Browsing by Subject "Robust design"

Now showing 1 - 5 of 5

Open Access
Optimal and robust power allocation for visible light positioning systems under illumination constraints
(IEEE, 2019-01) Keskin, Musa Furkan; Sezer, Ahmet Dündar; Gezici, Sinan
The problem of optimal power allocation among light emitting diode (LED) transmitters in a visible light positioning system is considered for the purpose of improving localization performance of visible light communication (VLC) receivers. Specifically, the aim is to minimize the Cramér-Rao lower bound (CRLB) on the localization error of a VLC receiver by optimizing LED transmission powers in the presence of practical constraints, such as individual and total power limitations and illuminance constraints. The formulated optimization problem is shown to be convex and thus can efficiently be solved via standard tools. We also investigate the case of imperfect knowledge of localization parameters and develop robust power allocation algorithms by taking into account both overall system uncertainty and individual parameter uncertainties related to the location and orientation of the VLC receiver. In addition, we address the total power minimization problem under predefined accuracy requirements to obtain the most energy-efficient power allocation vector for a given CRLB level. Numerical results illustrate the improvements in localization performance achieved by employing the proposed optimal and robust power allocation strategies over the conventional uniform and non-robust approaches.
Open Access
Power-efficient positioning for visible light systems via chance constrained optimization
(IEEE, 2020) Yazar, Onurcan; Keskin, M. F.; Gezici, Sinan
The problem of minimizing total power consumption in light-emitting diode transmitters is investigated for achieving power efficient localization in a visible light communication and positioning system. A robust power allocation approach based on stochastic uncertainties is proposed for total power minimization in the presence of localization accuracy, power, and illumination constraints. Specifically, the power consumption minimization problem is formulated under a chance constraint on the probability of Cramér-Rao lower bound exceeding a tolerable limit, which is a computationally intractable constraint. The sphere bounding method is used to propose a safe convex approximation to this intractable constraint, which makes the resulting problem suitable for standard convex optimization tools. Numerical results demonstrate the advantages of the proposed robust solution over the nonrobust solution and uniform power allocation in the presence of stochastic uncertainty.
Open Access
Production line calibration with data analysis
(2022-09) Taş, İsmail Burak
Product weights can be statistically related to controllable and uncontrollable factors of the production processes. Uncontrollable factors may be correlated with controllable factors. We fitted a response surface approximator of product weights and found sub-optimal controllable factors’ values that minimize product weight. Furthermore, we found that the uncertainty of uncontrollable variables and the correlation among them may affect the result of product weight minimization. The company may implement these findings to reduce the cost of production. Also, we formulated a fully Bayesian experimental design problem to minimize product weight tolerance limits and built hierarchical models. Posterior distributions of the hierarchical models’ parameters can be simulated by a Gibbs sampler. However, we conclude that the effectiveness and convergence of the Gibbs sampler may not be robust to candidate design settings while searching over the design space to solve the experimental design problem.
Open Access
Robust joint precoding/combining design for multiuser MIMO systems with calibration errors
(Institute of Electrical and Electronics Engineers, 2023-01-05) Kazemi, Mohammad; Göken, Çağrı; Duman, Tolga Mete
We consider the downlink of a multiuser system operating in the time-division duplexing mode, for which base station (BS) and users are equipped with multiple antennas, and provide a robust precoding/combining design against imperfect channel state information (CSI) and calibration errors due to hardware mismatch. Towards this end, we first formulate a robust joint precoder and combiner design as a stochastic minimum mean squared error optimization problem. Then, employing an alternating optimization approach, we propose an algorithm to obtain the precoding and combining matrices assuming imperfect CSI and calibration errors at both the BS and the user sides. We also provide asymptotic closed-form expressions for the mean squared error (MSE) and the achievable sum-rate in the massive MIMO regime. The results indicate that while the MSE linearly increases with the calibration errors at the user side, the sum-rate is asymptotically independent of them. Extensive simulation results show that the proposed robust joint precoder/combiner outperforms the existing solutions while having the same order of complexity. Moreover, when the BS sends a quantized version of the combining coefficients to the users, it is observed that the proposed solution is more robust to the quantization errors than the existing algorithms.
Open Access
Robust joint transceiver design for multiuser MIMO systems with calibration errors
(Institute of Electrical and Electronics Engineers, 2022-08-11) Kazemi, Mohammad; Göken, Ç.; Duman, Tolga Mete
We consider the downlink of a multiuser multiple-input multiple-output (MIMO) system operating in the time-division duplexing (TDD) mode. In this mode, assuming reciprocity, the channel coefficients estimated during the uplink channel training are utilized by the base station (BS) in the downlink data transmission. However, due to hardware mismatches, the uplink and downlink channels are not exactly the same, and therefore, there are calibration errors, which degrade the system performance. In this paper, our goal is to provide a transceiver design which has a robust performance under imperfect channel reciprocity. To this end, we first formulate a robust joint precoder and combiner design as a stochastic minimum mean square error (MMSE) optimization problem. Then, employing an alternating optimization approach, we propose an algorithm to obtain the precoding and combining matrices assuming imperfect CSI and calibration errors at both the BS and user sides. Extensive simulation results show that the proposed robust joint precoder/combiner outperforms the existing solutions in the literature.