Abstract-Recent advancement in digital communication application has grown significantly. Developed communication methods demand for higher performance for real time application scenarios where noisy channels are present. In this context, polar codes have grown as a promising technique for errorcorrecting scheme and performance enhancement in memoryless channel communication scenarios. This article presents a brief study about polar coding, principle, encoding schemes and introduces a new encoding scheme for performance improvement of polar codes.In this work, we propose new encoding schemes which mainly address the issue of computational complexity and memory requirements for polar coding scheme. Here we address the issue related to systematic polar coding schemes and their computational complexity reduction. Proposed method computes the requirement of XOR implementation to encode the data and total memory requirement for complete encoding scheme. An experimental study is carried out to show the significance of proposed model where performance is computed in terms of bit error rate and frame error rate. Experimental study shows that proposed systematic encoding scheme outperform when compared to state-of-art technique.I. INTRODUCTION During recent years, demand of digital communication has grown rapidly which has improved the emerging technique coding theory for efficient data communication. In this field of data coding, Shannon's introduced channel coding theory which is best known effort for transmission of data reliability over a wireless noise channel and performance of system can be enhanced. Mainly, channel coding theory depends on the essential ideas which are: Code selection: Transmittedcode word and received data equipartition property while performing for large number of code length Maximum likelihood decoding: Asymptotic equipartition probability (AEP) is a promising technique which guarantees for better communication by reducing error in received codeword. However, random code selection is also an efficient technique by considering mathematicalcomplexity during data encoding and decoding. In coding theory, achieving better coding performance is still remains a challenging issue for researchers. In order to address this issue various techniques have been proposed such as LDPC (Low-Density Parity Check) [1], turbo coding[2] etc. Another challenging issue is known as practical implementation of these coding schemes for real time application scenarios.In coding theory, coding randomness is an issue which affects the performance of communication which is introduced in turbo code due to interleavers connected between check nodes and variable nodes while considering LDPC. In order to achieve reliable and efficient decoding, turbo codes utilized BCJR algorithm and LDPC uses belief propagation approach. These methods improve the performance and due to better performance requirements it is adopted in WCDMA, LTE and 3GPP standards. These methods still suffer from the capacity to achieve joint AEP when communic...