Signal detection through circular convolution reconstruction for OFDM system in fast varying channel

A signal detection algorithm is proposed for the orthogonal frequency division multiplexing （OFDM） sys- tem in the presence of fast time-varying channel. The channel is represented by a piece-wise linear variant model with normalized Doppler frequency of less than 0.2. The channel parameters are extracted through ISI/ICI （inter-symbol in- terference/inter-carrier interference） cancellation and circular convolution reconstruction. Meanwhile, an improved OFDM symbol detection algorithm is also proposed based on circular convolution reconstruction. The channel state in- formation in the OFDM symbol duration can be obtained accurately from the adjacent two block pilots in a linear model. The simulation results show that the proposed method can not only track the channel variation, but also promise better performance gain in the OFDM symbol detection. Furthermore, the bit error ratio （BER） is close to the perform- ance with the perfect channel state information.

Dynamics of 18 (<i>Sophora japonica</i>) Tree Community’s Crown Volume along Elevation Gradient in <i>Ye County</i>

Applying plant community diversity techniques and SPSS statistic analysis, we quantified the relationship between crown volume of 18 (Sophora japonica) tree communities and elevation along different elevation gradient in Ye County in the study. We concluded that there was a significantly positive correlation between crown volume of 18 (Sophora japonica) tree communities and elevation gradient (P Sophora japonica) tree communities increased along elevation from 50 m to 200 m in Ye County in 2018. Therefore, understanding dynamic connecting crown volume of 18 (Sophora japonica) communities and elevation can be not just applied to preserve of (Sophora japonica) tree communities, but also applied to sustainable of biodiversity and processes of tree community’s crown volume along elevation.