Realization of Capacity Effects on Polar Codes and Simplified Successive Cancellation Decoding with GA Approach

Polar code (PC) innovation has drawn attention from businesses and academics over the decade, especially in the communication sector. The fifth-generation wireless standard (5G) uses polar codes as a coding technique. Concerning short- to intermediate or long-length codes, the polar decoding fails to repair errors in successive cancellation (SC) decoding sufficiently. Still, by employing successive cancellation list (SCL) decoding, SC decoding can more effectively rectify errors. The main disadvantage of SCL is its increased cost driven by throughput and computational complexity. Building polar codes over an AWGN channel with little computational cost remains an ongoing research issue. Therefore, to address the shortcomings of the SC/SCL decoders, the Simplified successive cancellation (SSC) decoder of polar codes with an improved Gaussian Approximation (GA) technique over an additive white Gaussian noise (AWGN) channel is proposed in this work. Compared to the density evolution technique, the SSC decoder with GA will more easily trace the mean log-likelihood ratio (LLR). The SSC decoder is examined using a GA technique at high and low code rates and lengths. The capacity effects of PCs concerning performance metrics like bit error rate (BER) and block error rate (BLER) are realized in detail at various code lengths. The proposed work is compared with conventional Huawei approximation (HA) and other decoding with better improvement in BER and BLER.