Distance-based-decoding of block turbo codes

List-based algorithms for. decoding block turbo Codes (BTC) have gained popularity due to their low computational complexity. The normal way to calculate the soft outputs involves searching for a decision code word D and a competing codeword B. In addition, a scaling factor /spl alpha/ and an estimated reliability value /spl beta/ are used. In this letter, we present a new approach that does not require /spl alpha/ and /spl beta/. Soft outputs are generated based on the Euclidean distance property of decision code words. By using the new algorithm, we achieve better error performance with even less complexity-for certain BTCs.