Recently, unmanned aerial vehicles (UAVs) are crucial in the low-altitude economy due to their high mobility and operational efficiency, which enable rapid and flexible operations in various applications. To support the flight control and management of low-altitude UAVs, ground base stations need to ensure communication quality that is high-capacity, ultra-low latency, and highly reliable. Extremely large-scale multiple-input multiple-output (XL-MIMO) systems, capable of forming high-gain directional beams, are highly suited for supporting the communication requirements of UAVs in the low-altitude economy. However, the communication signal may quickly deviate from the main lobe of the beam due to the mobility of UAVs, resulting in beam misalignment and significant degradation in communication quality. To address this problem, this paper first analyzes the near-field beam pattern of XL-MIMO system serving low-altitude UAVs and then decomposes phase of beam pattern into linear and nonlinear components to derive the angular and distance half-power beamwidth in the near field. Then, the prediction error is used to determine the number of activated antennas for dynamic beamwidth adjustment based on UAV position prediction. In addition, a near-field adaptive beamwidth control-aided tracking (NF-ABCT) algorithm is proposed to improve the effectiveness of beam tracking. Finally, simulation results demonstrate that the proposed NF-ABCT achieves a higher signal-to-noise ratio compared to the existing fixed beam scheme and channel estimation methods, while maintaining beam traking robustness and stability in both near-field and far-field.

To address the stringent demands of next-generation networks for massive connectivity, ultralow latency, and ultrahigh spectral efficiency, the win–win integration of reconfigurable intelligent surface (RIS) and nonorthogonal multiple access (NOMA) is considered as a promising solution. In this article, we investigate a downlink RIS-empowered NOMA system with short packet communications (SPCs) in the presence of hardware impairments at the transceiver nodes. To characterize the performance of the proposed network, the approximate and asymptotic closed-form expressions of average block error rate (BLER) at far and near users are derived and analyzed. Based on asymptotic average BLER in high signal-to-noise ratio regime, the diversity order, minimum blocklength, and optimal power allocation are examined. RIS exhibits an improvement in diversity order and minimum blocklength. The achieved results show that users with poorer channel conditions have less sensitivity to hardware impairments whether for near users or RIS-assisted far users. Furthermore, our results manifest the benefits of NOMA and RIS in SPC over the benchmark orthogonal multiple access (OMA) scheme.

LoRa has been recognized as one of the most promising low-power wide-area (LPWA) techniques. Since LoRa devices are usually powered by batteries, energy efficiency (EE) is an essential consideration. In this paper, we investigate the energy efficient resource allocation in LoRa networks to maximize the system EE (SEE) and the minimal EE (MEE) of LoRa users, respectively. Specifically, our objective is to maximize the corresponding EE by jointly exploiting user scheduling, spreading factor (SF) assignment, and transmit power allocations. To solve them efficiently, we first propose a suboptimal algorithm, including the low-complexity user scheduling scheme based on matching theory and the heuristic SF assignment approach for LoRa users scheduled on the same channel. Then, to deal with the power allocation, an optimal algorithm is proposed to maximize the SEE. To maximize the MEE of LoRa users assigned to the same channel, an iterative power allocation algorithm based on the generalized fractional programming and sequential convex programming is proposed. Numerical results show that the proposed user scheduling algorithm achieves near-optimal EE performance, and the proposed power allocation algorithms outperform the benchmarks.

We investigate the robust beamforming design for a simultaneous wireless information and power transfer (SWIPT) enabled system, with the cooperative non-orthogonal multiple access (NOMA) protocol applied. A novel cooperative NOMA scheme is proposed, where a strong user with better channel conditions adopts power splitting (PS) scheme and acts as an energy-harvesting relay to forward the decoded signal to the weak user. The presence of channel uncertainties is considered by introducing the outage-based constraints of signal to interference plus noise ratio (SINR). Specifically, it is assumed that only imperfect channel state information (CSI) is known at the base station (BS), due to the reason that the BS is far away from both users and suffers serious feedback delay. Our aim is to maximize the strong user's data rate, by optimally designing the robust transmit beamforming and PS ratio, while guaranteeing the correct decoding of the weak user. The proposed formulation yields to a challenging nonconvex optimization problem. To solve it, we first approximate the probabilistic constraints with the Bernstein-type inequalities, which can then be globally solved by two-dimensional exhaustive search. To further reduce the complexity, an efficient low-complexity algorithm is proposed with the aid of successive convex approximation (SCA). Numerical results show that the proposed algorithm converges quickly, and the proposed SWIPT-enabled robust cooperative NOMA system achieves better performance than existing protocols.

In this paper, we study the robust beamforming design for a simultaneous wireless information and power transfer (SWIPT) enabled system, with cooperative non-orthogonal multiple access (NOMA) protocol applied. A novel cooperative NOMA scheme is proposed, where the strong user with better channel conditions adopts power splitting (PS) scheme and acts as an energy-harvesting relay to transmit information to the weak user. The presence of channel uncertainties is considered and incorporated in our formulations to improve the design robustness and communication reliability. Specifically, only imperfect channel state information is assumed to be available at the base station (BS), due to the reason that the BS is far away from both users and suffers serious feedback delay. To comprehensively address the channel uncertainties, two major design criteria are adopted, which are the outage-based constraint design and the worst-case-based optimization. Then, our aim is to maximize the strong user's data rate, by optimally designing the robust transmit beamforming and PS ratio, while guaranteeing the correct decoding of the weak user. With two different channel uncertainty models respectively incorporated, the proposed formulations yield to challenging nonconvex optimization problems. For the outage-based constrained optimization, we first conservatively approximate the probabilistic constraints with the Bernstein-type inequalities, which are then globally solved by 2-D exhaustive search. To further reduce the complexity, an efficient low-complexity algorithm is then proposed with the aid of successive convex approximation (SCA). For the worst-case-based scenario, we first apply the semidefinite relaxation method to relax the quadratic terms and prove the rank-one optimality. Then the nonconvex max-min optimization problem is readily transformed into convex approximations based on S-procedure and SCA. Simulation results show that for both channel uncertainty models, the proposed algorithms can converge within a few iterations, and the proposed SWIPT-enabled robust cooperative NOMA system achieves better system performance than the existing protocols.

In this paper, we investigate energy efficiency for uplink LoRa, which is one of the most promising and widely deployed low-power wide-area (LPWA) networks. In the considered networks, we explore user scheduling, spreading factor (SF) assignment, and power allocation jointly. A nonconvex optimization problem for maximizing the system energy efficiency is formulated, with targeted SNR requirement and power range as constraints for each LoRa user. To solve this problem, we first propose a low-complexity suboptimal algorithm, which includes energy-efficient user scheduling and heuristic SF assignment for scheduled users based on matching theory. Then a novel power allocation based on Charnes-Cooper transformation is proposed to transform the fractional objective into the convex form to maximize the system energy efficiency. Simulation results show that the proposed algorithms achieve near-optimal performance in terms of energy efficiency.

Physical-layer security has drawn ever-increasing attention in the next generation wireless communications. In this paper, we focus on studying the secure communication in an HPN-to-devices (HTD) network, in which a new type of MAC spoofing attack is considered. To detect the malicious attack, we propose a novel algorithm, namely, eigenvalue test using random matrix theory (ETRMT) algorithm, which needs no prior information about the channel. In particular, when the number of samples is finite at the receiver or the number of devices is large, the sampled signal is the biased estimation of the actual signal, which inspires us to use the random matrix theory to analyze the spoofing attack detection. The closed-form expressions of the detection probability, the false alarm probability, and the Neyman-Pearson threshold are derived based on eigenvalue distribution of the spiked population model. In addition, taking the channel time-varying into consideration, we provide an adaptive threshold tracking method by using Bayesian forecasting. Finally, the simulations are conducted to validate our proposed method and some insightful conclusions are obtained.

This paper studies the secure transmission for downlink multiple-input single-output (MISO) non-orthogonal multiple access (NOMA) system in which imperfect channel state information (CSI) of the eavesdropper links is considered. We propose the novel robust beamforming strategies for the direct transmission NOMA (DT NOMA) and cooperative jamming NOMA (CJ NOMA) with a helper. We formulate our problem as the worst-case sum power minimization subject to secrecy rate constraint. The semidefinite relaxation (SDR) method is firstly applied to relax the quadratic terms and rank-one optimality is proved. Then an iterative algorithm based on successive convex approximation (SCA) is proposed to transform the nonconvex problem into convex approximations. Simulation results show that both the proposed NOMA schemes outperform the orthogonal multiple scheme, and CJ NOMA scheme can achieve much better system performance gain than DT NOMA scheme.