Citation
Hussein, Yassein Soubhi
(2014)
Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks.
Doctoral thesis, Universiti Putra Malaysia.
Abstract
The tremendous growth of mobile devices and their attendant applications demand for wireless communication networks supporting high data rates with large capacity. The Long Term Evolution (LTE) network which has been accepted as a 4G network, provides mobile users with a high throughput and low handover latency at high user speeds. The burgeoning growth of real-time applications such as interactive video and voice communications and other media rich contents, places a heavy demand on the network for high data rate and guaranteed quality of service (QoS). To support mobility to a user equipment (UE) it needs to be handed over to a new eNB (evolved node base-station) while still maintaining connectivity with the network at high data rates. This poses a significant challenge that needs to be addressed. In this thesis we propose a number of schemes to address handover issues such as Handover Failure (HOF), Handover Ping-Pong (HOPP), Outage Probability (OP), Handover Delay (HOD), Packet Loss Ratio (PLR) and Inter Cell Interference (ICI). These schemes extend over all handover phases, namely cell searching, cell selection and handover decision making. First, a scheme called soft frequency reuse and multiple preparations (SFRAMP) is proposed to provide a seamless and fast handover for a UE by way of reducing the handover latency and inter-cell interference which result in high throughput. It is shown that this proposed method significantly reduces the outage probability at various UE speeds. Simulation results using LTE-Sim show that the outage probability and delay are reduced by 24.4% and 11.9% respectively, compared to the hard handover (HHO) method that has been adopted for 4G. The second scheme is cell selection based on multiple criteria decision making (MCDM) approach. The scheme called fuzzy multiple criteria cell selection (FMCCS) considers S–criterion, a method which relies purely on the downlink signal strength, availability of resource blocks (RBs) and uplink SINR using an integrated fuzzy technique for order preference by similarity to ideal solution (TOPSIS). The conventional cell selection in LTE uses S-criterion only, which is inefficient. It is shown that FMCCS significantly reduces HOPP and HOF with higher throughput. The simulation results show that FMCCS outperforms conventional and cell selection scheme (CSS) methods in HOPP reduction by approximately 27% and 23% and HOF reduction by 19% and 15%, respectively. The throughput shows approximately 11% gain over the conventional scheme. The third scheme works on the self optimization of handover parameters using fuzzy logic control (FLC) and multiple preparation (MP) called FuzAMP. FLC can automatically optimize HO parameters i.e. Handover Margin (HOM) and Time-ToTrigger (TTT) based on a set of criteria, this is in order to minimize unwanted HOs known as HO Ping Pong (HOPP) and HO failure (HOF). The results demonstrated that our proposed method results in significant reductions of HOF, HOPP and packet loss ratio (PLR) compared to the conventional HHO and enhanced weighted performance HO parameter optimization (EWPHPO) algorithm. The results also show that the reduction of HOF through FuzAMP over conventional HHO algorithm is approximately 60%, 65%, and 66% at 3, 30, and 120 km/h, respectively, and over EWPHPO algorithm is approximately 30%, 46%, and 50% at 3, 30, and 120 km/h, respectively. In HOPP, the results demonstrate that the reduction of HOPP ratio by the FuzAMP algorithm relative to that of the conventional HHO algorithm is approximately 54%, 44%, and 69% at 3, 30, and 120 km/h, respectively, and over EWPHPO algorithm the improvement is approximately 38%, 33%, and 65%, respectively. Moreover, PLR is reduced by approximately 67%, 59%, and 68% at 3, 30, and 120 km/h, respectively, over HHO while over EWPHPO algorithm, the improvements are approximately 52%, 35%, and 48% at 3, 30, and 120 km/h, respectively.
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