Discrete-time level-crossing analysis of soft handoff performance in cellular networks

Leu, A.E.; Mark, Brian L.

doi:10.1109/tit.2006.876357

Cited by 3 publications

(3 citation statements)

References 26 publications

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“…There is a rich literature on handoff (see [8], [9], [12]- [14] and the references therein), which deal with handoff parameter optimization, decision criterion, etc. However, these studies do not deal with QoS and capacity-related performance.…”

Section: Related Work and Motivationmentioning

confidence: 99%

QoS-Aware Downlink Cooperation for Cell-Edge and Handoff Users

Agarwal

Kumar

Gupta

2015

IEEE Trans. Veh. Technol.

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In this paper, we present a quality-of-service (QoS)aware cooperative downlink scheduling approach for cell-edge and handoff users that offers more reliability and higher effective capacity. The cooperation (handoff) region is defined for active handoff users between two adjacent base stations (BSs) as a function of the user QoS requirements and network load. In addition, the proposed technique inherently acquires intercell interference (ICI) coordination by adjusting the position and size of the cooperation window suitably. Numerical results are presented showing reliability, user QoS and capacity gain performance, and the region for cooperative scheduling in a coded communication scenario. Our analysis indicates that cooperation provides relatively less gain in effective capacity, i.e., up to about 40% with respect to noncooperative handoff, when the QoS requirement is loose. On the other hand, when the QoS requirement is more stringent, the effective capacity gain can increase up to nearly 100%. Additionally, we show that, while for applications with a loose QoS requirement the cooperation window size is small, i.e., nearly 1% of the total area of the BSs participating in cooperation, it increases quite significantly, i.e., up to nearly 25%, for the applications with stringent QoS. Although the outage performance of the proposed approach is poorer than the joint transmission mode of a cooperative multipoint scheme in lightly loaded networks, its effective capacity is significantly higher under varying network traffic load and QoS constraints.Index Terms-Cooperative handoff, cooperation region-ofinterest, effective capacity, outage probability. 0018-9545

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Section: Related Work and Motivationmentioning

confidence: 99%

QoS-Aware Downlink Cooperation for Cell-Edge and Handoff Users

Agarwal

Kumar

Gupta

2015

IEEE Trans. Veh. Technol.

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“…[7], [11]) for analyzing the handoff algorithm in terms of the five components illustrated in Fig. 2: sampler, averaging filter, subsampler, classifier, and handoff automaton.…”

Section: A Framework For Handoff Analysismentioning

confidence: 99%

Local Averaging for Fast Handoffs in Cellular Networks

Mark

Leu²

2007

IEEE Trans. Wireless Commun.

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Abstract-We propose a local averaging technique for processing the received pilot signal strength, which can significantly improve handoff performance in cellular networks. In handoff algorithms, the received pilot signal strength is typically averaged to diminish the undesirable effect of the fast fading component. Unfortunately, the averaging process can substantially alter the characteristics of path loss and shadowing components, causing increased handoff delay. The proposed local averaging method provides significant improvement for handoff delay performance, especially in the non-line-of-sight case, when the mobile station turns around a corner. An important feature of local averaging is that the handoff performance is insensitive to the speed of the mobile station, such that velocity estimation is not needed. We develop efficient numerical procedures to compute the handoff performance metrics under local averaging.

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“…By introducing handoff interference, the important tradeoff between seamless connectivity (i.e., number of handoffs) and the interference associated with handoff can be taken into account. Using the discrete-time approach for handoff analysis discussed in [11], [17], we develop an exact method to compute the handoff interference along arbitrary trajectories. We also derive exact expressions for computing the outage probabilities along an arbitrary trajectory, in contrast to [14]- [16].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Handoff Interference and Outage along Arbitrary Trajectories in Cellular Networks

Leu

Mark

Tang

2008

IEEE Trans. Wireless Commun.

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Abstract-We introduce a new system performance measure due to handoff called handoff interference, which characterizes the additional interference noise induced by the handoff process. The handoff interference experienced by a mobile unit is determined by the parameters of the handoff algorithm. We present an exact analysis of the handoff interference and the outage probability and develop a discrete-time method to efficiently and accurately compute these performance metrics along arbitrary trajectories in a cellular network. Our numerical results reveal critical tradeoffs among the critical handoff performance metrics, which should be taken into account in dimensioning the handoff parameters to optimize system performance. We discuss an example handoff design problem, which illustrates how to dimension the handoff parameters to optimize this tradeoff using the proposed handoff analysis.

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Discrete-time level-crossing analysis of soft handoff performance in cellular networks

Cited by 3 publications

References 26 publications

QoS-Aware Downlink Cooperation for Cell-Edge and Handoff Users

QoS-Aware Downlink Cooperation for Cell-Edge and Handoff Users

Local Averaging for Fast Handoffs in Cellular Networks

Analysis of Handoff Interference and Outage along Arbitrary Trajectories in Cellular Networks

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