On the error probability of general trellis codes with applications to sequential decoding

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of randomL-branch binary trellis codes of rateR = 1/nis given which separates the effects of the tail lengthTand the memory lengthMof the code. It is shown that the bound is independent of the lengthLof the information Sequence whenM geq T + [nE_{VU}(R)]^{-1} log_{2} L. The implication that the actual error probability behaves similarly is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication which can thus be taken as a design rule for choosingMso that the error probability is reduced to its minimum value for a givenT

Maximal Capacity Partial Response Signaling

In this paper we investigate partial response signaling (PRS) systems that are intended to operate close to capacity. We show that finding PRS systems with maximal capacity is a rather easy optimization task. We give an alternate way of defining bandwidth for PRS systems based on capacity considerations; this differs considerably from the traditional method based on transmission power. Practical PRS schemes are derived, based on these ideas. Their bit error rate is significantly better than earlier, distance-optimizing schemes

Digital processing of signals in the presence of inter-symbol interference and additive noise

Imperial Users onl