Energy harvesting broadband communication systems with processing energy cost

Oner Orhan, Deniz Gündüz, Elza Erkip

Research output: Contribution to journalArticlepeer-review

Abstract

Communication over a broadband fading channel powered by an energy harvesting transmitter is studied. Assuming non-causal knowledge of energy/data arrivals and channel gains, optimal transmission schemes are identified by taking into account the energy cost of the processing circuitry as well as the transmission energy. A constant processing cost for each active sub-channel is assumed. Three different system objectives are considered: 1) throughput maximization, in which the total amount of transmitted data by a deadline is maximized for a backlogged transmitter with a finite capacity battery; 2) energy maximization, in which the remaining energy in an infinite capacity battery by a deadline is maximized such that all the arriving data packets are delivered; and 3) transmission completion time minimization, in which the delivery time of all the arriving data packets is minimized assuming infinite size battery. For each objective, a convex optimization problem is formulated, the properties of the optimal transmission policies are identified, and an algorithm which computes an optimal transmission policy is proposed. Finally, based on the insights gained from the offline optimizations, low-complexity online algorithms performing close to the optimal dynamic programming solution for the throughput and energy maximization problems are developed under the assumption that the energy/data arrivals and channel states are known causally at the transmitter.

Original languageEnglish (US)
Article number6825916
Pages (from-to)6095-6107
Number of pages13
JournalIEEE Transactions on Wireless Communications
Volume13
Issue number11
DOIs
StatePublished - Nov 1 2014

Keywords

  • Offline power optimization
  • online algorithms.
  • remaining energy maximization
  • throughput maximization
  • transmission completion time minimization

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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