Energy-efficient Joint Power Allocation in Uplink Massive MIMO Cognitive Radio Networks with Imperfect CSI
Résumé
In this paper, a joint pilot and data power allocationproblem with max-min fair energy efficiency (EE) guaranteein the uplink massive multiple-input multiple-output (MIMO)cognitive radio networks (CRNs) is investigated. Given the fractionalobjective function, channel estimation errors, and interuserinterference, the joint allocation problem is formulated asa nonconvex and NP-hard problem. To tackle this, we transformthe original problem into its convex form by introducing auxiliaryvariables and variable substitution, then address it with the helpof the Lagrangian dual method. Since the optimization variablesare interrelated and interact on each other, it is difficult todirectly obtain the closed-form solution to this problem. To settlethis issue, we propose an alternately iterative algorithm to achievethe optimal power policy by a gradient-based adaption method,with its corresponding optimal Lagrangian multipliers obtainedby the subgradient method. Numerical results show that theproposed approach has the best minimum EE performance anddecent spectral efficiency (SE) performance. Besides, comparedto other schemes, significant saving in total transmit power andgood cognitive user (CU) fairness are achieved by the proposedalgorithm.