Online Resource Allocation for Energy Harvesting Downlink Multiuser Systems: Precoding with Modulation, Coding Rate, and Subchannel Selection
This paper proposes an online resource allocation algorithm for weighted sum rate maximization in energy harvesting downlink multiuser multiple-input-multiple-output (MIMO) systems, where the base station transmitter is powered by both a regular energy source and an energy buffer that is connected to an energy harvester. Taking into account the discrete nature of the modulation and coding rates (MCRs) used in practice, we formulate a stochastic dynamic programming (SDP) problem to jointly design the MIMO precoders, select the MCRs, assign the subchannels, and optimize the energy consumption over multiple time slots with causal and statistical energy arrival information and statistical channel state information. Solving this high-dimensional SDP entails several difficulties: the SDP has a nonconcave objective function, the optimization variables are of mixed binary and continuous types, and the number of optimization variables is on the order of thousands. We propose a new method to solve this NP-hard SDP by decomposing the high-dimensional SDP into an equivalent three-layer optimization problem and develop efficient algorithms to solve each layer separately. The decomposition reduces the computational burden and breaks the curse of dimensionality successfully. We analyze the complexity of the proposed algorithm and demonstrate the performance gains based on numerical examples.
W. Zeng et al., "Online Resource Allocation for Energy Harvesting Downlink Multiuser Systems: Precoding with Modulation, Coding Rate, and Subchannel Selection," IEEE Transactions on Wireless Communications, vol. 14, no. 10, pp. 5780-5794, Institute of Electrical and Electronics Engineers (IEEE), Oct 2015.
The definitive version is available at https://doi.org/10.1109/TWC.2015.2442987
Electrical and Computer Engineering
National Science Foundation (U.S.)
Keywords and Phrases
Algorithms; Channel estimation; Channel state information; Communication channels (information theory); Energy harvesting; Energy utilization; MIMO systems; Modulation; Multiuser detection; Online systems; Optimization; Resource allocation; Stochastic systems; Base station transmitters; Curse of dimensionality Finite-alphabet inputs; Multiuser multiple-input multiple-output systems; Multiuser system; Statistical channel state informations; Stochastic dynamic programming; Weighted sum-rate maximizations; Dynamic programming; Energy harvesting; finite alphabet inputs
International Standard Serial Number (ISSN)
Article - Journal
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