arXiv subjects

Maryam Masjedi

Publications and source records attributed to Maryam Masjedi.

3 recordsLinked to original sources

arXiv2022

Design of a Multi-User Wireless Powered Communication System Employing Either Active IRS or AF Relay

In this paper, we optimize a Wireless Powered Communication (WPC) system including multiple pair of users, where transmitters employ single-antenna to transmit their information and power to their receivers with the help of one multiple-antennas Amplify-and-Forward (AF) relay or an active Intelligent Reflecting Surface (IRS). We propose a joint Time Switching (TS) scheme in which transmitters, receivers, and the relay/IRS are either in their energy or information transmission/reception modes. The transmitted multi-carrier unmodulated and modulated waveforms are used for Energy Harvesting (EH) and Information Decoding (ID) modes, respectively. In order to design an optimal fair system, we maximize the minimum rate of all pairs for both relay and IRS systems through a unified framework. This framework allows us to simultaneously design energy waveforms, find optimal relay/IRS amplification/reflection matrices, allocate powers for information waveforms, and allocate time durations for various phases. In addition, we take into account the non-linearity of the EH circuits in our problem. This problem turns out to be non-convex. Thus, we propose an iterative algorithm by using the Minorization-Maximization (MM) technique, which quickly converges to the optimal solution. Numerical examples show that the proposed method improves the performance of the multi-pair WPC relay/IRS system under various setups.

eess.SP↗

arXiv2022

Cooperative Fair Throughput Maximization in a Multi-Cluster Wireless Powered Network

In this paper, we study a multi-cluster Wireless Powered Communication Network (WPCN) where each cluster of users cooperate with a Cluster Head (CH) and a Hybrid Access Point (HAP). All users are equipped with multiple antennas. This HAP employs beamforming to deliver energy to the users in the downlink phase. The users of each cluster transmit their signals to the HAP and to their CHs in the uplink phase. In the next step the CHs first relay the signals of their cluster users and then transmit their own information to the HAP. We design the Energy Beamforming (EB) matrix, transmit covariance matrices of the users and allocate time slots to energy transfer and cooperation phases by optimizing the max-min and sum throughputs of the network. Our optimization is a non-convex problem which we break it to two non-convex sub-problems and solve them by employing the Alternating Optimization (AO) and the Minorization-Maximization (MM) technique. We recast the resulting sub-problems as a convex Second Order Cone Programming (SOCP) and a Quadratic Constraint Quadratic Programming (QCQP) for the max-min and sum throughput maximization problems, respectively. We take into account the consider imperfect Channel State Information (CSI) and non-linearity in Energy Harvesting (EH) circuits. Using numerical examples, we explore the impact of the proposed cooperation as well as optimal placement of CHs under various setups.

cs.IT↗

arXiv2019

Max-Min Fairness Design for MIMO Interference Channels: a Minorization-Maximization Approach

We address the problem of linear precoder (beamformer) design in a multiple-input multiple-output interference channel (MIMO-IC). The aim is to design the transmit covariance matrices in order to achieve max-min utility fairness for all users. The corresponding optimization problem is non-convex and NP-hard in general. We devise an efficient algorithm based on the minorization-maximization (MM) technique to obtain quality solutions to this problem. The proposed method solves a second-order cone convex program (SOCP) at each iteration. We prove that the devised method converges to stationary points of the problem. We also extend our algorithm to the case where there are uncertainties in the noise covariance matrices or channel state information (CSI). Simulation results show the effectiveness of the proposed method compared with its main competitor.

eess.SP↗