Abstract
This thesis considers semiblind maximum-likelihood (ML) detection of orthogonal space-time block coded OFDM (OSTBC-OFDM) systems within one OSTBC-OFDM block. Chang et al. [5] have shown an interesting channel identifiability result, that the whole time-domain multiple-input multiple-output (MIMO) channel can be uniquely identified in the noise-free situation by only using one of the subchannels to transmit pilots. However, this identifiability condition is in a probability-one sense relying on some mild assumptions on the channel statistics. In this thesis, through judicious use of so-called non-intersecting subspace OSTBCs and pilots over a small amount of subchannels, we establish a “perfect” channel identifiability (PCI) condition under which the channel is uniquely identifiable. The proposed scheme has the total number of pilots larger than that used in the previous probability-one identifiability achieving scheme, but smaller than that required in conventional pilot-aided channel estimation schemes. Also, it is shown that, in additive Gaussian noise and independent and identically distributed Rayleigh fading channels, the semiblind ML detector using the proposed PCI achieving scheme can achieve the same full spatial diversity as the coherent ML receiver. For the application in distributed (cooperative) space-time coding systems, we also extend the semiblind ML detector and the proposed PCI achieving scheme to that for a distributed OSTBC-OFDM scenario. Simulation results are presented to show that the proposed scheme can provide better performance than some existing schemes in both point-to-point and distributed OSTBC-OFDM systems.