The upcoming fifth 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 sixth 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 and cache contents), air interface (e.g., radio spectrum and propagation channel), and the user-side (e.g., battery-life and locations). The multi-state, multi-dimensional nature of the network state, requiring the 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.

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Abstract-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 smallscale 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-ofsight 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.

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 multipleoutput (MIMO) systems.

Statistical analysis of the UWB channel in an industrial environmentKåredal, Johan; Wyne, Shurjeel; Almers, Peter; Tufvesson, Fredrik; Molisch, Andreas General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Abstract-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 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 energy.