Institution profile

Koç University

Academic institutioneurope · tr
Official website
Research library140linked papers
Opportunities0open roles
Selected work

Representative Papers

A Novel Partitioning Scheme for RIS Identification and Beamforming

Nov 14, 2025IEEE Wireless Communications Letters

This paper addresses the resource allocation challenge in reconfigurable intelligent surface (RIS)-enabled integrated sensing and communication (ISAC) systems, where RIS must simultaneously support target detection and communication beamforming. We propose a dynamic functional partitioning method that adaptively divides RIS elements into two dedicated subsets—sensing-only and beamforming-only—and jointly optimizes their spatial allocation and phase profiles. The design explicitly incorporates heterogeneous performance metrics: it enforces detection probability and false alarm rate constraints for sensing reliability while maximizing the communication signal-to-noise ratio (SNR). Our key contribution lies in the first explicit modeling of disparate sensing and communication objectives, coupled with theoretical analysis and an efficient iterative optimization algorithm. Simulation results demonstrate that the proposed scheme achieves up to 3.2 dB SNR gain and a 12.7% improvement in detection accuracy over static partitioning and conventional joint design baselines, thereby significantly enhancing both resource efficiency and task-specific performance in ISAC systems.

1 citationsRead paper

Scalable Clustered Network Connectedness with Control Variables: Theory and Application to Global Banking

Sep 05, 2026

We extend the clustered connectedness framework of Buchwalter, Diebold and Yilmaz (2026) in two complementary directions that improve the robustness and interpretability of cross-cluster connectedness. First, we develop a diagnostic for residual ordering sensitivity by characterizing the distribution of cluster-level net connectedness across all admissible identification orderings and, in particular, by pairing first- and last-position orderings while holding fixed the relative ordering of all other clusters. Second, we introduce a dedicated cluster of control variables to absorb variation associated with observed common macro-financial factors while preserving the computational scalability of the clustered framework. The control cluster is fixed first, and bank innovations are residualized with respect to it before the remaining bank clusters are permuted and orthogonalized as usual, leaving the number of admissible bank-cluster identification strategies unchanged. Under the maintained recursive assumption that control-cluster innovations are contemporaneously exogenous to bank-cluster innovations, the remaining cross-cluster connectedness among the bank clusters can be interpreted as bank-to-bank transmission net of those observed common-factor shocks. We apply the methodology to seventy-one global banks grouped into seven regional clusters over 2003--2024. The treatment of common macro-financial factors materially affects both system-wide cross-group connectedness and cluster-level net positions. Placing the controls in a dedicated first cluster also substantially reduces paired first-versus-last ordering sensitivity across all seven bank clusters, with especially large reductions for the United States and the European clusters.

0 citationsRead paper
Recent publications

Latest Papers

Scalable Clustered Network Connectedness with Control Variables: Theory and Application to Global Banking

Sep 05, 2026

We extend the clustered connectedness framework of Buchwalter, Diebold and Yilmaz (2026) in two complementary directions that improve the robustness and interpretability of cross-cluster connectedness. First, we develop a diagnostic for residual ordering sensitivity by characterizing the distribution of cluster-level net connectedness across all admissible identification orderings and, in particular, by pairing first- and last-position orderings while holding fixed the relative ordering of all other clusters. Second, we introduce a dedicated cluster of control variables to absorb variation associated with observed common macro-financial factors while preserving the computational scalability of the clustered framework. The control cluster is fixed first, and bank innovations are residualized with respect to it before the remaining bank clusters are permuted and orthogonalized as usual, leaving the number of admissible bank-cluster identification strategies unchanged. Under the maintained recursive assumption that control-cluster innovations are contemporaneously exogenous to bank-cluster innovations, the remaining cross-cluster connectedness among the bank clusters can be interpreted as bank-to-bank transmission net of those observed common-factor shocks. We apply the methodology to seventy-one global banks grouped into seven regional clusters over 2003--2024. The treatment of common macro-financial factors materially affects both system-wide cross-group connectedness and cluster-level net positions. Placing the controls in a dedicated first cluster also substantially reduces paired first-versus-last ordering sensitivity across all seven bank clusters, with especially large reductions for the United States and the European clusters.

0 citationsRead paper