This paper investigates a multi-user pinching-antenna (PA) system, where a single PA is activated on each waveguide. With the maximum ratio transmission (MRT) beamforming, the system spectral efficiency (SE) is studied, where the inter-user interference term complicates the analysis of the SE. To overcome this obstacle, the stationary phase point method (SPPM) is applied to obtain an analytically tractable form of the SE. The analysis reveals that the average inter-user interference can be negligible with a large waveguide spacing even using the MRT. This insight makes the simple MRT appealing for PA-based multi-user communications. Finally, the theoretical analysis is verified through simulations. Our numerical results confirm that 1) with the aid of SPPM, the approximation of the system SE is accurate; 2) and while increasing the waveguide spacing helps reduce the average inter-user interference, it might degrade the SE due to the increased signal propagation path loss.

As a novel antenna array architecture, continuous aperture arrays (CAPAs) have garnered wide attention in recent years. While existing CAPA-based research has predominantly addressed unicast scenarios, the critical area of multicast beamforming remains unexplored. In this paper, a CAPA-based multi-group multicast communication system is investigated. An integral-based CAPA multi-group multicast beamforming design is formulated for the maximization of the system energy efficiency (EE), subject to a minimum multicast SE constraint of each user group and a total transmit power constraint. To address this non-convex fractional programming problem, we employ Dinkelbach’s method, such that the non-convex group-wise multicast spectral efficiency (SE) constraint is first equivalently transformed into a tractable form using auxiliary variables. Then, an efficient block coordinate descent (BCD)-based algorithm is developed to solve the reformulated problem. The CAPA beamforming design subproblem can be optimally solved via the Lagrangian dual method and the calculus of variations (CoV) theory. It reveals that the optimized CAPA beamformer should be a combination of all the groups’ user channels. To further reduce the computational complexity, a low-complexity zero-forcing (ZF)-based approach is proposed. The closed-form ZF CAPA beamformer is derived using each group’s most representative user channel to mitigate the inter-group interference while ensuring the intra-group multicast performance. Then, the beamforming design subproblem in the BCD-based algorithm becomes a convex power allocation subproblem, which can be efficiently solved. Numerical results demonstrate that 1) the CAPA can significantly improve the EE compared to conventional spatially discrete arrays (SPDAs); 2) due to the enhanced spatial resolutions, increasing the aperture size of CAPA is not always beneficial for EE enhancement in multicast scenarios; and 3) wider user distributions of each group cause a significant EE degradation of CAPA compared to SPDA.

Massive multiple-input multiple-output - orthogonal frequency division multiplexing (MIMO-OFDM) systems face the challenge of high channel acquisition overhead while providing significant spectral efficiency (SE). Adjustable phase shift pilots (APSPs) are an effective technique to acquire channels with low overhead by exploiting channel sparsity. In this paper, we extend it to multiple groups and propose multi-group adjustable phase shift pilots (MAPSPs) to improve SE further. We first introduce a massive MIMO-OFDM system model and transform the conventional channel model in the space-frequency domain to the angle-delay domain, obtaining a sparse channel matrix. Then, we propose a method of generating MAPSPs through multiple basic sequences and investigate channel estimation processes. By analyzing the components of pilot interference, we elucidate the underlying mechanism by which interference affects MMSE estimation. Building upon this foundation, we demonstrate the benefit of phase scheduling in MAPSP channel estimation and establish the optimal design condition tailored for scheduling. Furthermore, we propose an implementation scheme based on Zadoff-Chu sequences that includes received signal pre-processing and pilot scheduling methods to mitigate pilot interference. Simulation results indicate that the MAPSP method achieves a lower mean square error (MSE) of estimation than APSP and significantly enhances SE in mobility scenarios.

A continuous aperture array (CAPA)-based multicast communication system is investigated in this paper, where a base station (BS) employs a CAPA to serve a set of multicast users. Under a transmit power constraint, the problem of maximizing the system multicast spectral efficiency (SE) by designing the CAPA beamformer is formulated, where the involved beamformer is a continuous current density function across the CAPA surface. By introducing auxiliary variables, the non-convex multicast SE objective function is first transformed into a tractable form. Then, to address the reformulated problem, an efficient block coordinate descent (BCD)-based algorithm is developed. The CAPA beamforming design subproblem can be optimally solved via the Lagrangian dual method and the calculus of variations (CoV) theory. Numerical results demonstrate that the considered CAPA can significantly improve the multicast SE compared to a conventional spatially discrete array (SPDA).

Estimating massive multiple-input multiple-output - orthogonal frequency division multiplexing (MIMO-OFDM) channels with low pilot overhead presents a significant challenge. Leveraging channel sparsity and pilot argument information (PAI), we propose a multi-group adjustable phase shift pilot (MAPSP) channel estimation method aimed at reducing pilot overhead. We first introduce a sparse channel model in angle-delay domain. Then, we propose the approach of generating phase shift pilots by dividing user terminals (UT) into groups and explore channel estimation based on the sparse channel model. We demonstrate that pilot interference can be mitigated by phase scheduling and received signal pre-processing. Capitalizing on this property, we propose a MAPSP implementation scheme. Simulation results indicate that the proposed MAPSP technique achieves a lower mean square error (MSE) of estimation than APSP and significantly enhances spectral efficiency.

This paper investigates near-field multi-user downlink communications over Ricean fading channels underpinned by the holographic multiple-input multiple-output (HMIMO) technology. We first establish the mutual coupling and radiation efficiency models to characterize the effect of mutual coupling and then formulate the practical input-output relationship. Based on this, the achievable spectral efficiency (SE) is derived for maximum ratio transmission (MRT). By further investigating the special cases of pure line-of-sight (LoS) and Rayleigh fading, our analysis reveals that for a moderate number of antenna elements, the system's SE with mutual coupling might outperform that without mutual coupling, especially in the low transmit power regime. Moreover, the additional distance degrees-of-freedom (DoF) introduced by the near-filed channel can enable the inter-user interference mitigation, even for the worst case when the users have similar angular directions. Finally, the obtained theoretical analysis is validated through simulations.

The core idea of holographic MIMO (HMIMO) is to densely deploy numerous antenna elements within a given aperture size. However, with the denser distribution of antenna elements, stronger mutual coupling effects would kick in among antenna elements, which would eventually affect the communication performance. Meanwhile, as the holographic array usually has large physical size, the possibility of near-field communication increases. This paper investigates a near-field multi-user downlink HMIMO system and characterizes the spectral efficiency (SE) under the mutual coupling effect over Ricean fading channels. Both perfect and imperfect channel state information (CSI) scenarios are considered. (i) For the perfect CSI case, the mutual coupling and radiation efficiency model are first established. Then, a closed-form SE expression is derived under maximum ratio transmission (MRT). By comparing the SE between the cases with and without mutual coupling, it is unveiled that the system SE with mutual coupling might outperform that without mutual coupling in the low transmit power regime for a given aperture size. Moreover, it is also unveiled that the inter-user interference cannot be eliminated unless the physical size of the array increases to infinity. Fortunately, the additional distance term in the near-field channel can be exploited for the inter-user interference mitigation, especially for the worst case, where the users’ angular positions overlap to a great extent. (ii) For the imperfect CSI case, the channel estimation error is considered for the derivation of the closed-form SE under MRT. It shows that in the low transmit power regime, the system SE can be enhanced by increasing the pilot power and the antenna element density, the latter of which will lead to severe mutual coupling. In the high transmit power regime, increasing the pilot power has a limited effect on improving the system SE. However, increasing the antenna element density remains highly beneficial for enhancing the system SE. Finally, both analytical and simulation results confirm that reducing the antenna spacing will be accompanied by significant mutual coupling effects, which may potentially enhance the system SE. However, this enhancement is ultimately limited by the radiation efficiency of the antennas and the physical size of the array.

This paper investigates multi-user uplink transmission facilitated by holographic planar arrays (HPAs). It includes channel modeling and holographic precoding aimed at maximizing system spectral efficiency (SE) in scenarios where both users and base station are equipped with HPAs. First, we develop a holographic multiple-input multiple-output (MIMO) channel model utilizing electromagnetic field equations. Subsequently, we utilize Fourier space basis functions to discretize the continuous holographic MIMO model. Based on the discretized model, we formulate the problem of maximizing the system SE and propose a corresponding iterative water-filling algorithm to tackle it. Finally, we validate the effectiveness of the proposed scheme in enhancing the system SE and investigate the influence of physical size constraints of the transmitting and receiving arrays through simulation results.

With antenna spacing much less than half a wavelength in confined space, holographic multiple-input multiple-output (HMIMO) technology presents a promising frontier in next-generation mobile communication. We delve into the research of the multi-user uplink transmission with both the base station and the users equipped with holographic planar arrays. To begin, we construct an HMIMO channel model utilizing electromagnetic field equations, accompanied by a colored noise model that accounts for both electromagnetic interference and hardware noise. Since this model is continuous, we approximate it within a finite-dimensional space spanned by Fourier space series, which can be defined as the communication mode functions. We show that this channel model samples Green’s function in the wavenumber domain in different communication modes. Subsequently, we tackle the challenging task of maximizing the spectral efficiency (SE) of the system, which involves optimizing the continuous current density function (CDF) for each user. Using the aforementioned approximation model, we transform the optimization variables into expansion coefficients of the CDFs on a finite-dimensional space, for which we propose an iterative water-filling algorithm. Simulation results illustrate the efficacy of the proposed algorithm in enhancing the system SE and show the influence of the colored noise and the system parameters on the SE.