Quantum Computing Telecommunication Use New Technologies
Telecommunications firms innovate in the quantum leap and protect margins by utilising emerging technologies.
Communication with quantum computers
The global telecommunications industry, sometimes called the invisible architecture of the modern world, is undergoing a period of structural recalibration. Top operators are being compelled to reposition themselves as technology corporations by integrating cloud services, artificial intelligence, and increasingly, quantum technologies, as a result of the saturation of traditional connectivity-based revenue models. In addition to preserving market supremacy, this shift is essential for cybersecurity defences, new efficiency, and strategic distinction.
The foundation of the industry is facing scaling challenges despite the fact that networks are faster and denser than before. According to Global Telecom Outlook 2024-2028, the revenue from telecom services is expected to increase by 2.9% a year until 2028. In major economies, this rate is typically lower than anticipated inflation, a sign of structural stagnation. Significant capital expenditures (CapEx) on 5G densification and fibre rollout that do not produce commensurate returns are contributing factors, as is increased competition from hyperscalers like AWS, Google Cloud, and Microsoft Azure that offer edge computing solutions that can get around traditional operators.
Strategic Overhaul Is Forced by Market Stagnation
In this setting, competitive differentiation has been simplified to basic components such as dependability, coverage, and cost. Operators now have to search further up the value chain for value generation, which necessitates a deep understanding of artificial intelligence, cloud architecture, and cybersecurity. Quantum technology is showing promise as a differentiator in three areas that are directly relevant to telecom operations: data analytics, security, and network optimisation.
The Tri-Part Differentiator in Quantum
Quantum computing is expected to perform better than classical computers in network optimisation for certain types of computationally expensive, or NP-hard, activities, such as resource scheduling, network architecture, and traffic management. For example, Vodafone recently shown how to use a photonic quantum computer to optimise fibre routing.
The transition to quantum-safe communications in the field of cybersecurity is being propelled by quantum capabilities. This involves two techniques: Post-Quantum Cryptography (PQC), which employs mathematically secure algorithms implemented through software upgrades, and Quantum Key Distribution (QKD), which secures key exchange at the physical layer using quantum mechanics.
Regional initiatives are already demonstrating promise: SK Telecom runs one of the biggest QKD networks globally, connecting 48 public-sector enterprises, while BT runs a commercial QKD-secured metro network in London.
Initial experiments in data analytics suggest that quantum machine learning (QML) could enhance anomaly detection and predictive maintenance in complex networks. These systems are crucial because even small network outages can cause costly service interruptions. Telstra in Australia has piloted a QML model that can identify deterioration in network performance faster than traditional deep learning techniques.
Using Hybrid Systems to Increase Intelligence and Efficiency
Ericsson researchers have examined multi-chip quantum processors and quantum approaches for various telco workloads in order to discuss the potential advantages of quantum computing in telecom networks. They imagine quantum computers living in data centres and co-processing with classical computers to give network planning, control, and execution a computational edge.
Two particular issues that are researched in the radio domain are Maximum Likelihood MIMO (Multiple-Input, Multiple-Output) detection and Peak-to-Average Power Ratio (PAPR) minimisation. When modest examples of these optimisation tasks were transferred to a quantum annealer, a computational advantage over classical methods was shown. When compared to a single-threaded traditional QUBO solution, the 29x speedup achieved for PAPR minimisation in a 2×2 MIMO system could be negated by contemporary dual-socket servers running parallel simulated annealing.
In order to optimise antenna tilt a difficult task that seeks to strike a balance between coverage, quality, and capacity researchers also employed quantum techniques. Using 20 times fewer trainable parameters and fewer data points, a Quantum Neural Network (QNN) was able to attain prediction accuracy comparable to a classical artificial neural network when it was substituted for a regular deep-Q network. The reduction in trainable parameters and data sets suggests that training machine learning models in the quantum domain may reduce training overhead.
The Quantum-Native Infrastructure Roadmap
In order to overcome the restrictions of the Noisy Intermediate-Scale Quantum (NISQ) era, when qubits are not yet fault-tolerant, Ericsson proposes employing quantum computers as cloud-native coprocessors. These coprocessors could be multi-chip Quantum Processing Units (QPUs), which use a quantum communication channel to transport information between chips to achieve more computational fidelity than single-chip systems. This hybrid technique’s collaboration between classical and quantum computers validates that the quality of solutions for large issue instances may improve.
The industry is expected to go through three overlapping phases as it incorporates quantum technology:
Pilot Phase (2023–2026): Focusses on proofs-of-concept and quantum optimisation for QKD.
Testing quantum-enhanced AI models and incorporating PQC standards into network software are two aspects of hybrid integration (2026–2030).
After 2030, computing nodes and specialised quantum communication channels will be integrated directly into telecom networks as part of the Quantum-Native Infrastructure.
The success of the telecom sector over the next ten years will ultimately depend on how well quantum and AI capabilities are operationally integrated at scale. Quantum technologies are driving the next stage of competitiveness, where flexibility, efficiency, and trust are more significant differentiators than price and bandwidth, even though it is not expected that they would immediately transform networks. According to Ericsson’s research, quantum computers won’t be able to support the telco network architecture of the future until they are scalable and fault-tolerant.
