Session: Optimization Methods for Next-Generation Wireless Communication Networks (II)
Chair: Wei Yu
Cluster: Optimization Applications (Communication, Energy, Health, ML, ...)
Talk 1: Optimizations and Signalling for Sustainable and Multifunctional Wireless Networks
Speaker: Christos Masouros
Abstract: The future global cellular infrastructure will underpin a variety of applications, such as smart city solutions, urban security, infrastructure monitoring, and smart mobility, among others. These emerging applications require new network functionalities that go beyond traditional communication. Key network KPIs for 6G include Gb/s data rates, cm-level localization, μs-level latency, and Tb/Joule energy efficiency. Additionally, future networks must support the UN's Sustainable Development Goals to ensure sustainability, net-zero emissions, resilience, and inclusivity. This talk will discuss the applications of optimization and signalling design for sustainable and multifunctional wireless networks.
Talk 2: Optimal Joint Fronthaul Compression and Beamforming Design for Networked ISAC Systems
Speaker: Tsung-Hui Chang
Abstract: This study investigates a networked integrated sensing and communication (ISAC) system, where multiple base stations (BSs), connected to a central processor (CP) via capacity-limited fronthaul links, cooperatively serve communication users while simultaneously sensing a target. The primary objective is to minimize the total transmit power while meeting the signal-to-interference-plus-noise ratio (SINR) requirements for communication and sensing under fronthaul capacity constraints, resulting in a joint fronthaul compression and beamforming design (J-FCBD) problem. We demonstrate that the optimal fronthaul compression variables can be determined in closed form alongside the beamformers, a novel finding in this field. Leveraging this insight, we show that the remaining beamforming design problem can be solved globally using the semidefinite relaxation (SDR) technique, albeit with considerable complexity. Furthermore, the tightness of its SDR reveals zero duality gap between the considered problem and its Lagrangian dual. Building on this duality result, we exploit the novel UL-DL duality within the ISAC framework to develop an efficient primal-dual (PD)-based algorithm. The algorithm alternates between solving beamforming with a fixed dual variable via fixed-point iteration and updating dual variable via bisection, ensuring global optimality and achieving high efficiency due to the computationally inexpensive iterations. Numerical results confirm the global optimality, effectiveness, and efficiency of the proposed PD-based algorithm.
Talk 3: Covariance-Based Activity Detection in Cooperative Multi-Cell Massive MIMO: Scaling Law and Efficient Algorithms
Speaker: Ya-Feng Liu
Abstract: In this talk, we focus on the activity detection problem in a multi-cell massive multiple-input multiple-output (MIMO) system, where active devices transmit their signature sequences to multiple base stations (BSs), and the BSs cooperatively detect the active devices based on the received signals. In this talk, we shall present some recent results of the covariance-based approach for activity detection in cooperative multi-cell massive MIMO systems. In particular, we shall present some scaling law results and efficient coordinate descent (CD) algorithms.
