Comparison of convolutional and turbo coding for broadband FWA systems

It has been demonstrated that turbo codes substantially outperform other codes, e.g., convolutional codes, both in the non-fading additive white Gaussian noise (AWGN) channel as well as multiple-transmit and multiple-receive antenna fading channels. Moreover, it has also been reported that turbo codes perform very well in fast fading channels, but perform somewhat poorly on slow and block fading channels of which the broadband fixed wireless access (FWA) channel is an example. In this paper, we thoroughly compare the performance of turbo-coded and convolutional-coded broadband FWA systems both with and without antenna diversity under the condition of identical complexity for a variety of decoding algorithms. In particular, we derive mathematical expressions to characterize the complexity of turbo decoding based on state-of-the-art Log-MAP and Max-Log-MAP algorithms as well as convolutional decoding based on the Viterbi algorithm in terms of the number of equivalent addition operations. Simulation results show that turbo codes do not offer any performance advantage over convolutional codes in FWA systems without antenna diversity or FWA systems with limited antenna diversity. Indeed, turbo codes only outperform convolutional codes in FWA systems having significant antenna diversity.