park, Chang Yun
소프트웨어대학 (소프트웨어학부)
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