Flexible Continuous Aperture Arrays

A novel electromagnetic (EM) structure termed flexible continuous aperture array (FCAPA) is proposed, which incorporates inherent surface flexibility into typical continuous aperture array (CAPA) systems, thereby enhancing the degrees-of-freedom (DoF) of multiple-input multiple-output (MIMO) systems equipped with this technology. By formulating and solving a downlink multi-user beamforming optimization problem to maximize the weighted sum rate (WSR) of the multiple users with FCAPA, it is shown that the proposed structure outperforms typical CAPA systems by a wide margin, with performance increasing with increasing morphability.

Fractional Programming and Manifold Optimization for Reciprocal BD-RIS Scattering Matrix Design

We investigate the problem of maximizing the sum-rate performance of a beyond-diagonal reconfigurable intelligent surface (BD-RIS)-aided multi-user (MU)-multiple-input single-output (MISO) system using fractional programming (FP) techniques. More specifically, we leverage the Lagrangian Dual Transform (LDT) and Quadratic Transform (QT) to derive an equivalent objective function which is then solved iteratively via a manifold optimization framework. It is shown that these techniques reduce the complexity of the optimization problem for the scattering matrix solution, while also providing notable performance gains compared to state-of-the-art (SotA) methods under the same system conditions. Simulation results confirm the effectiveness of the proposed method in improving sum-rate performance.

The IEEE Signal Processing Society's Leading Role in Developing Standards for Computational Imaging and Sensing: Part II

In every imaging or sensing application, the physical hardware creates constraints that must be overcome or they limit system performance. Techniques that leverage additional degrees of freedom can effectively extend performance beyond the inherent physical capabilities of the hardware. An example includes synchronizing distributed sensors so as to synthesize a larger aperture for remote sensing applications. An additional example is integrating the communication and sensing functions in a wireless system through the clever design of waveforms and optimized resource management. As these technologies mature beyond the conceptual and prototype phase they will ultimately transition to the commercial market. Here, standards play a critical role in ensuring success. Standards ensure interoperability between systems manufactured by different vendors and define industry best practices for vendors and customers alike. The Signal Processing Society of the Institute for Electrical and Electronics Engineers (IEEE) plays a leading role in developing high-quality standards for computational sensing technologies through the working groups of the Synthetic Aperture Standards Committee (SASC). In this column we highlight the standards activities of the P3383 Performance Metrics for Integrated Sensing and Communication (ISAC) Systems Working Group and the P3343 Spatio-Temporal Synchronization of a Synthetic Aperture of Distributed Sensors Working Group.

Computing on Dirty Paper: Interference-Free Integrated Communication and Computing

Inspired by Costa's pioneering work on dirty paper coding (DPC), this paper proposes a novel scheme for integrated communication and computing (ICC), named Computing on Dirty Paper, whereby the transmission of discrete data symbols for communication, and over-the-air computation (AirComp) of nomographic functions can be achieved simultaneously over common multiple-access channels. In particular, the proposed scheme allows for the integration of communication and computation in a manner that is asymptotically interference-free, by precanceling the computing symbols at the transmitters (TXs) using DPC principles. A simulation-based assessment of the proposed ICC scheme under a single-input multiple-output (SIMO) setup is also offered, including the evaluation of performance for data detection, and of mean-squared-error (MSE) performance for function computation, over a block of symbols. The results validate the proposed method and demonstrate its ability to significantly outperform state-of-the-art (SotA) ICC schemes in terms of both bit error rate (BER) and MSE.

Integrated Communication and Computing in Time-Varying mmWave Channels

We propose a novel framework for integrated communication and computing (ICC) transceiver design in time-varying millimeter-wave (mmWave) channels. In particular, in order to cope with the dynamics of time-varying mmWave channels, the detection of communication symbols and the execution of an over-the-air computing (AirComp) operation are performed in parallel with channel tracking, as opposed to existing state-of-the-art (SotA) on ICC where perfect knowledge of the channel at all time instances is typically assumed. For clarity of exposition, we consider a single-input multiple-output (SIMO) uplink scenario where multiple single-antenna user equipment (UE) transmit to a base station (BS) equipped with multiple antennas, such that each UE, or edge device (ED), precodes its own transmit signal, while the BS, or access points (APs), also performs receive beamforming. The proposed transceiver framework then estimates channel state information (CSI) and data symbols in parallel, using a bilinear Gaussian belief propagation (BiGaBP) algorithm for joint channel and data detection (JCDE), aided by a channel prediction (CP) algorithm executed before each estimation window at the BS. The AirComp operation is then executed by means of an optimal combination of the residual signal. Simulation results demonstrate the effectiveness of the proposed scheme in performing ICC in challenging time-varying mmWave channels, with minimal degradation to both communication and computing performance.

Fundamental Limits of Rigid Body Localization

We consider a novel approach to formulate the Cram\'er-Rao Lower Bound (CRLB) for the rigid body localization (RBL) problem, which allows us to assess the fundamental accuracy limits on the estimation of the translation and rotation of a rigid body with respect to a known reference. To that end, we adopt an information-centric construction of the Fisher information matrix (FIM), which allows to capture the contribution of each measurement towards the FIM, both in terms of input measurement types, as well as of their error distributions. Taking advantage of this approach, we derive a generic framework for the CRLB formulation, which is applicable to any type of rigid body localization scenario, extending the conventional FIM formulation suitable for point targets to the case of a rigid body whose location include both translation vector and the rotation matrix (or alternative the rotation angles), with respect to a reference. Closed-form expressions for all CRLBs are given, including the bound incorporating an orthonormality constraint onto the rotation matrix. Numerical results illustrate that the derived expression correctly lower-bounds the errors of estimated localization parameters obtained via various related state-of-the-art (SotA) estimators, revealing their accuracies and suggesting that SotA RBL algorithms can still be improved.

Chirp-Permuted AFDM: A New Degree of Freedom for Next-Generation Versatile Waveform Design

We present a novel multicarrier waveform, termed chirp-permuted affine frequency division multiplexing (CP-AFDM), which introduces a unique chirp-permutation domain on top of the chirp subcarriers of the conventional AFDM. Rigorous analysis of the signal model and waveform properties, supported by numerical simulations, demonstrates that the proposed CP-AFDM preserves all core characteristics of affine frequency division multiplexing (AFDM) - including robustness to doubly-dispersive channels, peak-to-average power ratio (PAPR), and full delay-Doppler representation - while further enhancing ambiguity function resolution and peak-to-sidelobe ratio (PSLR) in the Doppler domain. These improvements establish CP-AFDM as a highly attractive candidate for emerging sixth generation (6G) use cases demanding both reliability and sensing-awareness. Moreover, by exploiting the vast degree of freedom in the chirp-permutation domain, two exemplary multifunctional applications are introduced: an index modulation (IM) technique over the permutation domain which achieves significant spectral efficiency gains, and a physical-layer security scheme that ensures practically perfect security through permutation-based keying, without requiring additional transmit energy or signaling overhead.

Quaternion-Domain Super MDS for Robust 3D Localization

This paper proposes a novel low-complexity three-dimensional (3D) localization algorithm for wireless sensor networks, termed quanternion-domain super multi-dimensional scaling (QD-SMDS). The algorithm is based on a reformulation of the SMDS, originally developed in the real domain, using quaternion algebra. By representing 3D coordinates as quaternions, the method constructs a rank-1 Gram edge kernel (GEK) matrix that integrates both relative distance and angular information between nodes, which enhances the noise reduction effect achieved through low-rank truncation employing singular value decomposition (SVD), thereby improving robustness against information loss. To further reduce computational complexity, we also propose a variant of QD-SMDS that eliminates the need for the computationally expensive SVD by leveraging the inherent structure of the quaternion-domain GEK matrix. This alternative directly estimates node coordinates using only matrix multiplications within the quaternion domain. Simulation results demonstrate that the proposed method significantly improves localization accuracy compared to the original SMDS algorithm, especially in scenarios with substantial measurement errors. The proposed method also achieves comparable localization accuracy without requiring SVD.

Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications

Quantum computing is poised to redefine the algorithmic foundations of communication systems. While quantum superposition and entanglement enable quadratic or exponential speedups for specific problems, identifying use cases where these advantages yield engineering benefits is, however, still nontrivial. This article presents the fundamentals of quantum computing in a style familiar to the communications society, outlining the current limits of fault-tolerant quantum computing and uncovering a mathematical harmony between quantum and wireless systems, which makes the topic more enticing to wireless researchers. Based on a systematic review of pioneering and state-of-the-art studies, we distill common design trends for the research and development of quantum-accelerated communication systems and highlight lessons learned. The key insight is that classical heuristics can sharpen certain quantum parameters, underscoring the complementary strengths of classical and quantum computing. This article aims to catalyze interdisciplinary research at the frontier of quantum information processing and future communication systems.

Metasurfaces-Integrated Doubly-Dispersive MIMO: Channel Modeling and Optimization

The doubly-dispersive (DD) channel structure has played a pivotal role in wireless communications, particularly in high-mobility scenarios and integrated sensing and communications (ISAC), due to its ability to capture the key fading effects experienced by a transmitted signal as it propagates through a dynamic medium. However, extending the DD framework to multiple-input multiple-output (MIMO) systems, especially in environments artificially enhanced by reconfigurable intelligent surfaces (RISs) and stacked intelligent metasurfaces (SIM), remains a challenging open problem. In this chapter, a novel metasurfaces-parametrized DD (MPDD) channel model that integrates an arbitrary number of RISs, while also incorporating SIM at both the transmitter and receiver is introduced. Next, the application of this model to some key waveforms optimized for DD environments -- namely orthogonal frequency division multiplexing (OFDM), orthogonal time frequency space (OTFS), and affine frequency division multiplexing (AFDM) -- is discussed. Finally, the programmability of the proposed model is highlighted through an illustrative application, demonstrating its potential for enhancing waveform performance in SIM-assisted wireless systems.