TY - GEN
T1 - Joint base station assignment and power control in hybrid energy supply wireless networks
AU - Mao, Yuyi
AU - Zhang, Jun
AU - Letaief, K. B.
PY - 2015/6/17
Y1 - 2015/6/17
N2 - This paper addresses the joint base station (BS) assignment and power control problem in a hybrid energy supply wireless network, where an energy harvesting BS and a grid-powered BS coordinate to serve a mobile user. In order to minimize the grid energy consumption while maximizing the number of transmitted data packets, we introduce the total service cost over an N-block frame as the performance metric, which is the weighted sum of the grid energy cost and the packet drop cost. With non-causal side information (SI) available at the BSs, including energy SI and channel SI, a Greedy Assignment algorithm with low complexity and near optimal performance is proposed. For the causal SI setting, the design problem is formulated as a discrete Markov decision problem. Interesting solution structures are derived, which help develop an efficient monotone backward induction algorithm. To further reduce the complexity, a heuristic online policy is also proposed. Simulation results shall validate the effectiveness of the proposed policies and demonstrate a unique tradeoff in such networks, i.e., the tradeoff between the grid energy consumption and the provided quality of service.
AB - This paper addresses the joint base station (BS) assignment and power control problem in a hybrid energy supply wireless network, where an energy harvesting BS and a grid-powered BS coordinate to serve a mobile user. In order to minimize the grid energy consumption while maximizing the number of transmitted data packets, we introduce the total service cost over an N-block frame as the performance metric, which is the weighted sum of the grid energy cost and the packet drop cost. With non-causal side information (SI) available at the BSs, including energy SI and channel SI, a Greedy Assignment algorithm with low complexity and near optimal performance is proposed. For the causal SI setting, the design problem is formulated as a discrete Markov decision problem. Interesting solution structures are derived, which help develop an efficient monotone backward induction algorithm. To further reduce the complexity, a heuristic online policy is also proposed. Simulation results shall validate the effectiveness of the proposed policies and demonstrate a unique tradeoff in such networks, i.e., the tradeoff between the grid energy consumption and the provided quality of service.
KW - Base Station Assignment
KW - Energy Harvesting
KW - Green Communications
KW - Power Control
KW - QoS
UR - http://www.scopus.com/inward/record.url?scp=84938717650&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2015.7127636
DO - 10.1109/WCNC.2015.7127636
M3 - Conference article published in proceeding or book
AN - SCOPUS:84938717650
T3 - 2015 IEEE Wireless Communications and Networking Conference, WCNC 2015
SP - 1177
EP - 1182
BT - 2015 IEEE Wireless Communications and Networking Conference, WCNC 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2015 IEEE Wireless Communications and Networking Conference, WCNC 2015
Y2 - 9 March 2015 through 12 March 2015
ER -