On efficient multiplier-free implementation of channel estimation and equalization

In state-of-the-art digital communication systems, channel estimation and/or equalization is an indispensable part of the system. Due to limited resources, only relatively simple algorithms with low complexity can be applied for channel estimation and equalization in high data-rate systems. In fact, the complexity of these algorithms can become prohibitive for very high bit-rate applications, for example, several 100 Msymbols-per-second. We explore the signal constellation structure of practical digital communication systems and describe an efficient computation technique that not only eliminates multiplications but also minimizes the number of addition operations required to implement channel estimation algorithms such as the least mean squares (LMS) estimation and equalization algorithms such as the maximum likelihood (ML) sequence detection using the Viterbi algorithm. This new technique preserves the numerical precision of the algorithms while it reduces their complexity dramatically