A Novel Signal Scrambling Technique for PAPR Reduction in OFDM Systems
Anjana Sharma1, Amarjeet Kaur2, Shikha Saxena3, Prashant Singh4
1Anjana Sharma, Assistant Professor, Chandigarh Engineering College since, Chandigarh (Punjab), India.
2Amarjeet Kaur, Assistant Professor, Chandigarh Engineering College since, Chandigarh (Punjab), India.
3Shikha Saxena, Assistant Professor, Chandigarh Engineering College since, Chandigarh (Punjab), India.
4Prashant Singh, Assistant Professor, Chandigarh Engineering College since, Chandigarh (Punjab), India.
Manuscript received on 05 August 2019 | Revised Manuscript received on 12 August 2019 | Manuscript Published on 26 August 2019 | PP: 767-770 | Volume-8 Issue-9S August 2019 | Retrieval Number: I11240789S19/19©BEIESP | DOI: 10.35940/ijitee.I1124.0789S19
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© 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: OFDM forms the basis of the upcoming next generation technologies so as to achieve higher data rates within a given bandwidth effectively. One of the major issues associated with OFDM is Peak to Average Power Ratio (PAPR) which needs to be minimized to get an efficient performance. The random variation in the signal amplitude of the OFDM signal leads to additional interference in the system and hence affecting the performance of HPA in non-linear region. In this paper, we propose a technique for the reduction of PAPR in OFDM systems with some increased complexity which works for any modulation type and any number of subcarriers. The simulation results show performance improvement with respect to the existing signal scrambling techniques.
Keywords: Orthogonal Frequency Division Multiplexing (OFDM), Peak to Average Power Ratio (PAPR), High Power Amplifier (HPA), Complimentary Cumulative Distribution Function (CCDF).
Scope of the Article: Community Information Systems