Viterbi State Selection for Discrete Pinching Antenna Systems

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.

Constellation Design and Detection under Generalized Hardware Impairments

This paper presents a maximum-likelihood detection framework that jointly mitigates hardware (HW) impairments in both amplitude and phase. By modeling transceiver distortions as residual amplitude and phase noise, we introduce the approximate phase-and-amplitude distortion detector (PAD-D), which operates in the polar domain and effectively mitigates both distortion components through distortion-aware weighting. The proposed detector performs reliable detection under generalized HW impairment conditions, achieving substantial performance gains over the conventional Euclidean detector (EUC-D) and the Gaussian-assumption phase noise detector (GAP-D), which is primarily designed to address phase distortions. In addition, we derive a closed-form high-SNR symbol error probability (SEP) approximation, which offers a generic analytical expression applicable to arbitrary constellations. Simulation results demonstrate that the PAD-D achieves up to an order-of-magnitude reduction in the error floor relative to EUC-D and GAP-D for both high-order quadrature amplitude modulation (QAM) and super amplitude phase-shift keying (SAPSK) constellations, establishing a unified and practical framework for detection under realistic transceiver impairments. Building on this framework, we further develop optimized constellations tailored to PAD-D, where the symbol positions are optimized in the complex plane to minimize SEP. The optimality of these constellations is confirmed through extensive simulations, which also verify the accuracy of the proposed analytical SEP approximation, even for the optimized designs.

OFDMA for Pinching Antenna Systems

Pinching-antenna (PA) systems route millimeter wave (mmWave) signals through a leaky waveguide and radiate them at "pinch" apertures, offering low-cost line-of-sight (LoS) coverage. However, when multiple PAs serve multiple users simultaneously, the downlink channel becomes strongly frequency-selective, creating inter-symbol interference (ISI) that existing single-carrier designs overlook. This paper models the overall channel as a finite impulse response (FIR) filter, characterizes its frequency selectivity, and explicitly accounts for the resulting ISI. To overcome ISI, we introduce an orthogonal frequency-division multiple access (OFDMA)-based framework and formulate a max-min resource-allocation problem to achieve user fairness. A lightweight two-stage heuristic-greedy subcarrier assignment, followed by per-user water-filling, achieves near-optimal fairness with polynomial complexity. Simulation results for an indoor layout demonstrate that the proposed scheme notably increases the minimum user rate compared to time-division single-carrier baselines and remains robust under moderate LoS blockage.

Elliptic Curve Modulation (ECM) for Extremely Robust Physical Layer Encryption

This paper introduces Elliptic Curve Modulation (ECM), a novel modulation scheme that can be leveraged to effectively shuffle transmitted data while maintaining symbol error probability (SEP) performance equivalent to unencrypted systems. By utilizing the well-distributed elliptic curve points over the field of large primes, ECM enhances symbol obfuscation, making it a powerful foundation for physical-layer encryption (PLE). Each symbol is mapped from a predefined key while preserving a minimum Euclidean distance constraint, ensuring strong security against adversarial inference without compromising error performance. Building on ECM's strong obfuscation capabilities, we propose ECM with dynamic rotation (ECM-DR) as a practical PLE scheme that achieves near-maximal obfuscation while balancing precomputation complexity. By leveraging a reduced subset of precomputed elliptic curve points and key-based dynamic constellation rotation, ECM-DR ensures that each transmission remains unpredictable, significantly enhancing security compared to traditional PLE schemes without additional computational cost. Security analysis confirms ECM's resilience to brute-force attacks, while numerical results demonstrate its strong obfuscation capabilities. Furthermore, ECM-DR achieves near-maximum information entropy while preserving the SEP performance of unencrypted quadrature amplitude modulation (QAM), offering an extremely robust solution for secure wireless communications.

Cross-Band Modulation Design for Hybrid RF-Optical Systems

We present a novel cross-band modulation framework that combines 3D modulation in the RF domain with intensity modulation and direct detection in the optical domain, the first such integration to enhance communication reliability. By harnessing cross-band diversity, the framework optimizes symbol mapping across RF and optical links, significantly boosting mutual information (MI) and reducing symbol error probability (SEP). Two practical modulation schemes implement this framework, both using quadrature amplitude modulation in the RF subsystem. The first is a linear cross-band mapping scheme, where RF symbols are mapped to optical intensity values via an analytically tractable optimization that ensures O(1) detection complexity while minimizing SEP. The second employs a deep neural network-generated (DNN-Gen) 3D constellation with a custom loss function that adaptively optimizes symbol placement to maximize MI and minimize SEP. Although DNN-Gen incurs higher computational complexity than the linear approach, it adapts the 3D constellation to varying signal-to-noise ratios, yielding significant performance gains. Furthermore, we derive a theoretical MI benchmark for the linear scheme, offering insights into the fundamental limits of RF-optical cross-band communication. Extensive Monte Carlo simulations confirm that both schemes outperform SoA cross-band modulation techniques, including cross-band pulse amplitude modulation, with notable improvements. Additionally, DNN-Gen maintains high performance over a range of RF SNRs, lessening the need for exhaustive training at every operating condition. Overall, these results establish our cross-band modulation framework as a scalable, high-performance solution for next-generation hybrid RF-optical networks, balancing low complexity with optimized symbol mapping to maximize system reliability and efficiency.

On the Design of Super Constellations

In the evolving landscape of sixth-generation (6G) wireless networks, which demand ultra high data rates, this study introduces the concept of super constellation communications. Also, we present super amplitude phase shift keying (SAPSK), an innovative modulation technique designed to achieve these ultra high data rate demands. SAPSK is complemented by the generalized polar distance detector (GPD-D), which approximates the optimal maximum likelihood detector in channels with Gaussian phase noise (GPN). By leveraging the decision regions formulated by GPD-D, a tight closed-form approximation for the symbol error probability (SEP) of SAPSK constellations is derived, while a detection algorithm with O(1) time complexity is developed to ensure fast and efficient SAPSK symbol detection. Finally, the theoretical performance of SAPSK and the efficiency of the proposed O(1) algorithm are validated by numerical simulations, highlighting both its superiority in terms of SEP compared to various constellations and its practical advantages in terms of fast and accurate symbol detection.