Interpreting the new dimensions after PCA I have telecom data with large number of dimentions. Now if I apply dimentionality reduction like PCA then from resulting dimention say PC1, PC2 I would loose the meaning or would not understand what they represent.

Are their any techniques other than PCA which can provide any meaning or intution about the new dimentions. Also suggest if there are any research papers in this.
To give meaning to the Axis of the PCA, you can study the scalar product between the two new axes and all your original axes (you have to normalise the vectors before doing that). 

Those axes with a high scalar product will be highly associated the with the new axes and viceversa. This may help you interpret them.