Viterbi State Selection for Discrete Pinching Antenna Systems

2025-12-23

AI Summary

Antenna subset selection for waveguide-fed discrete pinched antenna arrays in TDMA-based terrestrial communications faces a combinatorial challenge: maximizing user achievable rate while preserving phase alignment sensitivity—without resorting to exponential-complexity exhaustive search. Method: We propose the novel Viterbi State Selection (VSS) algorithm, which models quantized phases as Trellis states and exploits the phase structure of complex channel gains. By applying dynamic programming–based Trellis search with survivor-path pruning, VSS reduces complexity from exponential to polynomial. Contribution/Results: Theoretically and empirically, VSS achieves identical optimal antenna subsets and achievable rates as exhaustive search, yet with drastically reduced computational overhead. It enables scalable, high-accuracy real-time beamforming for large-scale waveguide-fed arrays, establishing a new paradigm for combinatorial optimization in phased-array systems.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation

Abstract

Pinching antennas enable dynamic control of electromagnetic wave propagation through reconfigurable radiating structures, but selecting an optimal subset of antennas remains a combinatorial problem with exponential complexity. This letter considers antenna subset selection for a waveguide-fed pinching antenna array serving ground users under a time-division access scheme. The achievable rate depends on the coherent superposition of the effective complex channel gains and is therefore highly sensitive to the relative phase alignment of the activated antennas. To address the prohibitive complexity of exhaustive search, we propose a Viterbi state selection (VSS) algorithm that exploits the phase structure of the combined received signal. The trellis state is defined by a quantized representation of the phase of the accumulated complex gain, and a Viterbi-based survivor rule is used to prune dominated antenna subsets across stages. Numerical results demonstrate that the proposed method achieves the same antenna selection and rate as exhaustive search, while reducing the computational complexity from exponential to polynomial in the number of available antennas.

Problem

• Optimizes antenna subset selection for dynamic pinching arrays
• Reduces exponential complexity to polynomial using Viterbi algorithm
• Maintains performance matching exhaustive search in achievable rate

Innovation

• Viterbi algorithm for antenna subset selection
• Quantized phase states in trellis representation
• Complexity reduction from exponential to polynomial