Error probability for reduced-state sequence estimation

The performance of ideal reduced-state sequence estimation (RSSE) (without error propagation) is known as a good approximation to the performance of real RSSE. In the literature, the minimum distance of ideal RSSE has been employed for approximating the error probability of real RSSE. However, this approximation can be very poor, even though the system has a large signal-to-noise ratio. In this work, a union upper bound on the error probability for ideal RSSE is used to approximate the true error probability. This union bound provides a better approximation than the minimum distance. A new method based on a stack algorithm and a subset-error state diagram is proposed for calculating this union bound. The stack algorithm is employed because it provides a good tradeoff between computer memory and computing time.<
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