Jul 2026· IEEE Transactions on Communications· Vol 74, pp. 12833-12851· 0 citations· 55 references
EngineeringComputer Science
Abstract
This paper examines the power consumption (PC) efficiency of a mixed near- and far-field (MF) simultaneous wireless information and power transfer (SWIPT) system underpinned by a hybrid beamforming (HB)-based modular extra-large multiple-input-multiple output (XL-MIMO) array. Multiple information decoding (ID) and energy harvesting (EH) users are served by multiple constituent subarrays in both the near-field (NF) and far-field (FF) region of the transmit array. A novel decision method is proposed for accurate classification of different field users using Frobenius norm-based frequency correlation of the least square (LS) channel estimates. The NF spatial non-stationarities (SnS) effects entail distinct electromagnetic (EM) visibility regions (VRs), which can be customized to employ strategic activation of the constituent XL-MIMO subarrays. We formulate a two-tier joint optimization problem to minimize the overall PC, considering the power allocation (PA) for both ID and EH users in addition to the subarray activation (SA). This challenging mixed-integer problem is transformed into computationally tractable formulations, accompanied by the development of well-optimized algorithms. Our simulation results demonstrate an overall PC reduction for our proposed PA-SA-HB scheme by up to 93% against the equal PA with full array (FA) and up to 18% with respect to the PA-FA-HB case.
This paper investigates a novel self-sustainable intelligent reflecting surface (IRS)-enhanced multi-input multi-output simultaneous wireless information and power transfer (SWIPT) system under imperfect channel state information. Equipped with an energy harvesting module, the IRS harvests energy from received signals to meet its operational needs. In particular, we focus on maximizing the weighted sum rate (WSR) of all information users (IUs) by jointly optimizing the access point (AP) precoding matrices and IRS reflection coefficient matrix. Meanwhile, the WSR maximization is constrained by the maximum transmit power of the AP and by the harvested power requirements of both IRS and energy users (EUs). To address the highly coupled and non-convex problem, we first adopt the minimum mean square error method to recast the WSR maximization problem into a simpler equivalent problem and split the transformed problem into two sub-problems, which can be tackled alternatively. In addition, we employ the successive convex approximation (SCA) technique to approximate the non-convex sub-problems. Furthermore, we adopt the Lagrangian dual transformation, majorization-minimization method and penalty-based technique to obtain the closed-form solutions. The simulation results demonstrate the effectiveness of the proposed algorithm and show that, with proper IRS deployment, the proposed self-sustainable IRS can achieve 96%–99% of the WSR obtained by the externally powered IRS under the default simulation setup, while eliminating the need for an external power supply.
Wanli Ma, Xiaokai Song, Zhendong Yin et al.· IEEE Transactions on Communi...· 0 citations
This paper investigates asymmetric spatial modulation (ASM) for multi-user multiple-input multiple-output (MIMO) systems operating in the near-field (NF) region. Considering spherical-wave propagation, closed-form expressions for the average bit error probability (BEP) of both users are derived under maximum likelihood (ML) detection. The analytical framework is validated through Monte Carlo simulations using five million transmitted symbols. Numerical results compare the near-field (NF) and far-field (FF) channel models. When users are located in the NF region, for example at a distance of 0.2 m from the array, the NF model achieves lower BER across the entire signal-to-noise ratio range. At an SNR of 20 dB, the BER gap between NF and FF increases from approximately 1.65e-3 for 16 transmit antennas to about $\mathbf{5. 0 1 e}-\mathbf{3}$ for 32 transmit antennas. The proposed ASM scheme also provides comparable BEP performance for the two users while enabling simultaneous transmission within the same MIMO resource block. These results show that near-field spatial characteristics can be effectively exploited for multi-user transmission in large-scale and high-frequency MIMO systems.
Quynh Nhu Nguyen, Do Hoang Anh, Thai-Hoc Vu et al.· IEEE International Conferenc...· 0 citations
This paper investigates a near-field (NF) multiple-input multiple-output (MIMO) communication system equipped with dual uniform planar arrays (UPAs). We first develop a generalized geometric model to calculate the 3D distance between arbitrary antenna elements across the transmitter and receiver panels. Leveraging the distance analysis, we derive a closed-form near-field to far-field (NF-FF) boundary for dual-UPA configurations. By exploiting the geometric structure of the UPAs, we further decompose the near-field channel matrix into a Kronecker-product of two lower-dimensional matrices. This decomposition enables a low-complexity NF beamforming design for achievable-rate maximization. Numerical results validate the analysis and demonstrate that the conventional Rayleigh distance is a special case of the generalized model. Furthermore, the proposed beamforming design achieves near-optimal rate performance while significantly reducing the computational complexity compared to state-of-the-art NF beamforming methods.
Lingeng Zheng, Xing Hao, Ziru Chen et al.· 0 citations
This paper proposes a tri-hybrid beamforming (tri-HBF) scheme with antenna-selection (AS)-based reconfigurable sub-arrays for full-duplex (FD) massive multiple-input multiple-output (mMIMO) systems. A sub-connected HBF architecture is adopted, where AS is performed in a group-wise manner to avoid excessive switch-network and routing complexity. An alternating optimization (AO) algorithm is developed to jointly optimize the i) active antenna subsets considering a self-interference (SI)-aware utility, ii) analog beamformers through projected gradient ascent (PGA), iii) digital precoders/combiners via SI-aware regularized zero-forcing (RZF) and minimum mean-square error (MMSE) updates, and iv) DL/UL power allocation by successive convex approximation (SCA). To capture realistic electromagnetic coupling in FD mMIMO operation, experimental SI channels based on an 8x8 Tx-8x8 Rx FD array prototype are incorporated into the study. The proposed AS-aided tri-HBF optimization scheme exhibits robust convergence across various base station configurations and effectively balances desired-signal enhancement, SI mitigation, and multi-user interference suppression in FD mMIMO operation. Illustrative results show that selective activation can outperform full-array activation, achieving a 21.3% higher average sum-rate and a more consistent performance across user realizations, with power-efficiency benefits by reducing the active paths. A comprehensive study is conducted to characterize how the number of activated antennas affects the achievable rate, user-channel coherence, and SI suppression gain. Compared with various selection baselines, it achieves a 45.1% improvement in average sum-rate, with average DL and UL rate gains of 36.9% and 82.9%, respectively. In addition, beam-level isolation better than 63 dB is achieved, further confirming the effectiveness of the proposed SI-aware design.
In this paper, we investigate a full-duplex (FD) cell-free massive multiple-input multiple-output (CF mMIMO) architecture with millimeter wave (mmWave) fronthaul, where uplink (UL) and downlink (DL) payload data and control signaling must be simultaneously supported. We first revisit the fronthaul requirements of representative wired low physical layer functional splits and show that the FD operation further aggravates the wired fronthaul bottleneck. To improve scalability beyond purely wired deployments, we propose a wireless fronthaul architecture in which the fronthaul links between access points (APs) and the central processing unit (CPU) operate over mmWave bands that are spectrally disjoint from the sub-6 GHz access links. Then, instead of forwarding antenna-domain baseband samples, we exploit low-dimensional sufficient statistics and develop a wireless fronthaul transmission framework. For the DL, Gram-regularized zero-forcing (Gram-RZF) and Gram-weighted minimum mean-square error (Gram-WMMSE) beamforming methods are designed using user-domain Gram matrices, thereby avoiding the transport of instantaneous channel state information. For the UL, the remaining two phases convey local UL signal estimates and slow-timescale second-order moments, enabling centralized large-scale fading decoding (LSFD) at the CPU. All UL information is delivered through subspace-domain wireless fronthaul transmission, together with a receive-subspace demultiplexing mechanism at the CPU for reliable packet recovery. Numerical results validate the proposed framework, demonstrating remarkable improvements over conventional half-duplex CF mMIMO.
Zhilong Liu, Jiayi Zhang, Enyu Shi et al.· IEEE Transactions on Wireles...· 0 citations
In integrated sensing and communication (ISAC) systems, stringent sensing performance constraints can severely limit the power available for communication. Hybrid reconfigurable intelligent surfaces (HRISs) with capabilities of both passive reflection and active signal amplification can significantly improve communication performance in the power-limited regime. This motivates us to analyze and optimize the performance of an HRIS-aided multiple-input-multiple-output (mMIMO) ISAC system. We first estimate the effective uplink/downlink channels using the minimum mean square error method. We then derive closed-form expressions for the communication sum-rate and sensing Cram\'er-Rao lower bound (CRLB). It is shown that under the equal power allocation strategy, the CRLB remains independent of the HRIS coefficients. Then, we formulate a joint optimization problem of power allocation and HRIS beamforming to maximize the communication sum-rate while ensuring specified sensing CRLB constraints. To solve the formulated non-convex problem, we propose an alternating optimization algorithm based on fractional programming and successive convex approximation. Extensive simulations validate our analysis and proposed algorithm, showing significant improvements in both communication and sensing performances enabled by the HRIS. For example, an HRIS with only $4$ active elements offers $97.30\%$ improvement in the communication sum-rate, while ensuring a sensing CRLB constraint of $-30$ dB.
Smriti Uniyal, Tian-Yu Fang, M. di Renzo et al.· 0 citations
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