arXiv subjects

Seongkyu Jung

Publications and source records attributed to Seongkyu Jung.

3 recordsLinked to original sources

arXiv2026

Efficient RF Chain Selection for MIMO Integrated Sensing and Communications: A Greedy Approach

In multiple-input multiple-output integrated sensing and communication (MIMO ISAC) systems, radio frequency chain (i.e., RF chain) selection plays a vital role in reducing hardware cost, power consumption, and computational complexity. However, designing an effective RF chain selection strategy is challenging due to the disparity in performance metrics between communication and sensing: mutual information (MI) versus beam-pattern mean-squared error (MSE) or the Cramér-Rao lower bound (CRLB). To overcome this, we propose a low-complexity greedy RF chain selection framework maximizing a unified MI-based performance metric applicable to both functions. By decomposing the total MI into individual contributions of each RF chain, we introduce two approaches: greedy eigen-based selection (GES) and greedy cofactor-based selection (GCS), which iteratively identify and remove the RF chains with the lowest contribution. We further extend our framework to beam selection for beamspace MIMO ISAC systems, introducing diagonal beam selection (DBS) as a simplified solution. Simulation results show that our proposed methods achieve near-optimal performance with significantly lower complexity than exhaustive search, demonstrating their practical effectiveness for MIMO ISAC systems.

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arXiv2026

Fractional Programming for Kullback-Leibler Divergence in Hypothesis Testing

Maximizing the Kullback-Leibler divergence (KLD) is a fundamental problem in waveform design for active sensing and hypothesis testing, as it directly relates to the error exponent of detection probability. However, the associated optimization problem is highly nonconvex due to the intricate coupling of log-determinant and matrix trace terms. Existing solutions often suffer from high computational complexity, typically requiring matrix inversion at every iteration. In this paper, we propose a computationally efficient optimization framework based on fractional programming (FP). Our key idea is to reformulate the KLD maximization problem into a sequence of tractable quadratic subproblems using matrix FP. To further reduce complexity, we introduce a nonhomogeneous relaxation technique that replaces the costly linear system solver with a simple closed-form update, thereby reducing the per-iteration complexity to quadratic order. To compensate for the convergence speed trade-off caused by relaxation, we employ an acceleration method called STEM by interpreting the iterative scheme as a fixed-point mapping. The resulting algorithm achieves significantly faster convergence rates with low per-iteration cost. Numerical results demonstrate that our approach reduces the total runtime by orders of magnitude compared to a state-of-the-art benchmark. Finally, we apply the proposed framework to a multiple random access scenario and a joint integrated sensing and communication scenario, validating the efficacy of our framework in such applications.

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arXiv2026

The MIMO-ME-MS Channel: Analysis and Algorithm for Secure MIMO Integrated Sensing and Communications

This paper addresses precoder design for secure multiple-input multiple-output (MIMO) integrated sensing and communications (ISAC) systems. We introduce a MIMO channel with a multiple-antenna eavesdropper and a multiple-antenna sensing receiver (MIMO-ME-MS) and analyze the fundamental performance limits of this tripartite tradeoff. Using sensing mutual information, we formulate the precoder design as a nonconvex weighted sum rate maximization problem. A high signal-to-noise ratio analysis based on a subspace decomposition characterizes the maximum weighted degrees of freedom. This analysis reveals the structure of a quasi-optimal precoder that must span the ``useful subspace'' and demonstrates the inadequacy of extending known schemes from simpler wiretap or ISAC channels. To solve this nonconvex problem, we develop a practical two-stage iterative algorithm that alternates between a sequential basis construction stage and a power allocation stage that solves the resulting difference-of-convex program. We demonstrate that the proposed method captures the desirable precoder structure identified in our analysis and achieves substantial performance gains in the MIMO-ME-MS channel.

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