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Mobile edge computing (MEC) enables communication users with limited computation power to offload computation-intensive tasks to the edge server, thus dramatically enhancing the limited computing capabilities of the users. As the reality of scarce spectrum resources and the energy-constrained nature of communication users, this paper introduces non-orthogonal multiple access (NOMA) and simultaneous wireless information and power transfer (SWIPT) techniques to achieve more efficient task offloading in MEC. To minimize the number of computationally failed tasks while simultaneously satisfying different quality of service (QoS) requirements of users, a joint resource management problem of the spectrum, computation, and energy resources is formulated. Due to the non-convexity of the offloading optimization problem and the stochastic nature of the constructed MEC environment, a multiple agents deep deterministic policy gradient (MADDPG)-based resource management algorithm is proposed to manage each user’s multidimensional resources without collaborating. The simulation results show that compared to other benchmark schemes, the proposed algorithm can effectively improve both the communication and computational performances in MEC.

In this correspondence, we investigate the average achievable secrecy rate (AASR) and average effective secrecy throughput (AEST) of the control link from the ground control station to the unmanned aerial vehicle (UAV), which requires ultra-reliable and low-latency communications. Both the UAV and eavesdropper are assumed to be randomly distributed within the restricted areas, and short packet transmission is adopted to guarantee the low latency. We consider both free space and 3-Dimensional channel models for the UAV, and the statistic distribution functions of both models are given. By using Gaussian-Chebyshev quadrature (GCQ), the approximation expressions of AASR are derived to give insight on the design of packet size. Moreover, analytical expressions of ASET are also developed to evaluate the effective secrecy performance. Numerical results corroborate the correctness of our derived results.

This correspondence investigates a joint power control, channel selection, and user dynamic access scheme to maximize the sum rate of non-orthogonal multiple access (NOMA) systems. The highly dynamic and uncertain environment hinders the collection of accurate instantaneous channel state information (CSI) at the base station for centralized resource management. Therefore, we propose a hybrid-decision-based multi-agent actor-critic (HD-MAAC) approach to optimize the sum rate of the system. The proposed scheme improves the standard actor-critic (AC) algorithm to obtain both discrete and continuous actions. Simulation results verify that the proposed scheme achieves higher sum rate than that of existing popular schemes under different settings.

Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has recently received significant research attention due to its outstanding ability of serving grant-free (GF) users with grant-based (GB) users’ spectrum, which greatly improves the spectrum efficiency and effectively relieves the massive access problem of 5G and beyond networks. In this paper, we first study the outage performance of the greedy best user scheduling SGF scheme (BU-SGF) by considering the impacts of Rayleigh fading, path loss, and random user locations. In order to tackle the admission fairness problem of the BU-SGF scheme, we propose a fair SGF scheme by applying cumulative distribution function (CDF)-based scheduling (CS-SGF), in which the GF user with the best channel relative to its own statistics will be admitted. Moreover, by employing the theories of order statistics and stochastic geometry, the outage performances of both BU-SGF and CS-SGF schemes are analyzed. Theoretical results show that both schemes can achieve full diversity orders only when the served users’ data rate is capped, which severely limits the rate performance of SGF schemes. To further address this issue, we propose a distributed power control strategy to relax such data rate constraint, and derive analytical expressions of the two schemes’ outage performances under this strategy. Finally, simulation results validate the fairness performance of the proposed CS-SGF scheme, the effectiveness of the power control strategy, and the accuracy of the theoretical analyses.