@InProceedings{7760316,
  author = {A. Arafa and O. Kaya and S. Ulukus},
  booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},
  title = {Energy harvesting cooperative multiple access channel with decoding costs},
  year = {2016},
  pages = {587-591},
  abstract = {We consider an energy harvesting cooperative multiple access channel (MAC) with decoding costs. In this setting, users cooperate at the physical layer (data cooperation) in order to increase the achievable rates. Data cooperation comes at the expense of decoding costs: each user spends some amount of its harvested energy to decode the message of the other user, before forwarding both messages to the receiver. The decoding power spent is an increasing convex function of the incoming message rate. We characterize the optimal power scheduling policies that achieve the boundary of the maximum departure region subject to energy causality constraints and decoding costs by using a generalized water-filling algorithm.},
  keywords = {convex programming;cooperative communication;decoding;energy harvesting;multi-access systems;multiuser channels;telecommunication scheduling;wireless channels;energy harvesting cooperative multiple access channel;decoding cost;MAC;physical layer;data cooperation;receiver;convex function;optimal power scheduling policy;maximum departure region boundary;energy causality constraint;generalized water-filling algorithm;Decoding;Silicon;Energy harvesting;Receivers;Europe;Signal processing;Convex functions},
  doi = {10.1109/EUSIPCO.2016.7760316},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570255886.pdf},
}

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Data cooperation comes at the expense of decoding costs: each user spends some amount of its harvested energy to decode the message of the other user, before forwarding both messages to the receiver. The decoding power spent is an increasing convex function of the incoming message rate. We characterize the optimal power scheduling policies that achieve the boundary of the maximum departure region subject to energy causality constraints and decoding costs by using a generalized water-filling algorithm.","keywords":"convex programming;cooperative communication;decoding;energy harvesting;multi-access systems;multiuser channels;telecommunication scheduling;wireless channels;energy harvesting cooperative multiple access channel;decoding cost;MAC;physical layer;data cooperation;receiver;convex function;optimal power scheduling policy;maximum departure region boundary;energy causality constraint;generalized water-filling algorithm;Decoding;Silicon;Energy harvesting;Receivers;Europe;Signal processing;Convex functions","doi":"10.1109/EUSIPCO.2016.7760316","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2016/papers/1570255886.pdf","bibtex":"@InProceedings{7760316,\n author = {A. Arafa and O. Kaya and S. Ulukus},\n booktitle = {2016 24th European Signal Processing Conference (EUSIPCO)},\n title = {Energy harvesting cooperative multiple access channel with decoding costs},\n year = {2016},\n pages = {587-591},\n abstract = {We consider an energy harvesting cooperative multiple access channel (MAC) with decoding costs. In this setting, users cooperate at the physical layer (data cooperation) in order to increase the achievable rates. Data cooperation comes at the expense of decoding costs: each user spends some amount of its harvested energy to decode the message of the other user, before forwarding both messages to the receiver. The decoding power spent is an increasing convex function of the incoming message rate. 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