Global Energy Efficiency Optimization for Wireless-Powered Massive MIMO Aided Multiway AF Relay Networks - 2018


This Project considers a wireless-powered massive multi-input multioutput aided multiway amplify-and-forward relay network, where a relay equipped with large antennas charges users through energy beamforming and assists with wireless info transmission. For this method, we have a tendency to propose a completely unique energy-economical resource allocation theme for the worldwide energy efficiency (GEE) optimization. In specific, we tend to 1st derive an correct closed-type expression of GEE when zero-forcing transceivers are utilized in the considered system. Second, based mostly on this analytical expression, we tend to formulate a resource allocation optimization drawback for the GEE maximization by jointly optimizing power and time allocation, subject to restricted transmit power, time period, and minimum quality-of-service constraints. Thanks to the complexity of this nonconvex optimization, a 2-layer iterative algorithm is proposed to address the original GEE maximization drawback. Numerical results demonstrate the accuracy of our theoretical analysis and also the effectiveness of the derived algorithms.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Traffic sign recognition by combining global and local features based on semi-supervised classification ABSTRACT: The legibility of traffic signs has been studied from the start of the design process to ensure
PROJECT TITLE : Development and Assessment of a New Global Mammographic Image Feature Analysis Scheme to Predict Likelihood of Malignant Cases ABSTRACT: Researchers in this project hope to create and test a new computer-aided
PROJECT TITLE : Combining Local and Global Measures for DIBR-Synthesized Image Quality Evaluation ABSTRACT: 3D video applications, such as 3D television and free perspective video, rely heavily on depth-image-based rendering (DIBR)
PROJECT TITLE : High-quality Image Restoration Using Low-Rank Patch Regularization and Global Structure Sparsity ABSTRACT: In recent years, picture restoration has improved significantly thanks to techniques based on nonlocal
PROJECT TITLE :Global Optimality in Low-Rank Matrix Optimization - 2018ABSTRACT:This Project considers the minimization of a general objective function f(X) over the set of rectangular n × m matrices that have rank at most r.

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry