A new orthogonal-diagonal steel open-web sandwich floor system has been developed by the authors in the past few years to replace the conventional methodology. This floor system owns excellent structural mechanical characteristics to be applied in civil engineering applications. The three-dimensional structural characteristics are achieved by letting the top and bottom chords of the space truss that constitutes the floor inclined 45° toward the edge of the boundary lines. The present work focuses on the fabrication and erection of the proposed floor and its structural behavior subjected to partial loadings. Field partially-loaded test was conducted and the performance was evaluated in terms of the deflection distribution and stress response at different load levels. A three-dimensional numerical finite element model was developed and calibrated against the test results. The results demonstrate that the new floor system offers satisfactory structural performance.

To reduce the influence of wireless transmission channel on transform domain communication system (TDCS) and improve the channel estimation accuracy, a system model of Least Square (LS) channel estimation on TDCS is established. In this paper, the influence of the unavailable frequency existing in basic function is analysed for the LS channel estimation, then the expression of mean square error (MSE) is derived. After that, the frequency pilot insertion pattern and the interpolation algorithm suitable for TDCS is proposed. The simulation results verify the paper’s theoretical analysis, and the effectiveness of the proposed algorithm is proved by the comparison of the MSE and BER performance.

In order to solve the problem that the wideband compressive sensing reconstruction algorithm cannot accurately recover the signal under the condition of blind sparsity in the low SNR environment of the transform domain communication system. This paper use band occupancy rates to estimate sparseness roughly, at the same time, use the residual ratio threshold as iteration termination condition to reduce the influence of the system noise. Therefore, an ICoSaMP(Improved Compressive Sampling Matching Pursuit) algorithm is proposed. The simulation results show that compared with CoSaMP algorithm, the ICoSaMP algorithm increases the probability of reconstruction under the same SNR environment and the same sparse degree. The mean square error under the blind sparsity is reduced.

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