TY - JOUR
T1 - Dynamic Resource Allocation for Smart-Grid Powered MIMO Downlink Transmissions
AU - Wang, Xin
AU - Chen, Tianyi
AU - Chen, Xiaojing
AU - Zhou, Xiaolin
AU - Giannakis, Georgios B.
N1 - Publisher Copyright:
© 1983-2012 IEEE.
PY - 2016/12
Y1 - 2016/12
N2 - Benefiting from technological advances in the smart grid era, next-generation multi-input multi-output (MIMO) communication systems are expected to be powered by renewable energy sources (RES) integrated in the distribution grid, thus realizing the vision of 'green communications.' However, penetration of renewables introduces variabilities in the traditional power system, making RES benefits achievable only after appropriately mitigating their inherently high variability, which challenges existing resource allocation strategies. Aligned with this goal, an infinite time-horizon resource allocation problem is formulated to maximize the time-Average MIMO downlink throughput, subject to a time-Average energy cost budget. By using the advanced time decoupling technique, a novel stochastic subgradient-based online control approach is developed for the resultant smart-grid powered communication system. It is established analytically that even without a priori knowledge of the independently and identically distributed (i.i.d.) processes involved such as channel coefficients, renewables, and electricity prices, the proposed online control algorithm is still able to yield a feasible and asymptotically optimal solution. Numerical results further demonstrate that the proposed algorithm also works well in non-i.i.d. scenarios, where the underlying randomness is highly correlated over time.
AB - Benefiting from technological advances in the smart grid era, next-generation multi-input multi-output (MIMO) communication systems are expected to be powered by renewable energy sources (RES) integrated in the distribution grid, thus realizing the vision of 'green communications.' However, penetration of renewables introduces variabilities in the traditional power system, making RES benefits achievable only after appropriately mitigating their inherently high variability, which challenges existing resource allocation strategies. Aligned with this goal, an infinite time-horizon resource allocation problem is formulated to maximize the time-Average MIMO downlink throughput, subject to a time-Average energy cost budget. By using the advanced time decoupling technique, a novel stochastic subgradient-based online control approach is developed for the resultant smart-grid powered communication system. It is established analytically that even without a priori knowledge of the independently and identically distributed (i.i.d.) processes involved such as channel coefficients, renewables, and electricity prices, the proposed online control algorithm is still able to yield a feasible and asymptotically optimal solution. Numerical results further demonstrate that the proposed algorithm also works well in non-i.i.d. scenarios, where the underlying randomness is highly correlated over time.
KW - MIMO broadcast channels
KW - renewable energy sources
KW - smart grids
KW - stochastic optimization
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U2 - 10.1109/JSAC.2016.2600543
DO - 10.1109/JSAC.2016.2600543
M3 - Article
AN - SCOPUS:85009739594
SN - 0733-8716
VL - 34
SP - 3354
EP - 3365
JO - IEEE Journal on Selected Areas in Communications
JF - IEEE Journal on Selected Areas in Communications
IS - 12
M1 - 7544445
ER -