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New SLM Technique with Low Complexity Based on Matrices Combined with DCT Transform for PAPR Reduction in OFDM Communication Systems

Abstract Orthogonal Frequency Division Multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems. However, the main drawback of OFDM systems is that, it exhibits high Peak to Average Power Ratio (PAPR) of the transmitted signals which causes inefficient use of the High Power Amplifier (HPA) and could limit transmission efficiency. OFDM consist of large number of independent subcarriers, as a result of which the amplitude of such a signal can have a high peak values. Selected Mapping (SLM) technique is one of the promising PAPR reduction techniques for Orthogonal Frequency Division Multiplexing (OFDM). But this reduction technique results in a huge amount of computation complexity which is costly and time consuming. This technique however increases the computational and phase search complexity and PAPR reduction is performance largely dependent on the selection of random phase sequences. In this paper, one effective PAPR reduction scheme is proposed. These techniques combine the DCT with SLM techniques and we proposed the use of Hanowa, Riemann, and Hilbert matrices to obtain phase sequences for the SLM. The experimental results clearly prove that Hanowa matrix approach offers the best PAPR reduction in comparison with the SLM scheme using other matrices for phase sequence. This approach also avoids randomness in phase sequence selection, which makes it simpler to decode at the receiver. As added benefits, the matrix can be generated at the receiver end to obtain the data signal and hence it is not required to transmit Side Information (SI).