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In this paper, channel estimation and data detection for multihop relayingorthogonal frequency division multiplexing (OFDM) system is investigated undertime-varying channel. Different from previous works, which highly depend on thestatistical information of the doubly-selective channel (DSC) and noise todeliver accurate channel estimation and data detection results, we focus onmore practical scenarios with unknown channel orders and Doppler frequencies.Firstly, we integrate the multilink, multihop channel matrices into onecomposite channel matrix. Then, we formulate the unknown channel usinggeneralized complex exponential basis expansion model (GCE-BEM) with a largeoversampling factor to introduce channel sparsity on delay-Doppler domain. Toenable the identification of nonzero entries, sparsity enhancing Gaussiandistributions with Gamma hyperpriors are adopted. An iterative algorithm isdeveloped under variational inference (VI) framework. The proposed algorithmiteratively estimate the channel, recover the unknown data using Viterbialgorithm and learn the channel and noise statistical information, using onlylimited number of pilot subcarrier in one OFDM symbol. Simulation results showthat, without any statistical information, the performance of the proposedalgorithm is very close to that of the optimal channel estimation and datadetection algorithm, which requires specific information on system structure,channel tap positions, channel lengths, Doppler shifts as well as noise powers.

Joint Channel Estimation and Data Detection for Multihop OFDM Relaying System under Unknown Channel Orders and Doppler Frequencies