A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).

This paper investigates the joint problem of access point (AP) assignment and power allocation (PA) in a three-tier hybrid radio frequency/visible light communication (VLC) heterogeneous network (HetNet). The main goal is to maximize the HetNet’s sum-rate under practical constraints such as APs’ power budgets and users’ quality-of-service (QoS) requirements, while maintaining an acceptable level of illumination in the VLC system. When this design problem is formulated mathematically, it turns out to be a combinatorial decision problem that involves non-linear constraints, and hence is NP hard. To efficiently obtain good quality solutions for the formulated problem, a reformulation into the college admission model is first performed. Then, a distributed and low-complexity algorithm based on matching theory and an efficient heuristic PA scheme are proposed to obtain a good quality suboptimal solution for the joint problem. Simulation results highlight the robustness of the proposed solution and its significant gain in network sum-rate as compared to different benchmark schemes. The effect of various system parameters such as the minimum QoS and maximum illumination requirements on the performance of the proposed solution is studied. Finally, the theoretical analysis of convergence, stability, and complexity of the proposed technique is performed.

Integrating visible light communication (VLC) system with indoor radio frequency (RF) network is seen as a possible way of increasing the capacity and coverage of indoor networks. In such a hybrid network, the traffic generated at the indoor RF and VLC access points must be backhauled to the core network. Power line communication (PLC) technology is seen as a cost-effective backhaul (BH) solution due to its infrastructure availability in every home. In this letter, a novel system model that captures the joint effect of power and BH flow optimization for hybrid VLC/RF/PLC indoor communication network is proposed. For the proposed system model, the problem of energy efficiency (EE) maximization via power and BH flow optimization is formulated as a non-convex problem, and then transformed into a convex problem via the Dinkelbach’s approach. An energy efficient algorithm is proposed to solve this joint problem with guaranteed optimality. Simulation results are used to verify the superiority of the proposed hybrid VLC/RF/PLC system and algorithm over a conventional indoor RF system and equal power allocation benchmark scheme, respectively, in terms of network throughput, power consumption, and EE.

Faster-than-Nyquist (FTN) signaling is a promising non-orthogonal pulse modulation technique that can improve the spectral efficiency (SE) of next generation communication systems at the expense of higher detection complexity to remove the introduced inter-symbol interference (ISI). In this paper, we investigate the detection problem of ultra high-order quadrature-amplitude modulation (QAM) FTN signaling where we exploit a mathematical programming technique based on the alternating directions multiplier method (ADMM). The proposed ADMM sequence estimation (ADMMSE) FTN signaling detector demonstrates an excellent trade-off between performance and computational effort enabling successful detection and SE gains for QAM modulation orders as high as 64K (65,536). The complexity of the proposed ADMMSE detector is polynomial in the length of the transmit symbols sequence and its sensitivity to the modulation order increases only logarithmically. Simulation results show that for 16-QAM, the proposed ADMMSE FTN signaling detector achieves comparable SE gains to the generalized approach semidefinite relaxation-based sequence estimation (GASDRSE) FTN signaling detector, but at an experimentally evaluated much lower computational time. Simulation results additionally show SE gains for modulation orders starting from 4-QAM, or quadrature phase shift keying (QPSK), up to and including 64K-QAM when compared to conventional Nyquist signaling. The very low computational effort required makes the proposed ADMMSE detector a practically promising FTN signaling detector for both low order and ultra high-order QAM FTN signaling systems.

In this letter, a collision-free sequential task offloading scheme to multiple mobile-edge computing servers is proposed. The problem is formulated as a multi-objective optimization of latency and offloading failure probability. An exact solution technique is developed to obtain a benchmark optimal solution for the problem. A more computationally efficient heuristic algorithm is additionally developed, whose sub-optimal solution yields a performance close to optimal. Simulation results illustrate that the proposed offloading scheme can effectively reduce both latency and offloading failure probability.

This paper investigates the physical layer security and data transmission in cellular networks with inband underlay Device-to-Device (D2D) communications, where there is no direct link between D2D users. We propose to apply full-duplex (FD) transmission and dual antenna selection at the D2D relay node. The relay node can simultaneously act as a friendly jammer to improve the secrecy performance of the cellular network while enhancing the D2D communication data transmission. This is an appealing and practical scheme where spectrum sharing is beneficial for the D2D and cellular networks in terms of throughput enhancement and security provisioning, respectively. The practical scenario, where the eavesdropper is passive, is considered. The eavesdropper uses either selection combining or maximal ratio combining to combine the wiretapped signals of the cellular network. The secrecy performance of the cellular network is analyzed, and closed-form expressions for the secrecy outage probability and the probability of non-zero secrecy capacity are derived. We show that increasing the number of FD jamming antennas enhances the secrecy performance of the cellular network. A closed-form expression of the D2D outage probability is also provided. Simulation and numerical results are provided to verify the efficiency of the proposed scheme and to validate the accuracy of the derived expressions.