This paper addresses hierarchical service placement, UAV trajectory design, access control, and resource scheduling issues in multi-access edge computing (MEC)-enabled time division multiple access (TDMA)-based air-ground integrated networks (AGINs) comprising multiple unmanned aerial vehicles (UAVs) and a ground base station. UAVs perform environmental sensing and data collection, but their limited onboard computing and energy resources pose challenges for handling heterogeneous, delay-sensitive tasks. To tackle this, we propose a two-tier actor-based deep reinforcement learning (DRL) algorithm for multi-timescale decision making. A high-level deep Q-Network (DQN) agent determines frame-level service placement, while a low-level improved deep deterministic policy gradient (IDDPG) agent manages time-slot-level UAV trajectory, access control, bandwidth allocation, and transmission power. A constraint-aware reward mechanism ensures learning stability and feasibility. Simulations show that the proposed method outperforms baseline schemes in task success rate, energy efficiency, and scheduling fairness.

To address the challenges of spectral leakage and self-interference in filter bank multicarrier with quadrature amplitude modulation (FBMC/QAM) system under spectrally-constrained low-altitude economy (LAE) communication scenarios, a prototype filter design scheme is proposed. This scheme relaxes the orthogonality conditions between the two prototype filters to formulate a constrained optimization problem, which aims to minimize self-interference power subject to time and frequency localization constraints. A prototype filter with complex frequency-domain coefficients is derived for odd-numbered subcarrier symbols by solving the problem. Simulation results show that the FBMC/QAM system with the proposed filter achieves low out-of-band (OOB) radiation, and at the same time maintains good bit error rate (BER) performance, providing a practical solution for efficient deployment in LAE networks.

A new search method named two-dimensional greedy search (TDGS) is proposed to progressively determine each element within an exponent matrix, so as to generate quasi-cyclic (QC) low-density parity-check (LDPC) codes without 4-cycles and 6-cycles. By applying four different two-dimensional scanning orders to the TDGS, a design framework is formulated to unify several existing and novel explicit constructions for short (3,$L$)-regular QC-LDPC codes without 4-cycles and 6-cycles. Through equivalence analysis between the exponent matrices greedily found by the TDGS and directly defined by explicit constructions, novel girth properties of (and connections between) these existing explicit constructions are also revealed.

Unmanned aerial vehicle (UAV) communication system assisted by intelligent reflecting surface (IRS) has promising applications in future wireless communication. Considering the realistic high-efficient IRS-UAVs transmission system in the three-dimensional (3D) space, we propose a joint beamforming and UAVs’ trajectory optimization algorithm to maximize the secrecy energy efficiency (SEE) of the system, which is constrained by the mobility of UAVs and the number of access users. In the proposed algorithm, the beamforming vector, multi-IRS diagonal phase shift matrix, and UAVs’ trajectory are optimized alternately using block coordinate descent (BCD). We not only derive the optimal closed-form expression of the multi-IRS diagonal phase shift matrix, but also solve the 3D trajectory optimization of UAVs under the given beamforming matrix. Simulation results show the effectiveness of the proposed algorithm and the performance improvement for IRS-UAVs communication.

Due to the existence of imaginary interference in filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) systems, channel estimation technology is a difficult task. In this paper, an innovative preamble structure is suggested to increase the channel estimation accuracy. The suggested preamble structure employs five FBMC/OQAM symbols and every three adjacent subcarriers constitute a preamble sub-block (PSB). According to interference factors, the special pilots are designed for PSB, which can increase the central point’s pseudo-pilot power and therefore improve channel estimation performance. Experimental results testify that the suggested approach works better than its conventional counterparts.

Filter bank multicarrier with offset quadrature amplitude modulation (FBMC/OQAM) has been studied as an alternative waveform for post-orthogonal frequency division multiplexing (OFDM) wireless communications. However, due to the intrinsic imaginary inter-carrier/inter-symbol interference of FBMC/OQAM signals, accurate channel estimation and equalization remain open issues for FBMC/OQAM systems in dispersive channels. In this article, two new signal models of the analysis filter bank (AFB) output are first derived in the absence of any channel assumption and in the presence of a relaxed channel assumption, respectively. Based on the new-built models, initial channel estimation with least squares (LS) (IniCE-LS) is presented and its output is used as the initial condition of recursive weighted LS (RWLS) estimation; moreover, non-iterative and iterative channel equalization combined with RWLS channel estimation (i.e., N-ICE-RWLS and ICE-RWLS) are proposed by using the real-time reconstructed FBMC/OQAM data symbols as pilots. The proposed N-ICE-RWLS and ICE-RWLS schemes not only allow to improve channel estimation and equalization performance, but also achieve high transmission efficiency. Considering the requirements of practical application, we further develop the low-complexity implementation methods of N-ICE-RWLS and ICE-RWLS. All these schemes are validated by analyzing the channel estimation accuracy and bit error rate (BER) over various frequency selective channels.

In this study, the authors present a cooperative spectrum sensing scheme based on opportunistic amplify‐and‐forward relaying (denoted by CSS‐OAFR), which provides higher detection performance by selecting the best cognitive relay and is interesting in distributed cognitive radio networks. Moreover, the authors focus on the detection performance using the energy detector over independent and non‐identically distributed Nakagami‐ m fading channels. In particular, a tight closed‐form lower bound of the average missed‐detection probability is derived for the convenience of performance evaluation in practice. Finally, simulations are provided to validate the CSS‐OAFR scheme and the derived closed‐form lower bound.