Abstract
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.
Highlights
Due to the rapid development of the Internet of Things (IoT) [1]–[3], the impact of wireless communication systems on the environment cannot be ignored [4], and the design of energy-efficient wireless communication systems has become an urgent task [5]–[8]
Since EE could be defined as the ratio of data rate to energy consumption, an energy efficient pilot design has to make a good tradeoff between energy consumption and channel state information (CSI) quality [16]
We investigate mixed integer nonlinear programming (MINLP) EE-maximization schemes for wireless communication system pilot design based on successive convex approximation (SCA), geometric programming (GP), and the Dinkelbach methods
Summary
Due to the rapid development of the Internet of Things (IoT) [1]–[3], the impact of wireless communication systems on the environment cannot be ignored [4], and the design of energy-efficient wireless communication systems has become an urgent task [5]–[8]. Wei et al.: Energy-Efficient Channel Estimation the average data rate and the EE In this case, an optimal length of time slots should be derived. 1) We model the time-varying channel, calculate the CSI errors with different correlation coefficients to obtain the analytical expression of the channel data rate, which depends on the number of data slots, the pilot transmission power, and the data transmission power. 3) We investigate the following network performance through simulation results, including the convergence rates of sub-optimal and low-complexity sub-optimal power control schemes, the gap between two solutions, VOLUME 8, 2020 the impact of the length of time slots, and the impact of the maximum allowed transmission power. Notations: a is a vector, a is a scalar, a(x) means a as a function of x, a(x0) (where x0 is a given value) means the value of function a with given independent variable value x0, CN m, σ 2 is a complex Gaussian scalar with mean m and covariance σ 2, and E[∗] represents expectation
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