Movable antenna (MA) has attracted increasing attention in wireless communications recently. As compared to conventional fixed-position antennas (FPAs), the geometry of MAs can be dynamically reconfigured, such that more flexible beamforming can be achieved for different purposes. In this paper, we investigate the application of MAs to wide-beam coverage, aiming to jointly optimize the MAs’ beamforming weights and positions within a line segment to maximize the minimum beam gain among all possible directions in a target region. However, the resulting optimization problem is non-convex and difficult to be optimally solved. To tackle this difficulty, we first derive a closed-form optimal solution to this problem in the special case with two MAs. While for the case with more than two MAs, an alternating optimization (AO) algorithm is proposed to obtain a high-quality suboptimal solution, where the MAs’ beamforming weights and positions are alternately optimized by applying the successive convex approximation (SCA) technique. To reduce computational complexity, we further propose a more efficient MA position optimization method by leveraging the frequency modulation continuous wave (FMCW) design. Specifically, we construct a spatial FMCW-based continuous phase profile for the entire line segment and then select an optimal set of MA positions to optimize the wide-beam coverage performance with their FMCW-based phase profiles, thus greatly simplifying the wide-beam design. Furthermore, we extend the proposed AO and FMCW-based algorithms for the linear MA array to the planar MA array. Numerical results show that both our proposed algorithms can significantly outperform conventional FPAs even with optimized beamforming weights.

Active intelligent reflecting surface (AIRS) is expected to further improve wireless communication performance compared to traditional passive IRS (PIRS) due to its additional signal amplification capability. To leverage the benefits of AIRSs at the network level, we investigate a new AIRS-user association problem in a general wireless network consisting of multiple base stations (BSs), users and distributed IRSs. Specifically, each AIRS assists in the communication from its associated BS to user, while randomly scattering and amplifying interference and noise to all users. We first derive the average signal-to-interference-plus-noise ratio (ASINR) achievable at each user for any given AIRS-user associations. We then analytically compare the ASINRs of multi-AIRS and multi-PIRS networks in terms of different metrics, gaining key insights into the advantages of AIRSs over PIRSs at the network level. Furthermore, we jointly optimize AIRS-user associations to maximize the minimum ASINR among all users and propose an efficient successive refinement algorithm to obtain a high-quality suboptimal solution. Numerical results validate our performance analysis and demonstrate the superiority of our proposed algorithm over other baseline schemes.

Terahertz (THz) communication systems suffer severe blockage issues, which may significantly degrade the communication coverage and quality. Bending beams, capable of adjusting their propagation direction to bypass obstacles, have recently emerged as a promising solution to resolve this issue by engineering the propagation trajectory of the beam. However, traditional bending beam generation methods rely heavily on the specific geometric properties of the propagation trajectory and can only achieve sub-optimal performance. In this paper, we propose a new and general bending beamforming method by adopting the convex optimization techniques. In particular, we formulate the bending beamforming design as a max-min optimization problem, aiming to optimize the analog or digital transmit beamforming vector to maximize the minimum received signal power among all positions along the bending beam trajectory. However, the resulting problem is non-convex and difficult to be solved optimally. To tackle this difficulty, we apply the successive convex approximation (SCA) technique to obtain a high-quality suboptimal solution. Numerical results show that our proposed bending beamforming method outperforms the traditional method and shows robustness to the obstacle in the environment.

Fluid antennas (FAs) and movable antennas (MAs) have attracted increasing attention in wireless communications recently. As compared to the conventional fixed-position antennas (FPAs), their geometry can be dynamically reconfigured, such that more flexible beamforming can be achieved for signal coverage and/or interference nulling. In this paper, we investigate the use of MAs to achieve uniform coverage for multiple regions with arbitrary number and width in the spatial domain. In particular, we aim to jointly optimize the MAs’ weights and positions within a linear array to maximize the minimum beam gain over the desired spatial regions. However, the resulting problem is non-convex and difficult to be optimally solved. To tackle this difficulty, we propose an alternating optimization (AO) algorithm to obtain a high-quality suboptimal solution, where the MAs’ weights and positions are alternately optimized by applying successive convex approximation (SCA) technique. Numerical results show that our proposed MA-based beam coverage scheme can achieve much better performance than conventional FPAs.

Intelligent reflecting surface (IRS) is deemed as a promising technology to improve the spectral and energy efficiency of wireless communications cost-effectively. In this paper, we investi-gate a double-IRS aided wideband terahertz (THz) communication system and the beam-squint effects at the two IRSs over their double-reflection line-of-sight (LoS) link. To gain useful insights into such beam-squint effects, we first analyze the performance loss incurred by applying the conventional narrowband cooperative passive beamforming (CPB) at the two IRSs in the considered wideband system, which unveils that signal nulling may frequently occur over frequency in the case of large-size IRSs. To resolve this issue, we propose in this paper a new max-min CPB design, aiming to maximize the minimum end-to-end channel power gain over the frequency band. However, this problem is non-convex and difficult to be optimally solved. To tackle this difficulty, we propose to combine the alternating optimization (AO) and alternating direction method of multipliers (ADMM) algorithms to obtain a high-quality suboptimal solution. Numerical results show that the proposed max-min CPB design can achieve much better performance than the conventional narrowband CPB design.

Intelligent reflecting surface (IRS) can be densely deployed in complex environments to create cascaded line-of-sight (LoS) links between base stations (BSs) and users, which significantly enhance the signal coverage for both wireless information transfer and wireless power transfer (WPT). In this paper, we consider the WPT from a multi-antenna BS to multiple energy users (EUs) by exploiting the signal beam routing via multi-IRS reflections. First, we present a baseline beam routing scheme with each IRS serving at most one EU, where the BS transmits wireless power to all EUs simultaneously while the signals to different EUs undergo disjoint sets of multi-IRS reflection paths. Under this setup, we aim to tackle the joint beam routing and resource allocation optimization problem by jointly optimizing the reflection paths for all EUs, the active/passive beamforming at the BS/each involved IRS, as well as the BS’s power allocation for different EUs to maximize the minimum received signal power among all EUs. Next, to further improve the WPT performance, we propose two new beam routing schemes, namely dynamic beam routing and subsurface-based beam routing, where each IRS can serve multiple EUs via different time slots and different subsurfaces, respectively. In particular, we prove that dynamic beam routing outperforms subsurface-based beam routing in terms of minimum harvested power among all EUs. In addition, we show that the optimal performance of dynamic beam routing is achieved by assigning all EUs with orthogonal time slots for WPT. A clique-based optimization approach is also proposed to solve the joint beam routing and resource allocation problems for the baseline beam routing and proposed dynamic beam routing schemes. Numerical results are finally presented, which demonstrate the superior performance of the proposed dynamic beam routing scheme to the baseline scheme.