Dynamic Neighbor Cell List Management for Handover Optimization in LTE

Watanabe, Yoshinori; Matsunaga, Yasushi; Kobayashi, Kosei; Sugahara, H.; Hamabe, Kojiro

doi:10.1109/vetecs.2011.5956456

Cited by 23 publications

(19 citation statements)

References 4 publications

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“…Perhaps the main motivation of this manuscript is the work of [18], where the authors propose a neighbour cell list management scheme based on the long-term statistics of UE measurements. A key parameter of this scheme is the forgetting factor , which weighs the longitudinal UE measurements.…”

Section: Related Workmentioning

confidence: 99%

“…A similar case, where the NCL needs to be updated when a new macrocell is deployed, is studied in [23]. Other ways to dynamically build the NCL via crowdsourcing are presented in [18,24]. A similar work applied to WiMax is presented in [25], and a closely related approach for the femtocell case is presented in [26].…”

Section: Related Workmentioning

confidence: 99%

“…To achieve that, the construction of a reliable NCL is one of the most critical tasks. While in the past this was achieved by drive and walk testing, the needs to adapt to changes in the network and to reduce the cost require different solutions [12,18,22].…”

Section: G Network Optimisationmentioning

confidence: 99%

See 2 more Smart Citations

Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

Checco

Lancia

Leith

2018

Wireless Communications and Mobile Computing

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In modern wireless networks deployments, each serving node needs to keep its Neighbour Cell List (NCL) constantly up to date to keep track of network changes. The time needed by each serving node to update its NCL is an important parameter of the network's reliability and performance. An adequate estimate of such parameter enables a significant improvement of self-configuration functionalities. This paper focuses on the update time of NCLs when an approach of crowdsourced user reports is adopted. In this setting, each user periodically reports to the serving node information about the set of nodes sensed by the user itself. We show that, by mapping the local topological structure of the network onto states of increasing knowledge, a crisp mathematical framework can be obtained, which allows in turn for the use of a variety of user mobility models. Further, using a simplified mobility model we show how to obtain useful upper bounds on the expected time for a serving node to gain Full Knowledge of its local neighbourhood.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

Checco

Lancia

Leith

2018

Wireless Communications and Mobile Computing

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“…In the most of cases, the number of neighbors is reduced based on statistical frequency of handovers performed to individual neighboring cells [8], [10], [11] or based on the length of the NCL [12]. However, any elimination of a neighbor to which the handover can be performed leads to a rise in probability of missing handover target cell and consequently to the call drops.…”

Section: Introductionmentioning

confidence: 99%

Self-configured Neighbor Cell List of macro cells in network with Small Cells

Vondra

Bečvář

2013

2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

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To ensure faultless handover procedure of mobile users, each cell in the network must establish a Neighbor Cell List (NCL). The NCL contains adjacent cells to which handover can be performed. A problem related to the handover from a Macro/Micro cell (MeNB) appears with the rising density of cells with the limited coverage, so-called Small Cells (SCeNBs). By using method of the NCL creation described in standards or literature, the number of neighboring cells suitable for handover from the MeNB can be extensive. Therefore, we propose an algorithm for automatic creation of the NCL with reduced number of included cells. The proposed algorithm exploits knowledge of the last visited cell in combination with the statistical information on performed handovers in the past to determine the possibility of transition to the neighboring cells. As the results show, the proposed algorithm significantly reduces the number of cells in the NCL while the probability of missing handover target cell in the NCL is kept negligible.

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“…Therefore, we focus on the second approach of the NCL optimization. Most of the work in this area of the NCL management focuses on networks with macrocells only (see, e.g., ). However, in the future mobile networks, dense deployment of small cells, such as femtocells, picocells, or microcells, is assumed to be an essential part of network architecture .…”

Section: Introductionmentioning

confidence: 99%

Self‐optimizing neighbor cell list with dynamic threshold for handover purposes in networks with small cells

Bečvář

Mach

Vondra

2013

Wireless Communications

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To select a proper target cell for handover of mobile users, signal level of cells in user's neighborhood is scanned by a user equipment (UE). Cells assumed to be scanned are included in the so-called neighbor cell list (NCL). Conventionally, the NCL is managed according to the probability of handover of users to a target cell with fixed threshold. Nevertheless, the size of NCL could be significant if this approach is applied to networks with small cells. In this paper, we exploit knowledge of handover probability among cells derived from a handover history to reduce the amount of scanned cells. We introduce dynamic adaptation of the amount of cells to be scanned according to the quality of signal of a serving cell, measured by the UE. We also investigate impact of relation between the handover probability and the signal level to maximize efficiency of this approach. Further, the NCL management considering either summarized handover history of all UE or individual history of each user is compared in our evaluations. As the results show, both methods notably reduce the amount of cells to be scanned, while call drop rate and outage of the users are still negligible as in the conventional way.

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Dynamic Neighbor Cell List Management for Handover Optimization in LTE

Cited by 23 publications

References 4 publications

Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

Updating Neighbour Cell List via Crowdsourced User Reports: A Framework for Measuring Time Performance

Self-configured Neighbor Cell List of macro cells in network with Small Cells

Self‐optimizing neighbor cell list with dynamic threshold for handover purposes in networks with small cells

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