Doubly-Selective Multiuser Channel Estimation using Superimposed Training and Discrete Prolate Spheroidal Basis Expansion Models

Channel estimation for multiuser doubly-selective channels is considered using superimposed training. The time-varying channel is assumed to be described by a discrete prolate spheroidal basis expansion model (DPS-BEM). A user-specific periodic training sequence is arithmetically added (superimposed) at a low power to each user's information sequence at the transmitter before modulation and transmission. A two step approach is adopted where in the first step we estimate the channel using only the first-order statistics of the observations. Using the estimated channel from the first step, a Viterbi detector is used to estimate the information sequence. In the second step a deterministic maximum likelihood (DML) approach is used to iteratively estimate the multiuser channel and the information sequences sequentially.

[1]  D. Slepian.  Prolate spheroidal wave functions, fourier analysis, and uncertainty — V: the discrete case , 1978, The Bell System Technical Journal.

[2]  Mounir Ghogho,et al.  SISO and MIMO channel estimation and symbol detection using data-dependent superimposed training , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

[3]  Jitendra K. Tugnait,et al.  MIMO channel estimation using superimposed training , 2004, 2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577).

[4]  Stephen A. Dyer,et al.  Digital signal processing , 2018, 8th International Multitopic Conference, 2004. Proceedings of INMIC 2004..

[5]  Georgios B. Giannakis,et al.  Optimal training for block transmissions over doubly-selective fading channels , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  T. Zemen,et al.  Time-variant channel estimation using discrete prolate spheroidal sequences , 2005, IEEE Transactions on Signal Processing.

[7]  X. Meng,et al.  Doubly-selective MIMO channel estimation using superimposed training , 2004, Processing Workshop Proceedings, 2004 Sensor Array and Multichannel Signal.

[8]  Jitendra K. Tugnait,et al.  SPC02-3: Doubly-Selective Channel Estimation Using Superimposed Training and Discrete Prolate Spheroidal Basis Models , 2006, IEEE Globecom 2006.

[9]  Georgios B. Giannakis,et al.  Maximum-diversity transmissions over doubly selective wireless channels , 2003, IEEE Transactions on Information Theory.

[10]  Georgios B. Giannakis,et al.  Optimal training for block transmissions over doubly selective wireless fading channels , 2003, IEEE Trans. Signal Process..