Abstract: A cellular network traffic prediction algorithm based on Threshold Regularized Orthogonal Matching Pursuit (BT-ROMP) is proposed to solve the problem of cellular network energy waste, where Bases transmitted power cannot be effectively adjusted according to the peak flow rate in cells. The block sparse model of cellular traffic is constructed by using the characteristics of periodic and stable changes. And the algorithm uses the threshold to effectively screen the suboptimal atoms which are regularized, and to expand the candidate set to reduce the number of iterative times and improve the accuracy of the reconstruction. Simulation results show that compared with regularized orthogonal matching pursuit algorithm (ROMP), the prediction accuracy of the proposed algorithm can be improved by 0.01 on average.

Key words: cellular traffic prediction, block sparsity, space-time compressed sensing, regularized orthogonal matching pursuit algorithm