  In this paper we propose a new soft-input soft-output equalization algorithm,
offering very good performance/complexity tradeoffs. It follows the structure
of the BCJR algorithm, but dynamically constructs a simplified trellis during
the forward recursion. In each trellis section, only the M states with the
strongest forward metric are preserved, similar to the M-BCJR algorithm. Unlike
the M-BCJR, however, the remaining states are not deleted, but rather merged
into the surviving states. The new algorithm compares favorably with the
reduced-state BCJR algorithm, offering better performance and more flexibility,
particularly for systems with higher order modulations.
