TY - GEN
T1 - Energy management in large-scale MIMO systems with per-antenna energy harvesting
AU - Hamdi, R.
AU - Driouch, E.
AU - Ajib, W.
PY - 2017
Y1 - 2017
N2 - This paper investigates the downlink of an energy efficient distributed large-scale MIMO system. The studied system is assumed to be made up of a set of remote radio heads (RRHs), each of which is powered by both an independent energy harvesting source and the grid. The grid energy allows to compensate for the randomness and intermittency of the harvested energy. Hence, the problem of grid power consumption minimization under quality of service (QoS) constraints has to be solved. First, this paper solves the optimal offline version of the problem using linear programming. Next, an iterative link removal algorithm is proposed in order to ensure the feasibility of the problem. Finally, the optimal online energy management algorithm is also proposed to solve the same problem. Simulation results show the performance of the proposed algorithms. The proposed approach in this paper allows efficient use of non-renewable energy to compensate the variability of renewable energy in large-scale MIMO systems.
AB - This paper investigates the downlink of an energy efficient distributed large-scale MIMO system. The studied system is assumed to be made up of a set of remote radio heads (RRHs), each of which is powered by both an independent energy harvesting source and the grid. The grid energy allows to compensate for the randomness and intermittency of the harvested energy. Hence, the problem of grid power consumption minimization under quality of service (QoS) constraints has to be solved. First, this paper solves the optimal offline version of the problem using linear programming. Next, an iterative link removal algorithm is proposed in order to ensure the feasibility of the problem. Finally, the optimal online energy management algorithm is also proposed to solve the same problem. Simulation results show the performance of the proposed algorithms. The proposed approach in this paper allows efficient use of non-renewable energy to compensate the variability of renewable energy in large-scale MIMO systems.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85028315227&partnerID=MN8TOARS
U2 - 10.1109/ICC.2017.7996695
DO - 10.1109/ICC.2017.7996695
M3 - Published conference contribution
BT - 2017 IEEE International Conference on Communications (ICC)
PB - IEEE Explore
ER -
