A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets
Long Term Evolution Advanced (LTE-A) Heterogeneous Networks (HetNet) are an important aspect of 5th generation mobile communication systems. They consists of high power macrocells along with low power cells i.e. picocells and femtocells to fill up macrocell coverage gaps. HetNet permit deployment of...
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| Format: | Article |
| Language: | English |
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Spolecnost pro radioelektronicke inzenyrstvi
2016-12-01
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| Series: | Radioengineering |
| Subjects: | |
| Online Access: | http://www.radioeng.cz/fulltexts/2016/16_04_0763_0773.pdf |
| _version_ | 1811231618191327232 |
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| author | M. N. Qureshi M. I. Tiwana |
| author_facet | M. N. Qureshi M. I. Tiwana |
| author_sort | M. N. Qureshi |
| collection | DOAJ |
| description | Long Term Evolution Advanced (LTE-A) Heterogeneous Networks (HetNet) are an important aspect of 5th generation mobile communication systems. They consists of high power macrocells along with low power cells i.e. picocells and femtocells to fill up macrocell coverage gaps. HetNet permit deployment of femtocells by users for added flexibility, but then interference issues between neighbouring cells have to be addressed as all femtocells use the same frequency channels for transmission. To mitigate this problem, LTE-A standard offers two new features, one is carrier aggregation in which Component Carriers (CC) form the basic aggregate units shared among cells and the other is enhanced Inter-Cell Interference Co-ordination (eICIC) through X2 interface. The physical implementation of these features is left open to research. This paper investigates two distinct techniques for orthogonal CC selection through Stochastic Cellular Learning Automata (SCLA) to improve the QoS performance of a femtocell. The first, technique uses SCLA with user feedback, and the second technique uses SCLA with a central publishing server where all cells upload their past used CC vectors. SCLA methods are better suited for Self Organizing Network (SON) as they do not require synchronized cell coordination, have low complexity and have good optimization characteristics. The simulation results show that the techniques enhance the cell edge performance considerably. |
| first_indexed | 2024-04-12T10:48:02Z |
| format | Article |
| id | doaj.art-a1b0d50c8e154cd2b5269006fae962e4 |
| institution | Directory Open Access Journal |
| issn | 1210-2512 |
| language | English |
| last_indexed | 2024-04-12T10:48:02Z |
| publishDate | 2016-12-01 |
| publisher | Spolecnost pro radioelektronicke inzenyrstvi |
| record_format | Article |
| series | Radioengineering |
| spelling | doaj.art-a1b0d50c8e154cd2b5269006fae962e42022-12-22T03:36:20ZengSpolecnost pro radioelektronicke inzenyrstviRadioengineering1210-25122016-12-01254763773A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNetsM. N. QureshiM. I. TiwanaLong Term Evolution Advanced (LTE-A) Heterogeneous Networks (HetNet) are an important aspect of 5th generation mobile communication systems. They consists of high power macrocells along with low power cells i.e. picocells and femtocells to fill up macrocell coverage gaps. HetNet permit deployment of femtocells by users for added flexibility, but then interference issues between neighbouring cells have to be addressed as all femtocells use the same frequency channels for transmission. To mitigate this problem, LTE-A standard offers two new features, one is carrier aggregation in which Component Carriers (CC) form the basic aggregate units shared among cells and the other is enhanced Inter-Cell Interference Co-ordination (eICIC) through X2 interface. The physical implementation of these features is left open to research. This paper investigates two distinct techniques for orthogonal CC selection through Stochastic Cellular Learning Automata (SCLA) to improve the QoS performance of a femtocell. The first, technique uses SCLA with user feedback, and the second technique uses SCLA with a central publishing server where all cells upload their past used CC vectors. SCLA methods are better suited for Self Organizing Network (SON) as they do not require synchronized cell coordination, have low complexity and have good optimization characteristics. The simulation results show that the techniques enhance the cell edge performance considerably.http://www.radioeng.cz/fulltexts/2016/16_04_0763_0773.pdfHeterogeneous networks (HetNets)LTE-A3GPPstochastic cellular learning automata (SCLA)cellular automataself-optimization network (SON)femtocellcomponent carrier (CC)carrier aggregationcell publishing |
| spellingShingle | M. N. Qureshi M. I. Tiwana A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets Radioengineering Heterogeneous networks (HetNets) LTE-A 3GPP stochastic cellular learning automata (SCLA) cellular automata self-optimization network (SON) femtocell component carrier (CC) carrier aggregation cell publishing |
| title | A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets |
| title_full | A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets |
| title_fullStr | A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets |
| title_full_unstemmed | A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets |
| title_short | A Novel Stochastic Learning Automata Based SON Interference Mitigation Framework for 5G HetNets |
| title_sort | novel stochastic learning automata based son interference mitigation framework for 5g hetnets |
| topic | Heterogeneous networks (HetNets) LTE-A 3GPP stochastic cellular learning automata (SCLA) cellular automata self-optimization network (SON) femtocell component carrier (CC) carrier aggregation cell publishing |
| url | http://www.radioeng.cz/fulltexts/2016/16_04_0763_0773.pdf |
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