Distributed Spectrum and Power Allocation for D2D-U Networks: A Scheme based on NN and Federated Learning

In this paper, a Device-to-Device communication on unlicensed bands (D2D-U) enabled network is studied. To improve the spectrum efficiency (SE) on the unlicensed bands and fit its distributed structure while ensuring the fairness among D2D-U links and the harmonious coexistence with WiFi networks, a distributed joint power and spectrum scheme is proposed. In particular, a parameter, named as price, is defined, which is updated at each D2D-U pair by a online trained Neural network (NN) according to the channel state and traffic load. In addition, the parameters used in the NN are updated by two ways, unsupervised self-iteration and federated learning, to guarantee the fairness and harmonious coexistence. Then, a non-convex optimization problem with respect to the spectrum and power is formulated and solved on each D2D-U link to maximize its own data rate. Numerical simulation results are demonstrated to verify the effectiveness of the proposed scheme

Learning-Assisted Clustered Access of 5G/B5G Networks to Unlicensed Spectrum

© 2002-2012 IEEE. License-assisted access (LAA) to unlicensed spectrum is a potential solution to improve the resource availability and system scalability of 5G/B5G networks. Challenges arise from coexistence between LAA and incumbent systems, especially the ubiquitous IEEE 802.11 WiFi systems. This article demonstrates that the coexistence can be substantially improved by leveraging learning-based clustering of small base stations (SBSs), referred to as learning-assisted clustered access (LACA), and improving the interoperability between licensed and unlicensed access. Fast signaling and a centralized control plane of licensed access can facilitate clustering SBSs for coordinated access to the unlicensed spectrum, hence reducing the number of parties contending for access and alleviating contention. Appropriate clustering of SBSs is important to the efficiency of LACA in 5G/B5G networks. LACA can quickly converge with strong locality, facilitating the coordination of the SBSs, for example, cooperatively connecting multiple users and conducting beamforming. Analytic evaluation and numerical tests confirm the improved coexistence through enlarged LAA-WiFi capacity regions, as well as reduced transmission delays