Orthogonal Frequency Division Multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems with high bandwidth efficiency and robustness against multipath fading. OFDM consists of many independent subcarriers, as a result of which the amplitude of such a signal can have high peak values. This high Peak to Average Power Ratio (PAPR) of the signal, when transmitted through a power amplifier generates out-of-band distortions and also increases the dynamic range of the Digital to Analog Converter (DAC) and Power Amplifier (PA). This paper proposes a new PAPR reduction technique termed Sliding Taxicab Norm Transform (STNT) at the transmitter and Inverse STNT (ISTNT) at the receiver. We further propose Permutation with Phase inversion STNT (PPSTNT) technique in our system to deal with highly correlated data. The results show that, the proposed scheme offer better performance in terms of PAPR reduction than the existing sliding norm transforms and various other conventional schemes. We have also proved that the computational complexity of the proposed scheme is lower than the conventional reduction techniques and further, there is no requirement for transmission of Side Information (SI) for recovering the signal at the receiver. The proposed algorithm is implemented on Wireless Open-Access Research Platform (WARP). Various performance measures were analyzed with random data, audio and image input. © 2019 by Begell House, Inc.