Comparison of alternative handoff strategies for micro-cellular mobile communication systems

Senarath, G.N.; Everitt, D.

doi:10.1109/vetec.1994.345338

Cited by 11 publications

(10 citation statements)

References 5 publications

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“…However, this scheme causes cell dragging; cell dragging occurs when an MS moves a considerable distance into the neighboring cell areas without making handover. In Reference [5], another approach is proposed which uses both adaptive relative threshold scheme [3,4] and an adaptive absolute threshold scheme. In this approach, more emphasis is given to the adaptive threshold when the risk factor is low.…”

Section: Handover Schemesmentioning

confidence: 99%

“…For a single class service networks, k and k can be assumed to be equal for all the cells. Therefore, Equation 7 can be written in terms of number of users as follows: Figure 3 shows the new handover points (solid lines) versus the handover points of the previous work [3,4] (dotted lines). For mobile users moving from a congested Cell 1 to a relatively free Cell 2, the handover is triggered at position D R12 , while using the scheme presented in References [3,4] handover takes place at position D 12 > D R12 .…”

Section: Generalized Distribution-based Handovermentioning

confidence: 99%

“…Therefore, Equation 7 can be written in terms of number of users as follows: Figure 3 shows the new handover points (solid lines) versus the handover points of the previous work [3,4] (dotted lines). For mobile users moving from a congested Cell 1 to a relatively free Cell 2, the handover is triggered at position D R12 , while using the scheme presented in References [3,4] handover takes place at position D 12 > D R12 . For a mobile user moving from Cell 2 to Cell 1, the handover is triggered at position D R21 , which is at a larger distance from Cell 2 than the handover position D 21 of the scheme in References [3,4].…”

Section: Generalized Distribution-based Handovermentioning

confidence: 99%

“…For mobile users moving from a congested Cell 1 to a relatively free Cell 2, the handover is triggered at position D R12 , while using the scheme presented in References [3,4] handover takes place at position D 12 > D R12 . For a mobile user moving from Cell 2 to Cell 1, the handover is triggered at position D R21 , which is at a larger distance from Cell 2 than the handover position D 21 of the scheme in References [3,4]. The proposed handover scheme is described in Figure 4.…”

Section: Generalized Distribution-based Handovermentioning

confidence: 99%

“…For example, when the RSS of the serving cell is low, the hysteresis margin is decreased. Simulation results in References [3,4] show that this scheme yields a lower average number of unnecessary handovers and call dropouts than the fixed threshold (FT) schemes. The applications of nonstandard approaches to handover control include prediction techniques, neural networks and hypothesis testing.…”

mentioning

confidence: 97%

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Adaptive distribution-based handover scheme for cellular communication networks

Almutairi

Ali

Karaata

2005

Wirel. Commun. Mob. Comput.

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In this paper, we propose a new Generalized Distribution-Based Handover (DBHO) to deal with the inefficient utilization of spectral resources due to the non-uniform cell loads. The DBHO scheme is different from the existing adaptive schemes since it uses a new criterion to initiate handover when moving from/to a congested cell. Two risk factors are used to dynamically change handover boundaries according to the distribution of traffic loads. This controls the handover initiation process such that a user in a congested cell that is moving to a free cell is allowed to initiate a handover to a new cell earlier, as long as the signal received from the target cell is higher than a certain threshold. While delaying the handover initiation process for a user moving in the opposite direction, as long as the signal received from the serving cell is not lower than a certain threshold. Our results show a substantial reduction in the handover and call dropouts rates. Our scheme is complementary to the existing adaptive schemes proposed in the literature. The proposed scheme also gives cellular system designers a new tool to optimize the overall network performance by initiating handovers based on the traffic intensities.Frequent handovers increase the load on switching networks, which consequently degrades the Quality of Service (QoS). Existing handover schemes usually use parameters such as the received signal strength for initiating a handover with some additional measurements to reduce unnecessary handovers and call dropouts. These schemes perform well when cell loads are somewhat evenly distributed, but fail to account for nonuniform traffic, as is often the case in microcells. Hence, it is desirable to design efficient handover schemes to avoid unnecessary handovers, reduce call dropouts and yet dynamically adapt to the variation of traffic among cells. In this paper, we present a new adaptive handover scheme that dynamically changes the handover boundaries to balance cell loads and to effectively reduce the average number of handovers.

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Section: Handover Schemesmentioning

confidence: 99%