The upcoming 5th Generation (5G) of wireless networks is expected to lay a foundation of intelligent networks with the provision of some isolated Artificial Intelligence (AI) operations. However, fully-intelligent network orchestration and management for providing innovative services will only be realized in Beyond 5G (B5G) networks. To this end, we envisage that the 6th Generation (6G) of wireless networks will be driven by on-demand self-reconfiguration to ensure a many-fold increase in the network performance and service types. The increasingly stringent performance requirements of emerging networks may finally trigger the deployment of some interesting new technologies such as large intelligent surfaces, electromagnetic-orbital angular momentum, visible light communications and cell-free communications – to name a few. Our vision for 6G is – a massively connected complex network capable of rapidly responding to the users’ service calls through real-time learning of the network state as described by the network-edge (e.g., base-station locations, cache contents, etc.), air interface (e.g., radio spectrum, propagation channel, etc.), and the user-side (e.g., battery-life, locations, etc.). The multi-state, multi-dimensional nature of the network state, requiring real-time knowledge, can be viewed as a quantum uncertainty problem. In this regard, the emerging paradigms of Machine Learning (ML), Quantum Computing (QC), and Quantum ML (QML) and their synergies with communication networks can be considered as core 6G enablers. Considering these potentials, starting with the 5G target services and enabling technologies, we provide a comprehensive review of the related state-of-the-art in the domains of ML (including deep learning), QC and QML, and identify their potential benefits, issues and use cases for their applications in the B5G networks. Subsequently, we propose a novel QC-assisted and QML-based framework for 6G communication networks while articulating its challenges and potential enabling technologies at the network-infrastructure, network-edge, air interface and user-end. Finally, some promising future research directions for the quantum-and QML-assisted B5G networks are identified and discussed.

Efficient and realistic mm-wave channel models are of vital importance for the development of novel mm-wave wireless technologies. Though many of the current 60 GHz channel models are based on the useful concept of multipath clusters, only a limited number of 60 GHz channel measurements have been reported in the literature for this purpose. Therefore, there is still a need for further measurement based analyses of multipath clustering in the 60 GHz band. This paper presents clustering results for a double-directional 60 GHz MIMO channel model. Based on these results, we derive a model which is validated with measured data. Statistical cluster parameters are evaluated and compared with existing channel models. It is shown that the cluster angular characteristics are closely related to the room geometry and environment, making it infeasible to model the delay and angular domains independently. We also show that when using ray tracing to model the channel, it is insufficient to only consider walls, ceiling, floor and tables; finer structures such as ceiling lamps, chairs and bookshelves need to be taken into account as well.

Physical layer security (PLS) has been extensively explored as an alternative to conventional cryptographic schemes for securing wireless links. Of late, the research community is actively working towards exploiting cooperative communication techniques to further improve the security. Many studies are showing that the cooperation between the legitimate nodes of a network can significantly enhance their secret communications, relative to the non-cooperative case. Motivated by the importance of this class of PLS systems, this paper provides a comprehensive survey of the recent works on cooperative relaying and jamming techniques for securing wireless transmissions against eavesdropping nodes which attempt to intercept the transmissions. First, it provides a in-depth overview of various secure relaying strategies and schemes. Next, a review of recently proposed solutions for cooperative jamming techniques has been provided with an emphasis on power allocation and beamforming techniques. Then, the latest developments in hybrid techniques, that use both cooperative relaying and jamming, are elaborated. Finally, several key challenges in the domain of cooperative security are presented along with an extensive discussion on the applications of cooperative security in key enablers for 5G communications, such as non-orthogonal multiple access (NOMA), device-to-device (D2D) communications, and massive multiple-input multiple-output (MIMO) systems.

The results of three ultra-wideband (UWB) measurement campaigns conducted in two different industrial environments are presented. A frequency range of 3.1-10.6 or 3.1-5.5 GHz was measured using a vector network analyzer and a virtual array technique enabling the investigation of small-scale statistics. The results show that the energy arrives in clusters, and that the abundance of metallic scatterers present in the factory hall causes dense multipath scattering. The latter produces a small-scale fading that is mostly Rayleigh distributed; the only exception being the delay bin containing the line-of- sight component. The power delay profile can be modeled by a generalized Saleh-Valenzuela model, where different clusters have different ray power decay constants. It is also noted that the number of multipath components required to capture a majority of the energy is quite large. More than a hundred components can be needed to capture 50% of the total available energy.

In this paper, we present a statistical model for the ultra-wideband (UWB) channel in an industrial environment. Based on a set of measurements in a factory hall, we find that the abundance of metallic scatterers causes dense multipath scattering. This can be seen to produce mostly a Rayleigh distributed small-scale fading signal, with only a few paths exhibiting Nakagami distributions. For the power delay profile, we suggest a generalization of the Saleh-Valenzuela model where clusters with different excess delays have different ray power decay constants; the decay constants follow a linear dependence on the delay. This model provides an excellent fit to the measured data. We also note that for non-line-of-sight scenarios at larger distances, several hundred multipath components need to be collected to capture 50% of the available energ