2025/09/22 by Kabuto Arai, Arai, Kabuto, Koji Ishibashi +9
Computer Science · Engineering · #Advanced MIMO Systems Optimization #Advanced Wireless Communication Techniques #FOS: Electrical engineering #Signal Processing (eess.SP) #Wireless Communication Networks Research #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2509.17916
openalex publication_date 2025/09/22 · openalex created_date 2025/10/17 · openalex updated_date 2026/07/28
This paper proposes a joint optimization of pilot subcarrier allocation and non-orthogonal sequence for multiple-input-multiple-output (MIMO)-orthogonal frequency-division multiplexing (OFDM) systems under compressed sensing (CS)-based channel estimation exploiting delay and angle sparsity. Since the performance of CS-based approaches depends on a coherence metric of the sensing matrix in the measurement process, we formulate a joint optimization problem to minimize this coherence. Due to the discrete nature of subcarrier allocation, a straightforward formulation of the joint optimization results in a mixed-integer nonlinear program (MINLP), which is computationally intractable due to the combinatorial explosion of allocation candidates. To overcome the intractability of discrete variables, we introduce a block sparse penalty for pilots across all subcarriers, which ensures that the power of some unnecessary pilots approaches zero. This framework enables joint optimization using only continuous variables. In addition, we propose an efficient computation method for the coherence metric by exploiting the structure of the sensing matrix, which allows its gradient to be derived in closed form, making the joint optimization problem solvable in an efficient way via a gradient descent approach. Numerical results confirm that the proposed pilot sequence exhibits superior coherence properties and enhances the CS-based channel estimation performance.