# Optimized Polar Codes as Forward Error Correction Coding for Digital Video Broadcasting Systems
This detector proceeds the candidate codewords and feeds back again SCL decoder with check results. CA-SCL decoding technique for polar codes achieves nearly a similar performance as LDPC codes and turbo codes [23]. However, its computational complexity leads to higher latency and lower throughput. Recently, fast-adaptive CA-SCL decoders are proposed in [24], named Fully Adaptive SCL (FA-SCL), Partially Adaptive SCL (PA-SCL). Both of them use the CRC to reduce the decoding processing time by gradually increasing the list size \(L\). Using these decoding techniques for polar codes, a potential trade-off can be achieved between throughput, latency, and decoding performance over other channel coding techniques. Also, other channel coding techniques such as LDPC codes and turbo codes suffer from an error floor region [25]. On the contrary, polar codes do not show these error floors [26]. Therefore, polar codes with flexible, fast-adaptive SCL decoders can be used as an alternative for LDPC codes to enhance performance of wireless systems. Since the field of data communications continues to grow rapidly due to the ever-increasing use of video, this has led to the demand of new technologies such as 4K, 8K, virtual reality and augmented reality. Millions of set-top boxes, tablets and smartphones need efficient broadcasting and reception of TV programs with minimum access time, minimum hardware processing time, maximum throughput, and best performance. Accordingly, in this paper, we propose polar codes to be utilized in DVB systems. We propose to replace the LDPC inner coding and the BCH outer coding of DVB systems by polar codes to take advantages of the benefits in the new coding technique. The motivation in this paper is to enhance the performance of DVB systems using polar codes as FEC coding. To design an optimized polar code construction, a simple mathematical relation to get approximately the optimized SNR design point is proposed. The proposed relation avoids complex iterative calculations or long algorithms executions as in [27; 28]. In addition to this, the present paper has compared the performance of the proposed optimized polar codes with LDPC codes not only in terms BER performance as in [29], but in terms of other important aspects such as the decoding latency and system throughput. In this comparison, the recently proposed FA-SCL decoding technique [24] is utilized for polar codes to achieve the desired minimum decoding latency while maintaining the error-correction performance almost unchanged. According to the obtained results, we proposed using optimized polar codes with FA-SCL decoding technique in DVB systems to enhance the overall throughput and decrease the latency. Furthermore, we utilize long code lengths which are more efficient in terms of BER performance for any DVB system, in contrast to [30; 31; 32] which only use short code lengths in mobile communications for 4G Long Term Evolution (LTE) and 5G New Radio (NR) systems. The main novelty of our paper is proposing the optimized polar codes as FEC technique for DVB systems. To prove this, we make the following contributions: (1) We propose a new mathematical relation to get the optimized SNR design point for polar code construction. (2) We compare the optimized polar codes with LDPC codes using different code rates and showed the advantages and disadvantages in terms of encoder and decoder parameters. According to the simulation results, it is shown that polar codes have a superior performance than LDPC in terms of the decoding latency and the overall throughput. (3) We compare the optimized polar codes with LDPC and BCH codes in terms of BER, latency, throughput and proved that it can be proposed as a FEC coding technique instead of LDPC and BCH codes in wireless communication systems such as DVB systems. The rest of the paper is organized as follows: Section 2 briefly presents an overview of polar codes construction, encoding, decoding, and some related preliminaries. Section 3 presents a derivation to get the optimized design SNR.