Dynamic Resource Allocation for Smart-Grid Powered MIMO Downlink Transmissions

Xin Wang, Tianyi Chen, Xiaojing Chen, Xiaolin Zhou, Georgios B. Giannakis

16 Scopus citations

Abstract

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.

Original languageEnglish (US)
Article number7544445
Pages (from-to)3354-3365
Number of pages12
JournalIEEE Journal on Selected Areas in Communications
Volume34
Issue number12
DOIs
StatePublished - Dec 2016

Keywords

  • MIMO broadcast channels
  • renewable energy sources
  • smart grids
  • stochastic optimization

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