Learning vector quantization network for PAPR reduction in orthogonal frequency division multiplexing systems

Authors:
Seema Khalid;Syed Ismail Shah;Jamil Ahmad
Affiliations:
Center for Advanced Studies in Engineering, Islamabad, Pakistan;Iqra University Islamabad, Islamabad, Pakistan;Iqra University Islamabad, Islamabad, Pakistan
Venue:
UC'07 Proceedings of the 6th international conference on Unconventional Computation
Year:
2007

Citing 2
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OFDM for Wireless Multimedia Communications

OFDM for Wireless Multimedia Communications
Reduction in PAPR of OFDM system using a revised companding

ICCS '02 Proceedings of the The 8th International Conference on Communication Systems - Volume 01

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Abstract

Major drawback of Orthogonal Frequency Division Multiplexing (OFDM) is its high Peak to Average Power Ratio (PAPR) that exhibits inter modulation noise when the signal has to be amplified with a non linear high power amplifier (HPA). This paper proposes an efficient PAPR reduction technique by taking the benefit of the classification capability of Learning Vector Quantization (LVQ) network. The symbols are classified in different classes and are multiplied by different phase sequences; to achieve minimum PAPR before they are transmitted. By this technique a significant reduction in number of computations is achieved.