Analyzing the quality of service of quantum oriented open radio access networks in 5G and 6G

Abstract

The Open Radio Access Network (ORAN) technology has been developed to provide efficient spectrum sharing and cost-effective solutions, but it also increases network infrastructure and power usage. To evaluate the performance of the power consumption (PC), a model was proposed to quantify the compromises associated with virtualizing a server within an ORAN infrastructure, considering factors like the quantity of virtual machines, allocation of system resource blocks, and bandwidth. However, virtualization of the network has resulted about 50% reduction in the total PC in comparison with traditional cloud networks. However, the ORAN paradigm has produced more PC compared to the virtualization case, about 30% in the total PC and 10% in the cooling PC. Unless the advantages of ORAN are fully realized, the addition of extra units within the ORAN, specifically the DU servers, may result in more PC that might advocate against the ORAN. Subsequently, a work was proposed to examine the criteria and evaluations for prospective quantum solutions in conventional ORAN networks, focusing on entanglement phenomena to enhance the efficiency of the X2 application (X2-AP) protocol. This approach reduces the overhead of X2-AP signaling, reducing time and power consumption associated with standard cloud-based systems. As a result, increasing the number of photons has decreased the delay to about 40% compared to the traditional ORAN network. In addition, the energy efficiency in the quantum case has been increased while decreasing the power consumption by about 10%. This study also investigates the use of quantum entanglement-based approaches and their influence on conventional ORAN architecture’s signaling among the central units (CUs) and distributed units (DUs) by replacing the traditional method with entangled photons. The results showed that the proposed method has promised about 45%, 40% and 10% reductions in the EE, PC and delay, respectively, when compared to the traditional ORAN. Finally, a novel methodology for addressing problems in ORAN and implementing load balancing algorithms is presented, focusing on selecting ORAN servers with lower energy efficiency for quantum load balancing. This comparative analysis offers valuable insights for developing power-efficient ORAN implementations. This nonlinear problem was solved using Lagrange multiplier method to solve the problem mathematically, and using the Matlab (fmincon) software to solve the problem numerically. In which, two algorithms are used, sequential quadratic programming (SQP) and active-set. It was shown that the SQP model exhibits superior energy efficiency compared to the active-set model, with a difference of approximately 45%.