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DC Field | Value | Language |
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dc.contributor.author | Fapohunda, K.O | - |
dc.contributor.author | Paulson, Eberechukwu Numan | - |
dc.contributor.author | Zubair, Suleiman | - |
dc.contributor.author | Dyaji, Charles Bala | - |
dc.contributor.author | David, Michael | - |
dc.contributor.author | Mohd Fauzi, Mohd Husaini Bin | - |
dc.contributor.author | Yusof, Kamaludin Mohammed | - |
dc.date.accessioned | 2021-06-03T12:06:54Z | - |
dc.date.available | 2021-06-03T12:06:54Z | - |
dc.date.issued | 2018-09 | - |
dc.identifier.issn | 2210 -1519 | - |
dc.identifier.uri | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/995 | - |
dc.description.abstract | Hidden node problem sometimes referred to as frequent packets collision that mostly leads to loss of packets is no longer new in wireless networks because it affects the previous IEEE802.11 standards. The new IEEE802.11ah standard which is also a substandard of IEEE 802.11 is no exemption. As a matter of fact, IEEE802.11ah suffers from hidden node problem more than networks (IEEE 802.11a/b/n/ac) due to their wider coverage which is up to 1km, high number of devices they can support (over 8000 node s to one AP) and frequent simultaneous sleeping and sending of the nodes (power saving mode). A few researchers have worked on this hidden node problem in IEEE802.11ah but could not get a lasting solution to it. Therefore, this paper proposes an algorithm which detects hidden nodes and also proposes a theoretical solution based on previous works which was also experimentally verified through the BIHD-CM | en_US |
dc.publisher | International Journal of Computing and Network Technology | en_US |
dc.subject | Restricted Access Window (RAW), Collision, Hidden node, IEEE802.11ah, NS-3, Packet Loss. | en_US |
dc.title | Bat-Inspired Hidden Node Detection Algorithm and Collision Minimization (BIHD-CM) Scheme for IEEE802.11AH | en_US |
dc.type | Article | en_US |
Appears in Collections: | Telecommunication Engineering |
Files in This Item:
File | Description | Size | Format | |
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Bat-Inspired Hidden Note DetectionAlgorithm.pdf | 386.49 kB | Adobe PDF | View/Open |
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