Optimal energy allocation between pilot and data symbols for minimizing frame error probability under imperfect fading channel information

Ghanavati, Ali Zarei; Lee, Daniel

doi:10.1109/wcnc.2014.6952595

Cited by 5 publications

(1 citation statement)

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“…Our optimization goal is the EE of the system instead of the frame error probability. The pilot length in our paper is a variable, so the objective function is completely different from [23]. Compared with [24], our paper focuses on how to optimize the energy efficiency of the system through resource allocation and pilot design with channel estimation information, rather than calculating the upper channel capacity limit in the case of multiple antenna arrays.…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Channel Estimation

et al. 2020

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We investigate the energy-efficient channel estimation in wireless networks, where one pilot is inserted for every several data slots to estimate the channel coefficients. Both the channel state information estimation error and the time-varying model are considered. We first formulate the energy-efficient channel estimation problem into a mixed integer nonlinear programming (MINLP) problem, where the variables include the transmitted power and the number of data slots. Due to the NP-hard nature, we degenerate the MINLP problem into a series of non-concave optimization problems without integer variables. Then we solve these problems using successive convex approximation, geometric programming, and the Dinkelbach algorithm to obtain a point satisfying the Karush-Kuhn-Tucker (KKT) conditions. Furthermore, we develop a low-complexity sub-optimal scheme through binary variable relaxation to obtain a solution, and the convergence point satisfies the KKT conditions of the relaxed non-concave problem. Simulation results demonstrate the convergence and effectiveness of our proposed schemes.

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Section: Introductionmentioning

confidence: 99%