Federated systems enable collaborative training on highly heterogeneous, non-i.i.d. data through model personalization, which can be facilitated by employing multi-task learning. However, multi-task learning algorithms are often implemented using methods like stochastic gradient descent, which may suffer from slow convergence in a multi-task federated setting. To accelerate the training procedure, we design an efficient iterative distributed method based on the alternating direction method of multipliers (ADMM) for support vector machines (SVMs), which tackles federated classification and regression. The proposed method utilizes efficient computations and model exchange in a network of heterogeneous nodes and allows personalization of the learning model in the presence of non-i.i.d. data. To ensure data privacy, we introduce a randomization algorithm that helps avoid data inversion. Finally, we analyze the impact of the proposed privacy mechanisms and participant hardware and data heterogeneity on the system performance. Our experiments confirm the advantages of the proposed ADMM-based personalized federated multi-task learning.

While optimizing the system-level performance in a network of advanced high-end wearables, millimeter-wave (mmWave) medium access protocols may benefit from leveraging the information on the spatial and temporal dynamics of the radio channel. In this paper, we aim to bridge the existing gap in mmWave on-body propagation studies by analyzing the channel structure based on an extensive shooting-and-bouncing ray simulations. Particularly, we model a set of on-body trajectories and illustrate the evolution of the core channel parameters as well as address the specifics of their dynamics, which can be exploited in subsequent protocol development. As a key contribution of this study, we propose a methodology for processing and applying the simulation data as well as illustrate our approach through an example of estimating the effects of directionality and antenna beam misalignment. Our results and data, also available online, facilitate the system-level analysis and performance evaluation of various on-body mmWave systems.

A diversity of wireless technologies will collaborate to support the fifth‐generation (5G) communication networks with their demanding applications and services. Despite decisive progress in many enabling solutions, next‐generation cellular deployments may still suffer from a glaring lack of bandwidth due to inefficient utilization of radio spectrum, which calls for immediate action. To this end, several capable frameworks have recently emerged to all help the mobile network operators (MNOs) leverage the abundant frequency bands that are utilized lightly by other incumbents. Along these lines, the recent Licensed Shared Access (LSA) regulatory framework allows for controlled sharing of spectrum between an incumbent and a licensee, such as the MNO, which coexist geographically. This powerful concept has been subject to several early technology demonstrations that confirm its implementation feasibility. However, the full potential of LSA‐based spectrum management can only become available if it is empowered to operate dynamically and at high space‐time‐frequency granularity. Complementing the prior efforts, we in this work outline the functionality that is required by the LSA system to achieve the much needed flexible operation as well as report on the results of our respective live trial that employs a full‐fledged commercial‐grade cellular network deployment. Our practical results become instrumental to facilitate more dynamic bandwidth sharing and thus promise to advance on the degrees of spectrum utilization in future 5G systems without compromising the service quality of their users.

As next-generation mobile networks are rapidly taking shape driven by the target standardization requirements and initial trial implementations, a range of accompanying technologies prepare to support them with more reliable wireless access and improved service provisioning. Among these are more advanced spectrum sharing options enabled by the emerging Licensed Shared Access (LSA) regulatory framework, which aims to efficiently employ the capacity of underutilized frequency bands in a controlled manner. The concept of LSA promises to equip network operators with the much needed additional spectrum on the secondary basis and thus brings changes to the existing cellular network management. Hence, additional research is in prompt demand to determine the required levels of Quality of Service (QoS) and service provisioning reliability, especially in cases of dynamic geographical and temporal LSA sharing. Motivated by this recent urge and having at our disposal a fully-functional 3GPP LTE cellular deployment, we have committed to implement and trial the principles of dynamic LSA-compatible spectrum management. This paper is our first disclosure on the comprehensive experimental evaluation of this promising technology. We expect that these unprecedented practical results together with the key lessons learned will become a valuable reference point for the subsequent integration of flexible LSA-based services, suitable for inter-operator and multi-tenant spectrum sharing.