# An Improved Channel Estimation Technique for IEEE 802.11p Standard in Vehicular Communications
## 4 The Proposed Scheme
The reason behind the construction of the phase tracking pilots is to get more information for the comparison block. The process flow chart of the proposed channel estimator algorithm is shown in Figure 5. It is clear from the process flowchart in Figure 5 that the time domain signal in Figure 4 is now converted to the frequency domain by taking the 64 points FFT. Then the LS estimation is performed on this signal using Equation (1). As stated earlier, the next task is to perform the equalization to get a rough estimate of the transmitted LTS. The initial Data pilots are created and then again LS estimation is performed which is based on the constructed data pilots. Figure 4: Transmitted and Received IEEE 802.11p packet. Since the adjacent subcarriers to the phase tracking pilots have a higher correlation with them, so the constructed phase tracking pilots and the originally known phase tracking pilots are compared to decide the channel response in those regions, which helps in improving the accuracy of the overall system. In the CDP estimation scheme, the assistance of demapping is used to partially alleviate the impact of noise from the other interferences. Then, the remaining error is further reduced by exploiting the correlation characteristics of the channel for the two adjacent symbols. The constructed data pilot \(\hat{X}_{i}(k)\) in [5] are then employed to obtain the \(i\)th data symbol's channel response by using the Equation (3). We further investigated that even though \(H_{i}(k)\) is a relatively accurate estimate of the channel response, however, it is can be improved by exploiting the high correlation characteristics of the channel. Therefore, \(H_{i}(k)\) is used to equalize \(S_{R,i-1}(k)\) in Equation (7). \[\hat{S^{\prime}}_{C,i-1}(k)=\frac{S_{R,i-1}(k)}{H_{i}(k)} \tag{7}\]  
Again, the \(S_{R,i-1}(k)\) is then equalized by \(H_{CDP,i-1}(k)\), i.e., the previous symbol's estimated CR, which has been used before in Equation (6). In order to make a comparison, \(S_{R,i-1}(k)\) is also equalized by the \(H_{CDP,i-1}(k)\) and the resulting equalized \(\hat{S^{\prime\prime}}_{C,i-1}(k)\) is given by Equation (8). \[\hat{S^{\prime\prime}}_{C,i-1}(k)=\frac{S_{R,i-1}(k)}{H_{CDP,i-1}(k)} \tag{8}\]  
The one to one comparison of \(\hat{S^{\prime}}_{C,i-1}(k)\) and \(\hat{S^{\prime\prime}}_{C,i-1}(k)\) is made by appropriately demapping them to their respective constellation points \(\hat{X}^{\prime}_{i}(k)\) and \(\hat{X^{\prime\prime}}_{i}(k)\). The proposed demapping process starts by using constellation demodulation of \(\hat{S^{\prime}}_{C,i-1}(k)\) and \(\hat{S^{\prime\prime}}_{C,i-1}(k)\), using the information from the standard IEEE 802.11 modulation coding scheme (MCS) table. Let us take the case of _mcs_ = 2, so that after the demodulation the \(\hat{S^{\prime}}_{C,i-1}(k)\) is now represented by \(\hat{S^{\prime}}_{C,dn,i-1}(k)\) and \(\hat{S^{\prime\prime}}_{C,i-1}(k)\) is represented by \(\hat{S^{\prime\prime}}_{Cdn,i-1}(k)\). For this particular configuration, \(\hat{S^{\prime}}_{Cdn,i-1}(k)\) can take four different values represented by \((n=1,2,3,4)\) Equation (9) to Equation (12). \[\hat{S^{\prime}}_{Cd1,i-1}(k)\approx\frac{1}{\sqrt{2}}+\frac{i}{\sqrt{2}} \tag{9}\]  
\[\hat{S^{\prime}}_{Cd2,i-1}(k)\approx\frac{1}{\sqrt{2}}-\frac{i}{\sqrt{2}} \tag{10}\]  
Figure 3:0Figure 3:1 Process flow of the proposed algorithm. Let say \(P1\), \(P2\), \(P3\), and \(P4\) represent the values \(\frac{1}{\sqrt{2}}+\frac{i}{\sqrt{2}}\), \(\frac{1}{\sqrt{2}}-\frac{i}{\sqrt{2}}\), \(-\frac{1}{\sqrt{2}}+\frac{i}{\sqrt{2}}\), and \(-\frac{1}{\sqrt{2}}-\frac{i}{\sqrt{2}}\) respectively. In order to choose the best value, we need to take the absolute difference of \(\hat{S}^{\prime}{}_{Cdn,i-1}(k)\) (where \(n\) can take any value from \(1\) to \(4\)) from \(P1\), \(P2\), \(P3\), and \(P4\) to get \(G1\), \(G2\), \(G3\), and \(G4\) as shown in Equation (13). Figure 3:2  
Then the argument or index of the minimum value from \(G1,G2,G3,G4\) is selected as shown in Equation (14).