Uncoded image transmission in cognitive radio systems

In this paper, we consider robust uncoded image transmission in cognitive radio systems, where the secondary user initially performs channel sensing with possible sensing errors in the form of false alarms and miss detections, and then sends image data to the secondary receiver with two power levels depending on the sensing decisions (e.g., idle or busy). It is assumed that two dimensional (2-D) Discrete Cosine Transform (DCT) is applied to the image and the resulting DCT coefficients are directly transmitted through the wireless channel under sensing uncertainty. At the secondary receiver, DCT coefficients are first estimated via linear minimum mean square error (LMMSE) or MMSE estimation, then the received image is reconstructed. In this setting, the optimal power levels that minimize the mean squared error (MSE) of LMMSE estimation are obtained subject to average transmit power and average interference power constraints. Also, a low-complexity power control algorithm is proposed. The impact of imperfect sensing decisions and power constraints on the performance of uncoded image transmission in cognitive radio systems is analyzed through simulations. In addition, the performances of estimating DCT coefficient by using MMSE and LMMSE are compared.