Online Resource Allocation for Energy Harvesting Downlink MIMO Systems with Finite-Alphabet Inputs

Abstract

This paper proposes an online resource allocation algorithm for weighted sum rate maximization in energy harvesting downlink multiuser multiple-input multiple-output (MIMO) systems. 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 show that efficient algorithms can be used to solve each layer separately. The decomposition reduces the computational burden and breaks the curse of dimensionality.

Meeting Name

2015 IEEE International Conference on Communications, ICC (2015: Jun. 8-12, London, UK)

Department(s)

Electrical and Computer Engineering

Sponsor(s)

National Science Foundation (U.S.)

Comments

This work was supported in part by the National Science Foundation under Grants ECCS-0846486 and ECCS-1408316.

International Standard Book Number (ISBN)

978-1-4673-6432-4

International Standard Serial Number (ISSN)

1550-3607; 1938-1883

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Jun 2015

Link to Full Text

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