Quantum aided efficient resource control for connected support in IRS assisted networks

Abstract

Context:To achieve the vision of all connected world with uninterrupted communication support, 6G technology plays an important role. But the scarce radio spectrum and limited network resources is the main challenge in delivering its promised performance. Objectives:This paper presents an IRS-aided cell free NOMA network model that aims to provide uniform network coverage. The future 6G technology envisions for serving billions of interconnected devices with seamless communication support, data handling capabilities and computational accuracy. But the scarcity of network resources is the main limitation. Thus, the need is to design quantum enabled intelligent and dynamic networks capable of offering extended network capabilities. Proposed work is on intelligent network framework that provides uniform network coverage through efficient resource management for a 6G enabled expanded IoT network. Methods:To enable efficient resource management, a quantum enabled resource control algorithm is proposed that creates user clusters and associates each AP-IRS pair to each cluster. Each AP transmits the superimposed signals of its intended cluster against all the user clusters as in conventional NOMA system. The nodes in each cluster have been assigned unique pilots so as to avoid intracluster interference. The use of IRS enables desired NOMA beamforming such that the effect of unfavourable wireless environment is mitigated. Results:The performance of the IRS-aided cell-free NOMA network is evaluated for average sum rate with different AP transmit power, cluster sizes, IRS reflecting elements and IRS phase shifts. It is shown that at transmit power per AP of 30dBm, the average sum rate of the system improves by 7.52% with the proposed algorithm using equal power allocation scheme. Further, the comparative performance analysis of three different communication systems is carried out to validate the proposed communication model. Conclusion:It is observed that with more number of users per cluster, the average sum rate of the system initially increases for small cluster sizes and then it becomes constant for large cluster sizes. The proposed clustering method outperforms the random clustering approach achieving sum rate of 12.9 bits/s/Hz with N =300 and M= 8. The comparison of different communication scenarios reveals that the maximum sum rate of 12.2 bits/s/Hz is achieved with the proposed model incorporating proposed clustering mechanism. Further, the energy efficiency analysis suggests that energy efficiency improves with N and Pc with proposed clustering approach. The use case scenarios for the integration of quantum computing with IRS technology are also presented.