ML sequence estimation for long ISI channels with controllable complexity

Channels with long impulse response often arise in high-rate digital transmissions due to severe multipath. This necessitates sophisticated equalization at the receiver. On the other hand, exploiting the available multipath diversity improves bit error performance. To collect the full multipath diversity, computationally cumbersome maximum likelihood sequence estimation (MLSE) is required. Although the Viterbi algorithm (VA) for MLSE is more efficient than the exhaustive ML search, its complexity increases exponentially with the channel length, which varies with the propagation environment. Since the computational power of the receiver is limited, VA becomes infeasible for long channels. In this paper, we develop a transmission capable of handling relatively long channels. The transmitter controls the computational complexity of MLSE at the receiver by periodically inserting zeros within information-bearing symbols, depending on the channel length and the computational power of the receiver. The optimal MLSE with reduced complexity becomes available at the expense of reduced data rate.