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Channel-hopping multiple access

Authors: Asimakis Tzamaloukas; J. J. Garcia-Luna-Aceves;

Channel-hopping multiple access

Abstract

The medium-access control (MAC) protocols for wireless networks proposed or implemented to date based on collision-avoidance handshakes between the sender and receiver either require carrier sensing or the assignment of unique codes to nodes to ensure that intended receivers hear data packets without interference from hidden sources. We present and analyze a protocol that we call channel-hopping multiple access (CHMA) for multi-channel, ad-hoc networks which does not require carrier sensing or the assignment of unique codes to nodes to ensure collision-free reception of data at the intended receivers in the presence of hidden terminals. We compare CHMA against MACA-CT and show considerable improvement in the performance achieved. The correct avoidance of collisions in CHMA protocols is verified, and their throughput and delay characteristics is studied analytically. CHMA protocols are applicable to ad-hoc networks based on commercial off-the shelf spread spectrum radios operating in unlicensed frequency bands.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
120
Top 10%
Top 1%
Average
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