We consider a heterogeneous ultra dense network (HUDN) with both the hexagon and Poisson point process (PPP) layouts, which is more relevant for practical scenarios. A user-centric and adaptive interference-aware non-coherent coordinated multi-point transmission (IA-CoMP) scheme is used as a system setup to reduce both the cross-tier and the co-tier inter-cell interference (ICI) for the HUDN with range expansion (RE) in small cells. Due to the involvement of hexagonal macrocells, it is intractable to analyze the coverage performance of HUDNs with IA-CoMP. To this end, we present a mobile station GrouPing (MSGP)-based coverage analysis method, which partitions all MSs into four groups according to their main interference, and the whole coverage is obtained as the sum of the coverage of each MS group. We demonstrate that the proposed MSGP-based coverage analysis method can provide a tight upper bound when compared with Monte Carlo simulations. As the small cell density increases, the system coverage of HUDNs with hexagonal macrocells reduces exponentially, while the system coverage of HUDNs with PPP-based macrocells remains unchanged. Moreover, the system coverage increases with the larger one of the main ICI judging coefficient and the RE bias.

With the increasing number of devices, the demand for data computation is growing rapidly. In edge-cloud collaborative computing, tasks can be scheduled to servers as interdependent subtasks, enhancing performance through parallel computing. A task is executed in an executor, which must first initialize the runtime environment in a process called task startup. However, most existing research neglects the reuse of executors, leading to considerable delays during task startup. To address this issue, we model the edge-cloud collaborative task scheduling scenario considering executor reuse, task startup, and dependency relationships. We then formulate the dependent task scheduling problem with task startup. To meet real-time demands in edge-cloud collaborative computing, we propose ReflexPilot, an online task scheduling architecture featuring executor management. Building on this architecture, we introduce OTSA-PPO, a task scheduling algorithm based on Proximal Policy Optimization (PPO), and EMA, an advanced executor allocation algorithm. Under constraints of computational and communication resources, ReflexPilot leverages OTSA-PPO for online scheduling of dependent tasks based on current states, while EMA pre-creates and reuses executors to reduce the average task completion time. Extensive simulations demonstrate that ReflexPilot significantly reduces the average task completion time by 31% to 71% compared with existing baselines.

In the fifth generation (5G) networks, isolated logical slices are formed by the same infrastructure and spectrum resource. In the coverage regions of the sharing access points (APs), device to device (D2D) communication can occur among different slices, i.e., one mobile terminal (MT) acts as a D2D relay for another MT serving by a different slice. Since the slices and the MTs are selfish who will not help others voluntarily, this paper proposes a two-layered incentive scheme to stimulate cooperation. To achieve this, two resource allocating problems of the proposed incentive scheme are formulated which introducing the slices' and the MTs' cooperative activities, thus more resources will be allocated to the cooperative slices and MTs as reward. Since the slices' and the MTs' instantaneous resource allocations can not be obtained by the two optimal problems, the incentive scheduling algorithms of the slices and the MTs are designed. Finally, we define the isolation indexes to evaluate the slice isolation when carrying out cooperation. By simulating, it is proved that the proposed incentive scheme can stimulate cooperation efficiently, since the throughputs of the cooperative slices and MTs are both improved. And the proposed incentive scheme is helpful for the slices and the MTs to meet the statistical service quality requirements and brings the bad effect to the instantaneous service quality requirements.

Although resource sharing and mixed numerology among slices are promising for improving wireless resource utilization, these techniques can compromise isolation performance and cause serious inter numerology interference (INI). Therefore, this paper studies wireless resource management in a mixed numerology-based sliced 6G space–terrestrial integrated radio access network (STI-RAN) with the aim of reducing INI and guaranteeing isolation performance while decreasing interference from Doppler frequency shifts caused by the high-speed movement of low-orbit satellites. First, an isolation performance indicator is defined to evaluate different isolation performances, and a universal spectral distance model is formulated to rewrite the INI power model. Next, the dynamic wireless resource management problem is formulated in a discrete form, yielding a scheme called Flex- $\mu$ , which is designed to reduce the INI and Doppler frequency shifts, guarantee isolation performance, and enhance the SINR. Finally, an intelligent multi-characteristic matrix coding-based social group optimization (MultiMatrix-SGO) algorithm is designed to solve the proposed NP-hard discrete optimization problem. Compared with existing schemes, the system utility is efficiently increased by up to 58.32%, the SINR can converge to 38.44dB, and the isolation performance is guaranteed while the INI and Doppler frequency shifts are reduced