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Hong Kong Metropolitan University

Academic institutionasia · hk
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Research library5linked papers
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Selected work

Representative Papers

CSI Reconstruction in Fluid Antenna Systems Without Spatial Covariance Priors

Aug 10, 2026

This work addresses the challenge of reconstructing full-port channel state information (CSI) in fluid antenna systems, where hardware constraints permit observation of CSI from only a limited number of ports and prior spatial covariance statistics are unavailable. Leveraging the Clarke isotropic scattering model, the study reveals that the channel resides in a low-dimensional modal subspace dictated by the scattering environment. It establishes, for the first time, a theoretical framework for CSI recoverability without requiring prior statistical knowledge and derives an exact feasibility threshold. By integrating spatial modal modeling, error decomposition analysis, and low-rank recovery techniques, the proposed approach enables high-fidelity reconstruction of full-port CSI using only a few active ports, substantially reducing the number of required RF chains, pilot overhead, and training data.

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Practical Portfolio Optimization with Metaheuristics:Pre-assignment Constraint and Margin Trading

Mar 20, 2025

This paper addresses portfolio optimization under investor preferences and margin trading mechanisms. Methodologically, it proposes a constraint-guided metaheuristic framework that: (1) explicitly incorporates pre-allocation constraints to encode investor preferences and reduce the feasible solution space; (2) endogenizes margin trading costs and leverage risk into a dynamic return model; and (3) replaces the conventional Sharpe ratio with the Rare Performance Ratio (RPR) to enhance robustness and practicality in risk-adjusted performance evaluation. The framework innovatively integrates pre-allocation constraints and leverage-aware strategies within standard metaheuristics—including genetic algorithms and particle swarm optimization—enabling synergistic constraint handling and search guidance. Empirical results across realistic market settings demonstrate statistically significant outperformance over traditional benchmarks, with an average 18.7% improvement in risk-adjusted returns. This validates both the methodological efficacy and operational deployability of the proposed approach in practical investment management.

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Recent publications

Latest Papers

CSI Reconstruction in Fluid Antenna Systems Without Spatial Covariance Priors

Aug 10, 2026

This work addresses the challenge of reconstructing full-port channel state information (CSI) in fluid antenna systems, where hardware constraints permit observation of CSI from only a limited number of ports and prior spatial covariance statistics are unavailable. Leveraging the Clarke isotropic scattering model, the study reveals that the channel resides in a low-dimensional modal subspace dictated by the scattering environment. It establishes, for the first time, a theoretical framework for CSI recoverability without requiring prior statistical knowledge and derives an exact feasibility threshold. By integrating spatial modal modeling, error decomposition analysis, and low-rank recovery techniques, the proposed approach enables high-fidelity reconstruction of full-port CSI using only a few active ports, substantially reducing the number of required RF chains, pilot overhead, and training data.

0 citationsRead paper

Practical Portfolio Optimization with Metaheuristics:Pre-assignment Constraint and Margin Trading

Mar 20, 2025

This paper addresses portfolio optimization under investor preferences and margin trading mechanisms. Methodologically, it proposes a constraint-guided metaheuristic framework that: (1) explicitly incorporates pre-allocation constraints to encode investor preferences and reduce the feasible solution space; (2) endogenizes margin trading costs and leverage risk into a dynamic return model; and (3) replaces the conventional Sharpe ratio with the Rare Performance Ratio (RPR) to enhance robustness and practicality in risk-adjusted performance evaluation. The framework innovatively integrates pre-allocation constraints and leverage-aware strategies within standard metaheuristics—including genetic algorithms and particle swarm optimization—enabling synergistic constraint handling and search guidance. Empirical results across realistic market settings demonstrate statistically significant outperformance over traditional benchmarks, with an average 18.7% improvement in risk-adjusted returns. This validates both the methodological efficacy and operational deployability of the proposed approach in practical investment management.

0 citationsRead paper