Novel Retransmission Scheme for Energy Harvesting Transmitter and Receiver

被引:0
作者
Yadav, Animesh [1 ]
Goonewardena, Mathew [2 ]
Ajib, Wessam [1 ]
Elbiaze, Halima [1 ]
机构
[1] Univ Quebec Montreal, Dept Comp Sci, Montreal, PQ, Canada
[2] ETS, Montreal, PQ, Canada
来源
2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC) | 2015年
关键词
RADIO; MODEL;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
We consider a point-to-point wireless link with automatic repeat request (ARQ) based packet transmission where both the transmitter and receiver nodes are energy harvesting (EHNs). Transmitter EHN has access to low-grade channel state information (CSI) as it is implicitly obtained from ARQ feedback. Furthermore, signal processing tasks such as sampling and decoding at the receiver EIIN can be interrupted if there is insufficient energy in the battery that cause loss of packet and wastage of harvested energy both at the transmitter and receiver EHNs. We propose selective sampling (SS) scheme where only part of the transmitted packet is sampled and stored depending on the receiver nodes stored energy. SS information (SSI) is then fed back to the transmitter. Packet decoding is not performed until full packet is constructed. hence, we modify the conventional ARQ messages, i.e., ACK/NAK by adding few more bits to carry additional SSI as well. Another objective is to find the optimal power allocation policy to adapt to the low-grade CSI and SSI available at the transmitter such that harvested energy can be utilized efficiently especially at the receiver. Furthermore, using a decision-theoretic framework, we propose greedy power allocation scheme to evaluate the performance of the proposed retransmission scheme. In numerical examples, we illustrate that our proposed scheme has lower average packet transmission lime and packet drop probability (PDP) compared to the equal power allocation and greedy power allocation with conventional retransmission scheme.
引用
收藏
页码:3198 / 3203
页数:6
相关论文
共 23 条
[1]  
[Anonymous], 1994, Markov Decision Processes Discrete Stochastic Dynamic Programming. Series in probability and statistics
[2]   Transmit Power Control Policies for Energy Harvesting Sensors With Retransmissions [J].
Aprem, Anup ;
Murthy, Chandra R. ;
Mehta, Neelesh B. .
IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2013, 7 (05) :895-906
[3]  
Bertsekas D. P., 2000, Dynamic programming and optimal control, V1
[4]  
Chen T., 2014, P INT S MOD OPT MOB, P466
[5]   Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks [J].
Cui, SG ;
Goldsmith, AJ ;
Bahai, A .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2004, 22 (06) :1089-1098
[6]   Towards a Communication-Theoretic Understanding of System-Level Power Consumption [J].
Grover, Pulkit ;
Woyach, Kristen ;
Sahai, Anant .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2011, 29 (08) :1744-1755
[7]   Power management in energy harvesting sensor networks [J].
Kansal, Aman ;
Hsu, Jason ;
Zahedi, Sadaf ;
Srivastava, Mani B. .
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2007, 6 (04) :32
[8]  
Littman M. L., 1995, Machine Learning. Proceedings of the Twelfth International Conference on Machine Learning, P362
[9]  
Mahdavi-Doost H, 2013, IEEE INT SYMP INFO, P1799, DOI 10.1109/ISIT.2013.6620537