The rapid evolution of 5G and emerging 6G telecom networks introduces new security challenges due to the potential threat posed by quantum computing to conventional cryptographic algorithms. This study proposes a post-quantum cryptographic framework for protecting critical 5G and 6G telecom infrastructure against quantum-enabled attacks. The framework investigates quantum-resistant cryptographic mechanisms for secure key establishment, authentication, data confidentiality, and communication integrity. Performance is evaluated using key size, encryption and decryption time, computational overhead, latency, and throughput. The proposed approach aims to achieve a balance between quantum resistance and network efficiency, providing a scalable and resilient security solution for next-generation wireless communication environments.
In order to meet mobile cellular users' ever-increasing network usage, today's 4G and 5G networks are designed mainly with the goal of maximizing spectral efficiency. While they have made progress in this regard, controlling the carbon footprint and operational costs of such networks remains a long-standing problem among network designers. This Challenge paper takes a long view on this problem, envisioning a NextG scenario where the network leverages quantum annealing computation for cellular baseband processing. We gather and synthesize insights on power consumption, computational throughput and latency, spectral efficiency, and operational cost, and deployment timelines surrounding quantum technology. Armed with these data, we analyze and project the quantitative performance targets future quantum hardware must meet in order to provide a computational and power advantage over silicon hardware, while matching its whole-network spectral efficiency. Our quantitative analysis predicts that with quantum hardware operating at a 140
μs problem latency and 4.3M qubits, quantum computation will achieve a spectral efficiency equal to silicon while reducing power consumption by 40.8 kW (45% lower) in a representative 5G base station scenario with 400 MHz bandwidth and 64 antennas, and an 8 kW power reduction (16% lower) using 2.2M qubits in a 200 MHz-bandwidth 5G scenario.
This paper presents a novel approach to quantum control, termed hardware-software co-optimization, aiming to enhance the efficiency of quantum computation. The core idea revolves around developing a dynamic optimization framework that adapts control pulses based on real-time feedback from the quantum hardware. This framework integrates quantum control algorithms with the specific characteristics of the quantum device, such as coherence time and gate fidelity. The optimization process is achieved through a collaborative system where the optimizer adjusts the control pulses, and the quantum computing software executes the computations. We demonstrate the potential of this approach to improve the overall performance of quantum algorithms by mitigating the impact of hardware imperfections. The proposed methodology offers a pathway to more robust and efficient quantum control, bridging the gap between theoretical algorithms and practical hardware implementation. Key mathematical elements explored include pulse shaping, error mitigation strategies, and adaptive control algorithms.