Qihao Peng

In this paper, we proposed a hybrid simultaneous wireless information and power transfer (SWIPT)-enabled multiple-input multiple-output (MIMO) architecture, where the base station (BS) uses a conventional RF transmitter for downlink transmission and a Rydberg atomic quantum receiver (RAQR) for receiving uplink signal from Internet of Things (IoT) devices. To fully exploit this integration, we jointly design the transmission scheme and the power-splitting strategy to maximize the sum rate, which leads to a non-convex problem. To address this challenge, we first derive closed-form lower bounds on the uplink achievable rates for maximum ratio combining (MRC) and zero-forcing (ZF), as well as on the downlink rate and harvested energy for maximum ratio transmission (MRT) and ZF precoding. Building upon these bounds, we propose an iterative algorithm relying on the best monomial approximation and geometric programming (GP) to solve the non-convex problem. Finally, simulations validate the tightness of our derived lower bounds and demonstrate the superiority of the proposed algorithm over benchmark schemes. Importantly, by integrating RAQR with SWIPT-enabled MIMO, the BS can reliably detect weak uplink signals from IoT devices powered only by harvested energy, enabling battery-free communication.

In this paper, we propose a novel and low-complexity atomic multiple-input multiple-output (MIMO) receiver architecture assisted by a reconfigurable intelligent surface (RIS). By introducing RIS and utilizing pulse amplitude modulation (PAM), the phase of the transmitted signal is effectively aligned with that of the local oscillator (LO), mitigating phase ambiguity and reducing the complexity of the receiver. To tackle the resulting non-convex optimization problem, we reformulate it into a tractable form by minimizing the Frobenius norm of an equivalent matrix, which is solved using an Adam-based gradient descent algorithm. Building upon the optimized equivalent signals , we develop a low-complexity signal detection algorithm and evaluate its performance. Simulation results demonstrate that the proposed RIS-assisted atomic MIMO receiver significantly enhances detection performance compared to the conventional atomic MIMO receivers. More importantly, these results underscore the proposed architecture's potential for scalable and high-performance atomic MIMO communication systems.

Atomic receivers, which leverage the quantum interference termed electromagnetically induced transparency (EIT) for radio-frequency (RF) to optical signal transduction, offer a revolutionary paradigm for next-generation wireless communications. However, current information-theoretic characterizations are predominantly restricted to the Ξ-type of EIT path and rely heavily on the weak-probe approximation, which fails to predict the behavior of the atomic receivers under high signal-to-noise ratio regimes. In this paper, we establish a unified analytical model for atomic receivers, and apply this model to three typical quantum interference paths, i.e., V-type, Λ-type, and Ξ-type configurations. To provide a universal characterization, we propose the quantum coherence transfer coefficient (QCTC) to model the equivalent channel response induced by atomic receivers, using a steady-state perturbation framework built on the three-level EIT solution. The closed-form expressions of equivalent channel gains are then derived for three paths. Our results provide an analytical foundation for future capacity analysis and waveform optimization in atomic radio communication.

In this paper, we propose a low-complexity channel estimation scheme of affine frequency division multiplexing (AFDM) based on generalized complex exponential basis expansion model (GCE-BEM) over doubly selective channels. The GCE-BEM is used to solve fractional Doppler dispersion.Then, the closed-form expression of channel estimation error is derived for the minimum mean square error (MMSE) estimation algorithm. Based on the estimated channel, the MMSE detection is adopt to characterize the impacts of estimated channel on bit error rate (BER) by deriving the theoretical lower bound. Finally, numerical results demonstrate that the proposed scheme effectively mitigates severe inter-Doppler interference (IDoI). Our theoretical performance analysis can perfectly match the Monte-Carlo results, validating the effectiveness of our proposed channel estimation based on GCE-BEM.

Ground-satellite links for 6G networks face critical challenges, including severe path loss, tight size-weight-power limits, and congested spectrum, all of which significantly hinder the performance of traditional radio frequency (RF) front ends. This article introduces the Rydberg Atomic Quantum Receiver (RAQR) for onboard satellite systems, a millimetre-scale front end that converts radio fields to optical signals through atomic electromagnetically induced transparency. RAQR's high sensitivity and high frequency selectivity have the potential to address link-budget, payload, and interference challenges while fitting within space constraints. Theoretically, a hybrid atomic-electronic design that is supported by a consistent signal model achieves spectral efficiency exceeding 6 bit/s/Hz, extends coverage by up to 1000 km, and improves sensing accuracy by two orders of magnitude relative to conventional RF receivers. The paper concludes with integration strategies, distributed-satellite concepts, and open research challenges for bringing RAQR-enabled satellite payloads into service.

This paper proposes a joint precoding–filtering framework based on widely linear (WL) processing to increase the mutual information between the transmitted symbols and the filter output in finite-alphabet multiple-input multiple-output (MIMO) systems. Existing WL transceiver designs have been confined to improper signal constellations. For the first time, this work extends WL processing to proper signals, enabling its application to practical modulations such as QAM. This generalization is realized through a joint transmitter-receiver design that induces controlled impropriety via a conjugate precoding branch and exploits the resulting pseudo-covariance at the receiver. Unlike conventional improper Gaussian signaling designs, the proposed framework operates at the WL precoder level for finite-alphabet MIMO transmission and couples the induced transmit impropriety with receiver-side WL filtering. We first derive an exact per-realization average mutual information (AMI) expression for finite-alphabet inputs under instantaneous channel state information. To reduce the computational cost, we derive a closed-form lower bound on AMI, which serves as a tractable surrogate for optimizing the WL precoding and filtering matrices. We further show that the conventional linear transceiver arises as a degenerate special case of the proposed WL framework, highlighting its generality and structural flexibility. Simulation results demonstrate consistent average AMI gains over linear baselines across modulation formats and antenna configurations. At a target AMI, the proposed design reduces the required SNR by up to 3 dB relative to the linear baseline, establishing the first generally applicable WL transceiver design with superior robustness and practical advantages across diverse communication scenarios. Index Terms—Widely linear precoding, mutual information optimization, MIMO system, joint precoding and filtering design.

Efficient sparse codebook design is a fundamental research problem in sparse code multiple access (SCMA) systems. This paper proposes an advanced nonlinear SCMA (NL-SCMA) framework for downlink channels, which subsumes conventional (linear) SCMA as a special case. Specifically, the proposed NL-SCMA enables a direct mapping of user messages to a superimposed codeword through a nonlinear mapping mechanism, eliminating the need of per-user based codebooks. The design problem therefore shifts from the conventional user codebook design to the nonlinear mapping optimization and superimposed constellation design. We first propose a Lattice constellation-based superimposed constellation by leveraging its advantages in terms of large minimum Euclidean distance (MED), compact constellation volume, design flexibility, low peak-to-average power ratio (PAPR) and favorable shape gain. By analyzing the error patterns of the lattice-based superimposed constellation using pairwise error probability, we prove that the MED of the proposed nonlinear codebook is lower bounded by the so-called "single error pattern". Motivated by this, we propose an error pattern-inspired nonlinear mapping strategy to maximize the MED. Simulation results demonstrate that the proposed nonlinear codebooks significantly outperform state-of-the-art linear codebooks in terms of PAPR, MED, and uncoded and coded error rate performance over Rician fading channels.