We adopt the concept of channel diagonalization to time-frequency signal expansions obtained by DFT filter banks. As a generalization of the frequency domain channel representation used by conventional orthogonal frequency-division multiplexing receivers, the time-frequency domain channel diagonalization can be applied to time-variant channels and aperiodic signals. An inherent error in the case of doubly dispersive channels can be limited by choosing adequate windows underlying the filter banks. We derive a formula for the mean-squared sample error in the case of wide-sense stationary uncorrelated scattering (WSSUS) channels, which serves as objective function in the window optimization. Furthermore, an enhanced scheme for the parameterization of tight Gabor frames enables us to constrain the window in order to define paraunitary filter banks. We show that the design of windows optimized for WSSUS channels with known statistical properties can be formulated as a convex optimization problem. The performance of the resulting windows is investigated under different channel conditions, for different oversampling factors, and compared against the performance of alternative windows. Finally, a generic matched filter receiver incorporating the proposed channel diagonalization is discussed which may be essential for future reconfigurable radio systems.

There is a trend towards flexible radios which are able to cope with a range of wireless communication standards. For the integrated processing of widely different signals-including single-carrier, multicarrier, and spread-spectrum signals-monolithic baseband receivers need universal formats for the signal representation and channel description. We consider a reconfigurable receiver architecture building on concepts from time-frequency (TF) signal analysis. The core elements are TF signal representations in form of a Gabor expansion along with a compatible parameterization of time-variant channels. While applicable to arbitrary signal types, the TF channel parameterization offers similar advantages as the frequency domain channel description employed by orthogonal frequencydivision multiplexing receivers. The freedom in the choice of the underlying analysis window function and the scalability in time and frequency facilitate the handling of diverse signal types as well as the adaptation to radio channels with different delay and Doppler spreads. Optimized window shapes limit the inherent model error, as demonstrated using the example of direct-sequence spread-spectrum signaling.

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