Enhancing Cell Throughput & Area Spectral Efficiency Using Two Level Soft Frequency Reuse Technique
Baljot kaur1, Garima Saini2

1Baljot kaur, M.Tech Student, Department of Electronics & Communication Engineering, National Institute of Technical Teachers Training & Research, Chandigarh, India.
2Garima Saini, Assistant Professor, Phd persuing, Department of Electronics & Communication Engineering, National Institute of Technical Teachers Training & Research, Chandigarh, India.

Manuscript received on 30 June 2019 | Revised Manuscript received on 05 July 2019 | Manuscript published on 30 July 2019 | PP: 1524-1530| Volume-8 Issue-9, July 2019 | Retrieval Number: I8159078919/19©BEIESP | DOI: 10.35940/ijitee.I8159.078919
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Heterogeneous networks consist of different characteristics of networks like small cells having low power deployed along with macro cells having high power. Interference is the major issue to degrade the quality of signal in the heterogeneous networks. Number of interference coordination techniques are implemented to minimize interference. One of the interference coordination technique is fractional frequency reuse (FFR) and soft frequency reuse (SFR). In this paper two level Soft Frequency Reuse technique is implemented along with sectors. Parameters such as area spectral efficiency and cell edge throughput are calculated and compared with conventional FFR and Multi-level FFR technique with 6 sectoring. Better results are analyzed while simulating in the network model. Cell edge throughput improved to 54 Mbps, average cell throughput improved to 667 Mbps, peak data throughput improved to 76.7 Mbps and area spectral efficiency improved to 70.3 bits/sec/Hz/cell.
Keywords: Area spectral efficiency, Fractional Frequency Reuse (FFR), Interference, Millimetre wave band, 5G.

Scope of the Article: Predictive Analysis