The linear reconstruction phase of analog-to-digital (A/D) conversion in signal processing is analyzed in quantizing finite frame expansions for R^d. The specific setting is a K-level first order Sigma-Delta quantization with step size delta. Based on basic analysis, the d-dimensional Euclidean 2-norm of quantization error of Sigma-Delta quantization with input of elements in R^d decays like O(1/N) as the frame size N approaches infinity; while the L-infinity norm of quantization error of Sigma-Delta quantization with input of bandlimited functions decays like O(T) as the sampling ratio T approaches zero. It has been, however, observed via numerical simulation that, with input of bandlimited functions, the mean square error norm of quantization error seems to decay like O(T^(3/2)) as T approaches zero. Since the frame size N can be taken to correspond to the reciprocal of the sampling ratio T, this belief suggests that the corresponding behavior of quantization error, namely O(1/N^(3/2)), holds in the setting of finite frame expansions in R^d as well. A number theoretic technique involving uniform distribution of sequences of real numbers and approximation of exponential sums is introduced to derive a better quantization error than O(1/N) as N tends to infinity. This estimate is signal dependent.