Phase noise (PN) significantly degrades the performance of millimeter-wave (mmWave) wireless communication systems. To mitigate this challenge, we propose the amplitude-phase-sphere block modulation (APSBM) scheme, which integrates amplitude-shift keying, phase-shift keying, and sphere modulation. Exploiting the Wiener random walk characteristic of PN, APSBM carries information on the relative amplitude and phase between consecutive symbols, thereby counteracting the impact of common PN. Immunity to residual PN in the scheme is further enhanced through a three-dimensional spherical constellation and modulation configurations. We also propose flexible detection strategies (joint, parallel, and cascaded) at the receiver to accommodate diverse application scenarios, minimizing the influence of PN while maintaining a low computational burden. Simulation and experimental results demonstrate that in the presence of PN, APSBM outperforms quadrature amplitude modulation (QAM), circular QAM, and spiral modulation, achieving a lower peak-to-average power ratio, a reduced bit error rate, and a higher achievable information rate. The proposed modulation and demodulation scheme is particularly effective under high PN conditions, offering a robust solution for PN mitigation in mmWave wireless communication systems.

In OFDM wireless communications, power amplifier nonlinearity generates significant out-of-band (OOB) emissions and in-band distortion, conventionally requiring large power back-offs to address both issues simultaneously. We propose a forward distortion compensation (FDC) scheme using amplitude-phase-frequency block modulation (APFBM) that decouples OOB emission suppression from in-band distortion management, enabling reliable transmission even under severe power amplifier nonlinearity. At the transmitter, in-band distortion is intentionally introduced to facilitate aggressive OOB emission suppression, while APFBM manages bit mapping and imposes a power-sum constraint on information-carrying subcarriers. At the receiver, this power-sum constraint guides the compensation for in-band distortion, ensuring reliable information recovery. This compensation strategy also relaxes digital pre-distortion (DPD) accuracy requirements, permitting a simpler Sigmoid-based static DPD focused solely on OOB suppression and eliminating feedback circuits. The experimental results show a relative gain of 4.4 dB with a power back-off of 5.2 dB compared to nonlinear transmission based on quadrature amplitude modulation with equivalent processing at 4.9 GHz, while a relative gain of 2.6 dB is achieved at 26.5 GHz. This approach achieves superior energy efficiency and spectral efficiency trade-offs, enhancing coverage and performance in wireless communications.

Operating power amplifiers (PAs) at lower input back-off (IBO) levels is an effective way to improve PA efficiency, but often introduces severe nonlinear distortion that degrades transmission performance. Amplitude-phase-time block modulation (APTBM) has recently emerged as an effective solution to this problem. The intrinsic amplitude and phase constraints of each APTBM block can be leveraged to mitigate PA-induced nonlinear distortion via constraint-guided signal reconstruction. However, existing reconstruction methods apply these constraints only heuristically and statistically, limiting the achievable IBO reduction and PA efficiency improvement. This paper addresses this limitation by decomposing the nonlinear distortion into dominant and residual components, and accordingly develops a novel two-stage signal reconstruction algorithm consisting of coarse and fine reconstruction stages. The coarse reconstruction stage eliminates the dominant distortion by jointly exploiting the APTBM block structure and PA nonlinear characteristics. Subsequently, the fine reconstruction stage minimizes the residual distortion by casting it as a nonconvex optimization problem subject to explicit APTBM constraints, for which a closed-form solution is derived. The proposed algorithm is validated through comprehensive numerical simulations and testbed experiments. Results show that, without compromising transmission quality, the proposed algorithm enables an additional IBO reduction of approximately 5 dB in simulations and 2 dB in experiments over baseline methods, yielding relative PA efficiency improvements of 77.8% and 30.9%, respectively.

A large proportion of the carbon emissions associated with wireless communications stem from electricity consumption during operation. Spectral efficiency (SE) and energy efficiency (EE) are fundamental considerations in wireless communications. However, nonlinear amplification results in a trade-off between these factors. Various techniques have been developed to address this issue, including the frequently-used amplifier linearization. Nonetheless, these approaches have limitations in terms of versatility and complexity, making them impractical for modern broadband multiantenna wireless communications. Here, an amplitude-phase-time block modulation (APTBM) scheme and a corresponding demodulation scheme for resisting amplifier nonlinearity are proposed, establishing a new paradigm for balancing the SE and EE. At the transmitter, the symbol block, consisting of two time-domain consecutive symbols, is used to carry information. Simultaneously, specific amplitude and phase constraints are imposed on the symbols within a block. At the receiver, nonlinearly distorted symbols can be effectively demodulated by utilizing these constraints. Numerical and experimental results show that the proposed APTBM demonstrates excellent nonlinear transmission characteristics compared with conventional offset quadrature amplitude modulation.

Passing-object detection is a basic function in an intelligent environment. However, as one of the main functions in an integrated sensing and communication system, it is still challenging to achieve due to the dense multipath propagation in typical indoor environments. First, a Fresnel zone model and a diffraction model are constructed from indoor radio wave propagation characteristics to estimate the first Fresnel zone maximum (FFZM) and phase difference (PD), both of which enable the utilization of antenna pairs to determine the existence and passing direction of an object. Next, using a mixture of the FFZM and PD, a joint detection algorithm (JDA) for passing objects is proposed for a multiantenna system, in which the dynamic time warping method is applied to obtain the signal similarity between antennas. In the preprocessing stage of the proposed JDA, the minimum delay sequence is used to extract the passing period, and an improved trilinear parallel factor decomposition method is used to remove multipath interference. For experimental demonstration, the proposed JDA is implemented using a software radio platform and applied to WLAN sensing. The measurement results show that the proposed JDA can achieve very low missing alarm and direction error rates for both single-passing and multipassing scenarios.