Ant colony‐based strategy to mitigate the pilot contamination problem in multicell massive multiple‐input multiple‐output systems

Abstract

AbstractDue to its ability to serve a large number of the user equipments (UEs), massive multiple‐input multiple‐output (mMIMO) technology has been elected to meet the requirement of the upcoming new five‐generation systems. Despite its advantages, mMIMO is still obstructed by the pilot contamination (PC) problem, which is birth from, simultaneously, reusing the same orthogonal pilot sequences (OPSs) across several cells. Due to the scarcity of the OPSs, it is necessary to properly allocate the available OPSs to the UEs. Specifically, the available OPSs should be assigned to the UEs while the severity of the PC problem, between the UEs that employ the same pilot sequences, remains as small as possible. To reach that goal, we have employed the ant colony‐based optimization (ACO) algorithm to find the best pattern in which the severity of the PC problem is reduced among all the UEs. In a nutshell, a graph that sizes the strength of the PC among the UEs is constructed; therefore, the ACO algorithm is employed to connect every two UEs that causes to each other the highest influence of the PC, therefore, the UEs are, successively, assigned with the available OPSs where the severity of the PC is significantly reduced.