Community-Based Sequential Paging for LTE-A Cellular Network

Human movement is strongly affected by the needs of humans to socialize or cooperate with each other, in one form or another, which results in some degree of clustering and correlation with their movements. In this paper, we exploit the movement correlations, and propose a new community-based sequential paging algorithm to reduce the paging signaling overhead. Our simulation results demonstrate that given the same location update scheme employed in the LTE-A network, the proposed algorithm is capable of reducing 20% of the paging messages in the best scenario when having high moving rate.