TY - GEN
T1 - Energy cooperation in renewable- powered cell-free massive MIMO systems
AU - Hamdi, R.
AU - Qaraqe, M.
PY - 2019/3/9
Y1 - 2019/3/9
N2 - We investigate in this paper the energy efficiency of cell-free massive MIMO systems made up of a set of distributed access points, each of which is powered by both an independent energy harvesting source and the grid. The grid energy source allows to compensate for the randomness and intermittency of the harvested energy. Moreover, we enable this system with energy exchange capabilities through a smart-grid infrastructure in order to enhance the energy efficiency of massive MIMO systems. Indeed, the problem of minimizing the grid power consumption has to be solved by efficiently managing the energy delivered from different sources while satisfying the system requirements in terms of users' quality of service demands. First, the optimal offline energy cooperation and management problem is solved using linear programming. Next, we investigate the online energy cooperation and management problem by proposing an efficient online algorithm based on energy prediction. Simulations results shows that the proposed energy cooperation and management approaches offer efficient use of non-renewable energy to compensate the variability of renewable energy in cell-free MIMO systems.
AB - We investigate in this paper the energy efficiency of cell-free massive MIMO systems made up of a set of distributed access points, each of which is powered by both an independent energy harvesting source and the grid. The grid energy source allows to compensate for the randomness and intermittency of the harvested energy. Moreover, we enable this system with energy exchange capabilities through a smart-grid infrastructure in order to enhance the energy efficiency of massive MIMO systems. Indeed, the problem of minimizing the grid power consumption has to be solved by efficiently managing the energy delivered from different sources while satisfying the system requirements in terms of users' quality of service demands. First, the optimal offline energy cooperation and management problem is solved using linear programming. Next, we investigate the online energy cooperation and management problem by proposing an efficient online algorithm based on energy prediction. Simulations results shows that the proposed energy cooperation and management approaches offer efficient use of non-renewable energy to compensate the variability of renewable energy in cell-free MIMO systems.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-85082950092&partnerID=MN8TOARS
U2 - 10.1109/APCC47188.2019.9026523
DO - 10.1109/APCC47188.2019.9026523
M3 - Published conference contribution
SP - 305
EP - 309
BT - Proceedings of 2019 25th Asia-Pacific Conference on Communications, APCC 2019
ER -
