TY - JOUR
T1 - Optimal transmission schemes for parallel and fading Gaussian broadcast channels with an energy harvesting rechargeable transmitter
AU - Ozel, Omur
AU - Yang, Jing
AU - Ulukus, Sennur
N1 - Funding Information:
This work was supported by NSF Grants CCF 07-29127 , CNS 09-64632 , CCF 09-64645 , CCF 10-18185 and presented in part at the Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, November, 2011 and at the IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), San Juan, Puerto Rico, December 2011.
PY - 2013/7/1
Y1 - 2013/7/1
N2 - We consider an energy harvesting transmitter sending messages to two users over parallel and fading Gaussian broadcast channels. Energy required for communication arrives (is harvested) at the transmitter and a finite-capacity battery stores it before being consumed for transmission. Under off-line knowledge of energy arrival and channel fading variations, we obtain the trade-off between the performances of the users by characterizing the maximum departure region in a given interval. We first analyze the transmission with an energy harvesting transmitter over parallel broadcast channels. We show that the optimal total transmit power policy that achieves the boundary of the maximum departure region is the same as the optimal policy for the non-fading broadcast channel, which does not depend on the priorities of the users, and therefore is the same as the optimal policy for the non-fading scalar single-user channel. The optimal total transmit power can be found by a directional water-filling algorithm. The optimal splitting of the power among the parallel channels is performed in each epoch separately. Next, we consider fading broadcast channels and obtain the transmission policies that achieve the boundary of the maximum departure region. The optimal total transmit power allocation policy is found using a specific directional water-filling algorithm for fading broadcast channels. The optimal power allocation depends on the priorities of the users unlike in the case of parallel broadcast channels. Finally, we provide numerical illustrations of the optimal policies and maximum departure regions for both parallel and fading broadcast channels.
AB - We consider an energy harvesting transmitter sending messages to two users over parallel and fading Gaussian broadcast channels. Energy required for communication arrives (is harvested) at the transmitter and a finite-capacity battery stores it before being consumed for transmission. Under off-line knowledge of energy arrival and channel fading variations, we obtain the trade-off between the performances of the users by characterizing the maximum departure region in a given interval. We first analyze the transmission with an energy harvesting transmitter over parallel broadcast channels. We show that the optimal total transmit power policy that achieves the boundary of the maximum departure region is the same as the optimal policy for the non-fading broadcast channel, which does not depend on the priorities of the users, and therefore is the same as the optimal policy for the non-fading scalar single-user channel. The optimal total transmit power can be found by a directional water-filling algorithm. The optimal splitting of the power among the parallel channels is performed in each epoch separately. Next, we consider fading broadcast channels and obtain the transmission policies that achieve the boundary of the maximum departure region. The optimal total transmit power allocation policy is found using a specific directional water-filling algorithm for fading broadcast channels. The optimal power allocation depends on the priorities of the users unlike in the case of parallel broadcast channels. Finally, we provide numerical illustrations of the optimal policies and maximum departure regions for both parallel and fading broadcast channels.
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U2 - 10.1016/j.comcom.2012.04.010
DO - 10.1016/j.comcom.2012.04.010
M3 - Article
AN - SCOPUS:84879841703
SN - 0140-3664
VL - 36
SP - 1360
EP - 1372
JO - Computer Communications
JF - Computer Communications
IS - 12
ER -