On Code Design for Wireless Channels with Additive Radar Interference This paper considers the problem of code design for a channel where communications and radar systems coexist, modeled as having both Additive White Gaussian Noise (AWGN) and Additive Radar Interference (ARI). The question of how to adapt or redesign convolutional codes (decoded by the Viterbi algorithm) and LDPC codes (decoded by the sumproduct algorithm and optimized by using the EXIT chart method) to effectively handle the overall nonGaussian ARI noise is investigated. Interestingly, it is found that codes optimized for AWGNonly noise and decoded using a decoding metric that accounts for both the SignaltoNoise Ratio (SNR) of the useful signal and the InterferencetoNoise Ratio (INR) of the radar signal is only slightly outperformed by codes that are optimized for the AWGNARI channel.

Comparing Decoding Performance of LDPC Codes and Convolutional Codes for Short Packet Transmission In the field of industrial automation research, wireless control in key application scenarios has become a research hotspot. Nevertheless, transmission over wireless channels in industrial environments is prone to interference, resulting in frequent erroneous packet deliveries. Forward Error Correction (FEC) code as an approach is able to effectively improve reliability and reduce the number of retransmissions. Therefore, channel coding needs further analysis to achieve better industrial wireless application. To this aim, this paper compares the decoding performance of convolutional codes and lowdensity paritycheck (LDPC) codes on the condition of short packet transmission. The metrics employed for evaluation are bit error rate (BER) and packet error rate (PER). The logarithmic belief propagation (LogBP) algorithm and the Viterbi decoding algorithm are adopted to LDPC codes and convolutional codes respectively. The results show that the decoding algorithm of LDPC codes is prominent in short packet transmission.