The paper deals with detection of encoded discrete data transmitted over band-limited Gaussian channels with unknown parameters. The problem is to detect the data sequence and at the same time estimate the channel parameters such that the output from the decoder is as reliable as possible. Maximum likelihood (ML) detection fulfils this goal but, unfortunately, it leads to non-recursive and computationally complex algorithms. The approach taken in the present paper is to use the trellis corresponding to the combined states of the encoder and the channel. A modified Viterbi algorithm is then used. Simulation results show that when the channel is time-invariant and noisy, data can be detected with only 0.5 [dB] loss compared to ML-detection with the channel known to the receiver. The algorithm also performs well when the channel is time-varying. Compared to algorithms performing channel detection and decoding separately, the new algorithm is more complex but the performance loss is lower.<<ETX>>
[1]
N. Seshadri,et al.
Joint data and channel estimation using fast blind trellis search techniques
,
1990,
[Proceedings] GLOBECOM '90: IEEE Global Telecommunications Conference and Exhibition.
[2]
Gottfried Ungerboeck,et al.
Channel coding with multilevel/phase signals
,
1982,
IEEE Trans. Inf. Theory.
[3]
G. David Forney,et al.
Maximum-likelihood sequence estimation of digital sequences in the presence of intersymbol interference
,
1972,
IEEE Trans. Inf. Theory.
[4]
John G. Proakis,et al.
A 'quantized' channel approach to blind equalization
,
1992,
[Conference Record] SUPERCOMM/ICC '92 Discovering a New World of Communications.
[5]
Jr. G. Forney,et al.
The viterbi algorithm
,
1973
.