2016Unpublished venueRequires access

Dwell Time and Predicted Mobility Based Handover for LTE networks

S Raghavi, Senthil Kumar T, M. A. Bhagyaveni

Open publisher page 4 citations

Abstract

Long Term Evolution (LTE) suffers from ‘Cell dragging effect’ and ‘Pilot pollution’ problem which results in inefficient handover performance. While considering the Reference Signal Received Strength (RSRP) of the serving and target cells for making handover decision, the problem of ‘Cell dragging effect’ occurs. It is a condition where a user entered into the coverage of a target cell still not handed over from the serving cell since he sees better RSRP from serving cell. ‘Pilot pollution’ is a condition where the power transmitted from many different cells appears in a location but none is significantly better than others. This paper proposes an algorithm to address the issue of ‘Cell dragging effect’ and ‘Pilot pollution’. It considers user equipment moving direction and dwell time of the target cells for implementing handover. The target cell is selected such that the considered factors are in favor to the corresponding target cell which in turn yields an efficient handover performance. A comparative analysis is done between ‘conventional coverage based handover’ and the ‘Dwell Time and Predicted Mobility Based Handover Algorithm’ (DPH). The simulation results show that the DPH scheme performs better than the traditional handover algorithm as it reduces the number of handovers.

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What this paper is about

Long Term Evolution (LTE) suffers from ‘Cell dragging effect’ and ‘Pilot pollution’ problem which results in inefficient handover performance. While considering the Reference Signal Received Strength (RSRP) of the serving and target cells for making handover decision, the problem of ‘Cell dragging effect’ occurs. It is a condition where a user entered into the coverage of a target cell still not handed over from the serving cell since he sees better RSRP from serving cell. ‘Pilot pollution’ is a condition where the power transmitted from many different cells appears in a location but none is significantly better than others. This paper proposes an algorithm to address the issue of ‘Cell dragging effect’ and ‘Pilot pollution’. It considers user equipment moving direction and dwell time of the target cells for implementing handover. The target cell is selected such that the considered factors are in favor to the corresponding target cell which in turn yields an efficient handover performance. A comparative analysis is done between ‘conventional coverage based handover’ and the ‘Dwell Time and Predicted Mobility Based Handover Algorithm’ (DPH). The simulation results show that the DPH scheme performs better than the traditional handover algorithm as it reduces the number of handovers.

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Available abstract

Long Term Evolution (LTE) suffers from ‘Cell dragging effect’ and ‘Pilot pollution’ problem which results in inefficient handover performance. While considering the Reference Signal Received Strength (RSRP) of the serving and target cells for making handover decision, the problem of ‘Cell dragging effect’ occurs. It is a condition where a user entered into the coverage of a target cell still not handed over from the serving cell since he sees better RSRP from serving cell. ‘Pilot pollution’ is a condition where the power transmitted from many different cells appears in a location but none is significantly better than others. This paper proposes an algorithm to address the issue of ‘Cell dragging effect’ and ‘Pilot pollution’. It considers user equipment moving direction and dwell time of the target cells for implementing handover. The target cell is selected such that the considered factors are in favor to the corresponding target cell which in turn yields an efficient handover performance. A comparative analysis is done between ‘conventional coverage based handover’ and the ‘Dwell Time and Predicted Mobility Based Handover Algorithm’ (DPH). The simulation results show that the DPH scheme performs better than the traditional handover algorithm as it reduces the number of handovers.

Key concepts: Handover, Dwell time, Computer science, Soft handover, Term (time), Computer network, Power (physics), Real-time computing

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