Abstract
Although Long Term Evolution Advanced (LTE-Advanced) system has benefited from Carrier Aggregation (CA) technology, the advent of CA technology has increased handover scenario probability through user mobility. That leads to a user’s throughput degradation and its outage probability. Therefore, a handover decision algorithm must be designed properly in order to contribute effectively for reducing this phenomenon. In this paper, Multi-Influence Factors for Adaptive Handover Decision Algorithm (MIF-AHODA) have been proposed through CA implementation in LTE-Advanced system. MIF-AHODA adaptively makes handover decisions based on different decision algorithms, which are selected based on the handover scenario type and resource availability. Simulation results show that MIF-AHODA enhances system performance better than the other considered algorithms from the literature by 8.3 dB, 46%, and 51% as average gains over all the considered algorithms in terms of SINR, cell-edge spectral efficiency, and outage probability reduction, respectively.
Highlights
In mobile wireless systems, there are several handover decision algorithms (HODAs) which have been proposed based on different parameters such as (i) Received Signal Strength (RSS), (ii) RSS with a threshold, (iii) RSS with hysteresis, (iv) RSS with hysteresis and threshold (parameters (i) to (iv) are discussed in detail from Pollini) [1], (v) RSS with hysteresis and distance [2], (vi) Signal-to-Interference-plus-NoiseRatio (SINR) [3], and (vii) Interference-to-Interference-plusNoise-Ratio (IINR) [4]
There are five handover scenarios that can occur in LTE-Advanced system when Carrier Aggregation (CA) technology is implemented, which are described in Figure 2 and can be introduced by (i) interfrequency intrasector and intra-evolved node B (eNB) handover, (ii) intrafrequency intersector and intra-eNB handover, (iii) interfrequency intersector and intra-eNB handover, (iv) intrafrequency inter-eNB handover, and (v) interfrequency inter-eNB handover [6]
System performance evaluations achieved by MIF-AHODA and the other considered HODAs are presented in terms of user SINR, spectral efficiency, and user’s outage probability as shown in Figures 5, 6, and 7, respectively
Summary
There are several handover decision algorithms (HODAs) which have been proposed based on different parameters such as (i) Received Signal Strength (RSS), (ii) RSS with a threshold, (iii) RSS with hysteresis, (iv) RSS with hysteresis and threshold (parameters (i) to (iv) are discussed in detail from Pollini) [1], (v) RSS with hysteresis and distance [2], (vi) Signal-to-Interference-plus-NoiseRatio (SINR) [3], and (vii) Interference-to-Interference-plusNoise-Ratio (IINR) [4]. The advent of CA technology has added a new handover scenario, which can be performed between the serving component carriers (CCs) under the same sector and the same evolved node B (eNB) to change the primary component carriers (PCCs) This leads to increased handover probability, which in turn leads to increased throughput degradation and user outage probability. Journal of Computer Networks and Communications changing handover decision algorithm based on the handover scenario type and availability of resources This algorithm aims to enhance system performance in the perspective of SINR, cell-edge spectral efficiency, and outage probability reduction through the users’ mobility.
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