To select appropriate target cell for handover if a
user is moving, cells in user's neighborhood must be scanned and
their signal quality must be measured by a User Equipment (UE).
The cells intended to be scanned are listed in a Neighbor Cell List
(NCL). The NCL is defined for each cell in the network and it is
distributed to the users. A size of the NCL can be negatively
influenced by dense deployment of cells with small radius, such
as femtocells. In this paper, we investigate potential reduction of
an amount of cells in the NCL to minimize signaling overhead
and time required for scanning in networks with femtocells.
Contrary to a conventional management of the NCL, we reduce
the NCL for each UE individually. The lower number of cells in
the UEs' NCL is achieved by consideration of mobility patterns
of individual user. To avoid situation when a real target cell is
missing in the NCL, we propose a dynamic adaptation of the
UE's NCL according to the quality of signal measured by the UE
from a serving cell. As the results show, the proposed approach
with dynamic threshold significantly reduces amount of scanned
cells comparing to competitive algorithms. Simultaneously, the
outage probability and call drop rates are still kept at minimum
level by our proposal.
Index Terms—neighbor cell list, self-optimization, mobility
pattern, handover statistics, femtocell
To select appropriate target cell for handover if auser is moving, cells in user's neighborhood must be scanned andtheir signal quality must be measured by a User Equipment (UE).The cells intended to be scanned are listed in a Neighbor Cell List(NCL). The NCL is defined for each cell in the network and it isdistributed to the users. A size of the NCL can be negativelyinfluenced by dense deployment of cells with small radius, suchas femtocells. In this paper, we investigate potential reduction ofan amount of cells in the NCL to minimize signaling overheadand time required for scanning in networks with femtocells.Contrary to a conventional management of the NCL, we reducethe NCL for each UE individually. The lower number of cells inthe UEs' NCL is achieved by consideration of mobility patternsof individual user. To avoid situation when a real target cell ismissing in the NCL, we propose a dynamic adaptation of theUE's NCL according to the quality of signal measured by the UEfrom a serving cell. As the results show, the proposed approachwith dynamic threshold significantly reduces amount of scannedcells comparing to competitive algorithms. Simultaneously, theoutage probability and call drop rates are still kept at minimumlevel by our proposal.Index Terms—neighbor cell list, self-optimization, mobilitypattern, handover statistics, femtocell
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