Amirkabir University of Technology

About: Amirkabir University of Technology is a education organization based out in Tehran, Iran. It is known for research contribution in the topics: Nonlinear system & Finite element method. The organization has 15254 authors who have published 31165 publications receiving 487551 citations. The organization is also known as: Tehran Polytechnic & Tehran Polytechnic University.

Buckling of imperfect functionally graded plates under in-plane compressive loading

Abstract: Buckling behavior of rectangular functionally graded plates with geometrical imperfections is studied in this paper. The equilibrium, stability, and compatibility equations of an imperfect functionally graded plate are derived using the classical plate theory. It is assumed that the nonhomogeneous mechanical properties of the plate, graded through thickness, are described by a power function of the thickness variable. The plate is assumed to be under in-plane compressive loading. Simultaneous solving of the stability and compatibility equations in conjunction with the equilibrium equations leads to the buckling relation of the plate. The critical buckling load of a sample plate is obtained and compared for different geometrical ratios. The results are reduced and compared with the results of perfect functionally graded and imperfect isotropic plates.

Performance Analysis of Cell-Free Massive MIMO System With Limited Fronthaul Capacity and Hardware Impairments

Abstract: We study uplink of cell-free massive multiple-input multiple-output system with limited capacity fronthaul link connecting each access point (AP) to a central processing unit (CPU), under hardware impairments at user equipments and APs. Achievable rates are derived for three transmission strategies at APs, named as compress-forward-estimate (CFE), estimate-compress-forward (ECF), and estimate-multiply-compress-forward (EMCF), to efficiently share the fronthaul capacity for sending channel state information (CSI) and/or data signals of the users to the CPU. For forwarding the compressed version of the signals, low-complexity fronthaul rate allocations are proposed for ECF and EMCF strategies, which considerably improve the performance especially for limited capacity fronthauls. Besides, for CFE and ECF strategies, two power allocations are presented to maximize the sum rates; One approximate solution based on geometric programming and an alternative general iterative algorithm. It is shown that performances of the strategies are not the same, because they require different fronthaul rate allocations for CSI and/or data signals transmission to CPU, and their AP signal processing capabilities are different. Finally, to highlight performance characteristics of the proposed system under different transmission strategies and circumstances such as pilot reuse and multiple-antenna APs scenarios, numerical results are presented and the three strategies are compared.