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Design and analysis of handoff algor...

Leu, Alexe Emanoil.

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Design and analysis of handoff algorithms in mobile networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Design and analysis of handoff algorithms in mobile networks./
作者:	Leu, Alexe Emanoil.
面頁冊數:	174 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5127.
Contained By:	Dissertation Abstracts International64-10B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3108638

Design and analysis of handoff algorithms in mobile networks.
Leu, Alexe Emanoil.

Design and analysis of handoff algorithms in mobile networks. - 174 p.

Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5127.

Thesis (Ph.D.)--George Mason University, 2003.

The handoff algorithms employed in a cellular network have a significant impact on overall network performance, but evaluation of handoff performance has for the most part been done using only brute-force computer simulation or approximations. We introduce a new discrete-time approach to analyze the performance of handoff algorithms based on pilot signal strength measurements. We derive closed-form expressions and develop numerical procedures to evaluate handoff performance metrics for a mobile station moving along straight-line trajectories in a cellular network employing hard and soft handoff. The numerical procedures provide computational solutions for the open problem of modeling the discrete-time level crossing probabilities determined by hysteresis and drop-timer margins used in hard and soft handoff algorithms.Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Design and analysis of handoff algorithms in mobile networks.
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100 1 $a Leu, Alexe Emanoil. $3 1951012
245 1 0 $a Design and analysis of handoff algorithms in mobile networks.
300 $a 174 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5127.
500 $a Director: Brian L. Mark.
502 $a Thesis (Ph.D.)--George Mason University, 2003.
520 $a The handoff algorithms employed in a cellular network have a significant impact on overall network performance, but evaluation of handoff performance has for the most part been done using only brute-force computer simulation or approximations. We introduce a new discrete-time approach to analyze the performance of handoff algorithms based on pilot signal strength measurements. We derive closed-form expressions and develop numerical procedures to evaluate handoff performance metrics for a mobile station moving along straight-line trajectories in a cellular network employing hard and soft handoff. The numerical procedures provide computational solutions for the open problem of modeling the discrete-time level crossing probabilities determined by hysteresis and drop-timer margins used in hard and soft handoff algorithms.
520 $a Our discrete-time approach provides valuable analytical insight into the performance impact of handoff algorithms. Moreover our numerical procedures for discrete-time handoff analysis provide accurate and efficient tools for the design and dimensioning of high performance handoff algorithms. The accuracy of the numerical procedures are validated by simulation results.
520 $a We develop a new local averaging technique for processing signal strength measurements in a wireless network. The local averaging technique removes the fast fading component of the received signal strength without altering the shadowing and path loss components, unlike conventional averaging techniques. Application of the local averaging technique provides better hard handoff performance particularly when the mobile station turns around the corners. We introduce a new hard handoff algorithm that employs local averaging, a drop timer, and hysteresis. The proposed algorithm achieves better performance than conventional hysteresis-based handoff algorithms that employ exponential averaging. Also, the local averaging technique simplifies the statistical properties of the processed signal measurements. This can be exploited to derive more efficient computational procedures for evaluating handoff performance when local averaging technique is used.
590 $a School code: 0883.
650 4 $a Engineering, Electronics and Electrical. $3 626636
650 4 $a Engineering, System Science. $3 1018128
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710 2 0 $a George Mason University. $3 1019450
773 0 $t Dissertation Abstracts International $g 64-10B.
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791 $a Ph.D.
792 $a 2003
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