Course 078 Quantum Computing and QC-Assisted Communications

Professor Savo Glisic, Worcester Polytechnic Institute, MA, United States, is teaching this 3-day course about Quantum Computing and QC-Assisted Communications.

When moving from 5G to 6G/7G communication networks there will be need for more sophisticated network optimization tools with respect to both, computational speed and efficiency of optimization algorithms.   

It looks like that Quantum Computing (QC) technology offers significant improvements in both of these aspects. Due to inherent parallelism in the processing of quantum information, unpresented increases in computation speed are anticipated.  Similarly a number of algorithms developed within the umbrella of quantum technology, like quantum search algorithms (QSA) developed for big data analysis, could be used to help us  with more efficient optimization of communication networks. In the past, most of the time we would end up with a formulation of the optimization problem that would need exhaustive search through all combination of the system parameters. This would be unacceptable solution when it comes to complexity and as a consequence we would be looking for simplifications that would on the other hand reduce the performance. By combining the advantageousness of both, unprecedented increase of computational speed and efficiency of QSA we will be able to significantly improve the optimization algorithms for network, deployment and optimization.  

For these reasons, the focus of the course will be on discussing the principles of QC and detailed presentations of possibilities of using QSA in communication networks.