Capture effects on PRMA stability and performance

Qi, Honghui; Wyrwas, R.

doi:10.1049/el:19940417

Cited by 1 publication

(1 citation statement)

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“…A test packet is assumed to capture the mobile receiver if and only if its instantaneous power exceeds the instantaneous joint interference power by at least a threshold z [13], which reflects the capture performance of the applied receiver, modulation and coding techniques. During the capture of a packet, the received power p s is assumed constant [14]. The ALOHA channel is principally contention limited, so thermal and man-made noise are neglected, as is the influence of the irreducible errors due to random Doppler modulation.…”

Section: A Propagation Model and Capture Modelmentioning

confidence: 99%

Capture effect on R-ALOHA protocol for inter-vehicle communications

Ma¹,

Hrubik²,

Refai³

et al.

VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005.

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As a component of the intelligent transportation system (ITS) and one of the concrete applications of mobile ad-hoc networks, inter-vehicle communication (IVC) has attracted research attention from both the academia and industry. A key issue in the wireless network is the design of medium access control (MAC) layer protocols for distributed channel assignment. A promising class of protocols for IVC networks is R-ALOHA-based protocols. In this paper, we document our investigation of near-far effects and capture effects on R-ALOHA for a real-time distributed packet wireless network or IVC in the presence of multipath, and shadowing. The research recorded in this paper also studied the stability of R-ALOHA protocol for IVC analytically and by simulation. In order to analyze how fast R-ALOHA makes the network stable once communication among terminals is initiated, we construct a discrete Markov chain and derive new recursive formulas based on solutions to Markov chain to evaluate distribution and mean value of system stabilization time in the fading environment.

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Section: A Propagation Model and Capture Modelmentioning

confidence: 99%