雅各布大学

The municipal solid waste management sector is a nationally significant greenhouse gas source in Sri Lanka, yet decision makers lack comprehensive, city-level life-cycle assessment of full waste management chains. This study quantifies and compares greenhouse gas emissions and mitigation potential of alternative waste management scenarios for Colombo and Kandy, supporting nationally determined contributions (NDC) 3.0. Using IPCC 2021 GWP100 V1.03 as the impact assessment method, six scenarios were assessed, including business-as-usual, recycling, composting, confined cover windrow composting, anaerobic digestion, refuse-derived fuel production, incineration, pyrolysis, co-processing in cement kilns, open dumping, and sanitary landfilling. The business-as-usual scenario, dominated by open dumping, resulted in the highest greenhouse gas emissions in both Colombo and Kandy. In contrast, the integrated waste management approach (Scenario 3), combining anaerobic digestion, confined cover windrow composting, refuse-derived fuel production, and enhanced recycling, converted both cities from net emitters to net carbon sinks. Over the projection period of 2026-2035, this transition is expected to deliver substantial cumulative emission reductions, contributing significantly toward achieving NDC 3.0 waste sector targets in Sri Lanka despite the relatively small share of national baseline emissions in the sector. These findings highlight the strong mitigation potential of integrated waste management systems for advancing low-carbon urban strategies.

We introduce a comprehensive approach to enhance the security, privacy, and sensing capabilities of integrated sensing and communications (ISAC) systems by leveraging random frequency agility (RFA) and random pulse repetition interval (PRI) agility (RPA) techniques. The combination of these techniques, which we refer to collectively as random frequency and PRI agility (RFPA), with channel reciprocity-based key generation (CRKG) obfuscates both Doppler frequency and PRIs, significantly hindering the chances that passive adversaries can successfully estimate radar parameters. In addition, a hybrid information embedding method integrating amplitude shift keying (ASK), phase shift keying (PSK), index modulation (IM), and spatial modulation (SM) is incorporated to increase the achievable bit rate of the system significantly. Next, a sparse-matched filter receiver design is proposed to efficiently decode the embedded information with a low bit error rate (BER). Finally, a novel RFPA-based secret generation scheme using CRKG ensures secure code creation without a coordinating authority. The improved range and velocity estimation and reduced clutter effects achieved with the method are demonstrated via the evaluation of the ambiguity function (AF) of the proposed waveforms.

We propose a novel DD MIMO channel model incorporating FIM, which is suitable for ISAC in high-mobility scenarios. We then discuss how the proposed FPDD channel model can be applied in a logical manner to multicarrier waveforms that are known to perform well in DD environments, namely, OFDM, OTFS, and AFDM. Leveraging the proposed model, we formulate an achievable rate maximization problem with a strong sensing constraint for all the aforementioned waveforms, which we then solve via a gradient ascent algorithm with closed-form gradients presented as a bonus. Our numerical results indicate that the achievable rate is significantly impacted by the emerging FIM technology with careful parametrization essential in obtaining strong ISAC performance across all waveforms suitable to mitigating the effects of DD channels.

The phenomenon of mutual coupling in continuous aperture arrays (CAPAs) is studied. First, a general physical model for the phenomenon that accounts for both polarization and surface dissipation losses is developed. Then, the unipolarized coupling kernel is characterized, revealing that polarization induces anisotropic coupling and invalidates the conventional half-wavelength spacing rule for coupling elimination. Next, the beamforming design problem for CAPAs with coupling is formulated as a functional optimization problem, leading to the derivation of optimal beamforming structures via the calculus of variations. To address the challenge of inverting the coupling kernel in the optimal structure, two methods are proposed: 1) the kernel approximation method, which yields a closed-form solution via wavenumber-domain transformation and GaussLegendre quadrature, and 2) the conjugate gradient method, which addresses an equivalent quadratic functional optimization problem iteratively. Furthermore, the optimal array gain and beampattern are analyzed at the large-aperture limit. Finally, the proposed continuous mutual coupling model is extended to spatially discrete arrays (SPDAs), and comprehensive numerical results are provided, demonstrating that: 1) coupled SPDA performance correctly converges to the CAPA limit, while uncoupled models are shown to violate physics, 2) polarization results in anisotropic array gain behavior, and 3) the coupled beampattern exhibits higher directivity than the uncoupled beampattern.

Beyond-diagonal reconfigurable intelligent surfaces (BD-RISs) are emerging as a transformative technology in wireless communications, enabling enhanced performance and quality of service (QoS) of wireless systems in harsh urban environments due to their relatively low cost and advanced signal processing capabilities. Generally, BD-RIS systems are employed to improve robustness, increase achievable rates, and enhance energy efficiency of wireless systems in both direct and indirect ways. The direct way is to produce a favorable propagation environment via the design of optimized scattering matrices, while the indirect way is to reap additional improvements via the design of multiple-input multiple-output (MIMO) beamformers that further exploit the latter "engineered" medium. In this article, the problem of sum-rate maximization via BD-RIS is examined, with a focus on feasibility, namely low-complexity physical implementation, by enforcing reciprocity in the BD-RIS design. We begin by outlining the system model and formulating an optimization problem that aims to enhance the system's sum-rate by designing a symmetric scattering matrix. In particular, the approach leverages a manifold optimization framework, where a penalty term is added to the objective function to ensure that the symmetry constraint is upheld, with reciprocity further enforced by projecting the obtained solution onto a set of feasible scattering matrices. Simulation results demonstrate the effectiveness of the proposed method in outperforming current state-of-the-art (SotA) approaches in terms of sum-rate maximization.