Finite-Horizon Energy-Efficient Scheduling With Energy Harvesting Transmitters Over Fading Channels


Creative Commons License

BACINOĞLU B. T., UYSAL BIYIKOĞLU E., Koksal C. E.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, cilt.16, sa.9, ss.6105-6118, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 16 Sayı: 9
  • Basım Tarihi: 2017
  • Doi Numarası: 10.1109/twc.2017.2718544
  • Dergi Adı: IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.6105-6118
  • Anahtar Kelimeler: Energy-efficient communication, throughput maximization, energy harvesting transmitters, energy harvesting, energy causality, data causality, water-filling, time-varying channels, stochastic dynamic programming, offline scheduling, online scheduling, COMMUNICATION-SYSTEM, DELAY CONSTRAINTS, TRANSMISSION, ALLOCATION, NETWORKS, POLICIES, NODES, LINK
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

In this paper, energy-efficient transmission schemes achieving maximal throughput over a finite time interval are studied in a problem setting, including energy harvests, data arrivals, and channel variation. The goal is to express the offline optimal policy in a way that facilitates a good online solution. We express any throughput maximizing energy-efficient offline schedule (EE-TM-OFF) explicitly in terms of water levels. This allows per-slot real-time evaluation of transmit power and rate decisions, using estimates of the associated offline water levels. To compute the online power level, we construct a stochastic dynamic program that incorporates the offline optimal solution as a stochastic process. We introduce the immediate fill measure, which provides a lower bound on the efficiency of any online policy with respect to the corresponding optimal offline solution. The online algorithms obtained this way exhibit performance close to the offline optimal, not only in the long run but also in short problem horizons, deeming them suitable for practical implementations.