Energy Harvesting Communication System with a Finite Set of Transmission Rates

A point-to-point communication system in which the transmitter is equipped with an energy harvesting (EH) device and a rechargeable battery of limited size is considered. The harvested energy profile is assumed to be known in advance, that is, the problem is studied in the offline optimization framework. A practical communication system is considered, in which the possible transmission rates, and equivalently, power levels, belong to a finite set of discrete values. This problem is formulated as a convex optimization problem, which can be solved numerically. In order to provide further insights into the nature of the optimal transmission policy, an alternative solution is provided based on the solution of the continuous version of this problem, which itself has a “shortest path” interpretation. We propose an optimal algorithm, which permits us to easily build the solution of the discrete case from the continuous case, using an equivalence notion between different transmission policies, and several equivalence- preserving transformations.

[1]  Deniz Gündüz,et al.  A Learning Theoretic Approach to Energy Harvesting Communication System Optimization , 2012, IEEE Transactions on Wireless Communications.

[2]  Jing Yang,et al.  Optimal packet scheduling in a multiple access channel with energy harvesting transmitters , 2012, Journal of Communications and Networks.

[3]  Elif Uysal-Biyikoglu,et al.  Finite-horizon Online Transmission Rate and Power Adaptation on a Communication Link with Markovian Energy Harvesting , 2013, ArXiv.

[4]  Aylin Yener,et al.  Optimum Transmission Policies for Battery Limited Energy Harvesting Nodes , 2010, IEEE Transactions on Wireless Communications.

[5]  Neelesh B. Mehta,et al.  Transmit Power Control Policies for Energy Harvesting Sensors With Retransmissions , 2013, IEEE Journal of Selected Topics in Signal Processing.

[6]  Deniz Gündüz,et al.  Designing intelligent energy harvesting communication systems , 2014, IEEE Communications Magazine.

[7]  Michele Zorzi,et al.  Transmission Policies for Energy Harvesting Sensors with Time-Correlated Energy Supply , 2013, IEEE Transactions on Communications.

[8]  Deniz Gündüz,et al.  Energy Harvesting Broadband Communication Systems With Processing Energy Cost , 2014, IEEE Transactions on Wireless Communications.

[9]  Qing Bai,et al.  Modulation optimization for energy harvesting transmitters with compound Poisson energy arrivals , 2013, 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications (SPAWC).

[10]  Deniz Gündüz,et al.  Optimizing feedback in energy harvesting MISO communication channels , 2013, 2013 IEEE Global Conference on Signal and Information Processing.

[11]  Eytan Modiano,et al.  A Calculus Approach to Energy-Efficient Data Transmission With Quality-of-Service Constraints , 2009, IEEE/ACM Transactions on Networking.

[12]  Deniz Gündüz,et al.  Two-hop communication with energy harvesting , 2011, 2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP).

[13]  Deniz Gündüz,et al.  A general framework for the optimization of energy harvesting communication systems with battery imperfections , 2011, Journal of Communications and Networks.

[14]  Jing Yang,et al.  Optimal Packet Scheduling in an Energy Harvesting Communication System , 2010, IEEE Transactions on Communications.

[15]  Jing Yang,et al.  Transmission with Energy Harvesting Nodes in Fading Wireless Channels: Optimal Policies , 2011, IEEE Journal on Selected Areas in Communications.