In this paper, we jointly study the real-time user association, traffic routing and x-Network Function (xNF) placement problem in an integrated Terrestrial and Satellite 6G Network (TN-SN), with the aim of maximizing the network energy efficiency and user acceptance ratio. We formulate the aforementioned problem as a Mixed Integer Linear Program (MILP), considering various capacity, power and flow conservation constraints for the integrated network, while also meeting the specific service requirements of each user. To tackle the increased complexity of the optimal solution, we also develop an efficient heuristic (named as TERA). Through extensive simulations, TERA demonstrates a notable superiority in energy efficiency compared to the current State-of-the-Art (SoA), achieving up to 85 % of the optimal with up to 87 % lower execution time even under challenging traffic load conditions.

Due to the fact that large swathes on Earth still lack broadband communication coverage, especially in remote/rural areas and developing countries, there have been several attempts, starting from 3GPP Release 17, to lay out the architectural amendments needed for the integration of terrestrial networks with their non-terrestrial counterparts. Such attempts have led to recent projects regarding such integration that consider either 5G/5G-Advanced networks or more revolutionary approaches for the forthcoming 6G networks. In this manuscript, we give an overview of the architectural framework, technical innovations, and considered use cases of the Horizon Europe ETHER project.

We present an optimized Medium-Transparent MAC (oMT-MAC) protocol for Analog-RoF Fiber-Wireless 5G and beyond X-haul networks, capable of generating an optimum transmission schedule, which boosts the protocol's efficiency by utilizing the full delay budget of higher priority flows. Results show that oMT-MAC's optimization model can reduce delays by up to 20% for low-priority flows while maintaining the 5G Fronthaul and URLLC KPIs.

We propose an enhanced Medium-Transparent MAC (eMT-MAC) protocol for Analog-RoF Fiber-Wireless 5G and beyond X-haul networks, capable of handling variable packet sizes and wavelength sharing among multiple Remote Antenna Units (RAUs), thus increasing the protocol's efficiency for low-payload-length services such as URLLC/mMTC, while adding support for Point-to-Point links. Results show that eMT-MAC achieves high protocol efficiency, while also supporting wavelength sharing, and meets Low-layer split fronthaul specifications even for wavelength switching delays up to$12\mu\mathrm{s}$.

In this work, we propose a time- and a unit cell-splitting protocol for supplying the energy needs of reconfigurable intelligent surfaces (RISs) through wireless energy harvesting (EH) from information signals. We first compute the RIS energy consumption per frame that is common for both protocols and incorporates the energy burden for channel estimation. Based on it, we subsequently formulate an optimization problem that maximizes the average rate under the constraint of meeting the RIS long-term energy consumption demands. In addition, closed-form solutions regarding the optimal allocation of resources are provided for both protocols in the case of deterministic channel gains for the transmitter-RIS links and a methodology to obtain such a solution in the general case of random channels. Finally, for the optimal resource allocation for both protocols numerical results based on Monte-Carlo simulations reveal that the unit cell-splitting protocol exhibits a superior performance compared to its time-splitting counterpart.

Next-generation cellular networks, i.e., beyond fifth generation (B5G) and sixth generation (6G) networks, aim at significantly increasing capacity by deploying a massive number of small cells (SCs) and leveraging millimeter wave (mmWave) links that have large bandwidth availability. However, as optical connections to a large number of base stations (BSs) are not cost effective, wireless backhaul (BH) links may be used to connect SCs to the core network using mmWave frequencies and forming multihop mesh BH paths. While very flexible in deployment, the uncertainty in user demand, which varies over time and place, makes network planning and management challenging. In this work, we propose novel algorithms to solve the joint problem of energy-efficient user association, BH traffic routing and BS/BH link on/off switching. We first formulate an exact model assuming user traffic demand uncertainty leveraging Γ-robustness theory. As the model is intractable for large-scale instances, we develop a novel greedy robust heuristic (P-HEUR), which includes a robustifying step to effectively cope with demand uncertainty. Our evaluation demonstrates that P-HEUR provides robust and energy-efficient solutions quickly for different scenarios and traffic demand uncertainty levels, and it significantly outperforms state-of-the-art approaches while achieving up to 83% of the optimal capacity, even in the most demanding scenarios in terms of traffic load and demand uncertainty, with up to 200k times lower complexity.

We study the problem of downlink Coordinated Beamforming for dense fixed-wireless millimeter wave (mmWave) networks under a Centralized/Cloud Radio Access Network (C-RAN) setting. To compensate for the increased mmWave path loss, we consider directional transmissions via antenna array analog beamforming, which leads to adiscreteset of available beams. We apply the Lyapunov optimization framework to propose a throughput-optimal policy which explicitly accounts for stochastic traffic and channel fluctuations and dynamically performs joint Base Station-to-user association and analog beam selection. Our model makes minimal assumptions and considers realistic mmWave antenna radiation patterns, while it can be easily extended to include additional MAC and PHY layer controls. Since this flexibility comes at the cost of high computational complexity, we also propose two heuristic policies offering reduced complexity. Their performance is compared against a baseline Round-Robin (RR)-based policy, while a theoreticalworst-caseperformance bound is derived. Extensive simulations show the optimal Lyapunov policy achieving a stable throughput increase of more than 2Xper usercompared to the RR policy, while the proposed heuristics incur only a 20-30% performance penalty with respect to the optimal Lyapunov policy with 60X-900X computational time savings.

Network Function Virtualization (NFV) is expected to be a crucial enabler of Beyond 5G (B5G) networks, supporting new services with stringent requirements, while offering high flexibility and configurability. In this paper, we consider the joint problem of Virtual Network Function (VNF) placement alongside computational and communication resource allocation in a mobile network to minimize total power expenditure while satisfying the Service Function Chain (SFC), throughput and delay requirements. We explicitly account for the Access Network (AN) and formulate a general Mixed Integer Linear Program (MILP). Due to the high complexity of the latter, we propose an efficient heuristic, which is shown to significantly outperform the State-of-Art (SoA), while achieving up to 78% of the optimal energy efficiency with up to 742 times lower complexity.

In order to meet the ever-increasing traffic demands, the combination of fiber and Millimeter Wave (mmWave) is expected to play a key role for 5G Centralized-Radio Access Networks (C-RANs). Due to the inefficiency of the Common Public Radio Interface for the Baseband Unit (BBU)-Remote Radio Head (RRH) communication, analog-Radio-over-Fiber (a-RoF) technology is considered a promising solution, mainly due to the RRH simplification and lower fronthaul requirements it imposes. In such mmWave a-RoF C-RANs, efficient Medium Transparent-Medium Access Control (MT-MAC) protocols are needed able to meet the challenging 5G requirements. To this end, in this paper, we propose a gated service MT-MAC protocol which authorizes each user to transmit the amount of data it requested. A detailed delay model is proposed, which is validated through simulations for different fiber lengths, network load conditions and number of available optical wavelengths. Moreover, the proposed protocol is compared with the state-of-the-art (SoA) and is shown to achieve up to 20 times higher throughput, 2 times lower delay with 100% lower blocking probability and 5 times higher data wavelength utilization, while being able to adapt to varying network traffic conditions. Our proposal also attains sub-ms latency in most cases, constituting it a promising candidate for 5G mmWave a-RoF C-RANs.

5G New Radio's (NR) spectrum expansion towards higher bands, although critical towards achieving the envisioned 5G capacity requirements, creates the need for installing a very large number of Access Points (APs), which asserts tremendous capital burden on the Mobile Network Operators. Current centralization solutions such as the Cloud Radio Access Network (C-RAN) alleviate partially the costs of densification by moving the majority of radio processing functionalities from the Remote Radio Heads (RRHs) to the central Base Band Unit (BBU), but still require very high-speed Point-to-Point links between the BBU and each RRH mainly due to the digitized Common Public Radio Interface (CPRI) that is excessively inefficient for hauling broadband signals. In this article, we present a novel architecture that employs an analog converged Fiber-Wireless scheme in order to create a very spectrally efficient Point-to-Multipoint network capable of interconnecting a large number of APs, while allowing compatibility with mature Ethernet-based low-cost equipment. Preliminary simulation results show very low end-to-end Ethernet packet delay, well below eCPRI's 100 μs mark, even for fiber lengths up to 10 km, indicating the suitability of our solution for employment in 5G NR large-scale fronthaul networks.

Fifth Generation (5G) Cloud-Radio Access Networks (C-RANs) are about to exploit both optical and Millimeter Wave (mmWave) technology to meet the ever-increasing traffic demands. In this new type of converged Fiber-Wireless (FiWi) systems efficient Medium Transparent-Medium Access Control (MT-MAC) protocols should be designed, able to satisfy the very strict 5G service requirements. To this end, in this paper, we propose an MT-MAC protocol for mmWave Analog Radio-over-Fiber (A-RoF) C-RANs, which employs gated service, according to which users are granted transmission windows equal to the number of bytes contained in their buffer. An analytical model is also proposed for the mean packet delay, which is verified by means of simulation for different fiber length values, network load conditions and optical capacity values. Our results not only prove the accuracy of the proposed model but also the suitability of the proposed MT-MAC protocol to meet the sub-ms delay challenge of latency-critical 5G network requirements.

With the advance of fifth generation (5G) networks, network density needs to grow significantly in order to meet the required capacity demands. A massive deployment of small cells may lead to a high cost for providing fiber connectivity to each node. Consequently, many small cells are expected to be connected through wireless links to the umbrella eNodeB, leading to a mesh backhaul topology. This backhaul solution will most probably be composed of high capacity point-to-point links, typically operating in the millimeter wave (mmWave) frequency band due to its massive bandwidth availability. In this paper, we propose a mathematical model that jointly solves the user association and backhaul routing problem in the aforementioned context, aiming at the energy efficiency maximization of the network. Our study considers the energy consumption of both the access and backhaul links, while taking into account the capacity constraints of all the nodes as well as the fulfillment of the service-level agreements (SLAs). Due to the high complexity of the optimal solution, we also propose an energy efficient heuristic algorithm (Joint), which solves the discussed joint problem, while inducing low complexity in the system. We numerically evaluate the algorithm performance by comparing it not only with the optimal solution but also with reference approaches under different traffic load scenarios and backhaul parameters. Our results demonstrate that Joint outperforms the state-of-the-art, while being able to find good solutions, close to optimal, in short time.

Fifth generation (5G) wireless networks will target at energy and spectrum efficient solutions to cope with the increasing demands in capacity and energy efficiency. To achieve this joint goal, dense networks of small cells (SCs) are expected to overlay the existing macro cells. In parallel, for the SC connection to the core network, a promising solution lies in a mesh network of high capacity millimeter wave backhaul (BH) links. In the considered 5G architecture, each SC is able to forward its BH traffic to the core network through alternative paths, thus offering high BH network reliability. In this context, the joint problem of user association and BH routing becomes challenging. In this paper, we focus on this problem targeting at energy and spectrum efficient solutions. A low-complexity algorithm is proposed, which bases its user association and BH routing decision i) on minimizing the spectrum resources to guarantee the user rate, so as to provide high spectrum efficiency, and ii) on minimizing both the access network and BH route power consumption to provide high energy efficiency. Our results show that our solution provides better trade-offs between energy and spectrum efficiency than the state-of-the-art in 3GPP scenarios.

Contemporary technologies as implemented in the field of healthcare have provided the everyday clinical practice with a plethora of tools to be used in various settings. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most promising technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. WSN4QoL is a Marie Curie project involving academic and industrial partners from three EU countries, which aims to show how new WSNs-based technologies suit the specific requirements of pervasive healthcare applications. In particular, in this paper, the WSN4QoL's system architecture is presented as designed to exploit the Network Coding (NC) mechanisms to achieve energy efficiency in the wireless communications and distributed positioning solutions to locate patients in indoor home environments. The system has been validated through experimental activities using commercial off the shelf (COTS) WSN testbeds and medical devices prototypes offered by a commercial partner. Results demonstrate that NC helps in achieving substantial gains in terms of energy efficiency as compared to traditional relay mechanisms, while the proposed positioning solution is able to locate people in indoor environments at a sub-room accuracy level, without requiring any extra dedicated hardware.

Due to the dense small cell deployment to cope with the increased data traffic of fifth generation (5G) networks, the direct backhaul (BH) connection of all small cells to the core network becomes challenging. To that end, millimeter wave (mmWave) is a promising solution for cost-efficient high capacity small cell BH links. However, due to the severe signal attenuation at high frequencies, mmWave can provide good coverage only for short distances, thus favoring a multi-hop 5G BH architecture. In this context, user association that impacts both the network and user performance calls for BH-aware strategies. Hence, in this paper, we study the user association problem aiming at the joint energy and spectrum efficiency maximization of the network, without compromising the user quality of service. The problem is formulated as a generalized assignment problem, which considers the capacity and energy consumption both in the access network and BH links. Provided that the considered problem is shown to be NP-hard, we employ optimization techniques to obtain an upper bound on system performance. We also propose a low complexity algorithm, which is shown to outperform the state-of-the-art while achieving near-optimal performance.

Spectrum scarcity together with high capacity demands make the use of millimeter wave (mmWave) frequencies an interesting alternative for next generation, i.e., fifth generation (5G), networks. Although mmWave is expected to play a key role for both access network and backhaul (BH), its initial use in the BH network seems more straight-forward. This stems from the fact that, in the BH case, its deployment is less challenging due to the fixed locations of BH transceivers. Still, provided that mmWave spectrum consists of several subbands, each one with different characteristics and thus different deployment constraints (e.g., channel bandwidth, maximum transmission power), a comparison is required in order to gain a better insight into the potentials of each solution. To that end, in this paper, the main mmWave candidate frequency bands are compared in terms of range, throughput and energy consumption. In our results, the bandwidth availability, the maximum transmission power as well as the antenna gains of each BH technology are taken into account, as defined by the Federal Communications Commission. The results are also compared with current industry-oriented state-of-the-art transceiver characteristics in order to gain further insights into the maximum achievable gains of each subband.

In the next few years, small cells (SCs) are expected to be densely deployed to achieve sustainable capacity enhancement. Due to the high SC density, some SCs will not have a direct connection to the core network, and thus will forward their traffic to their neighboring SCs through a multi-hop backhaul (BH). In such multi-hop architectures, the user association problem becomes challenging with BH energy consumption playing a key role. In parallel, the ever-increasing need to minimize the user equipment (UE) transmission power along with the uplink (UL) and downlink (DL) traffic asymmetry, predicate the joint study of UL and DL. Thus, in this paper, we study the joint UL and DL cell selection problem aiming at maximizing the total network energy efficiency, without compromising the UE quality of service. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a heuristic context-aware algorithm that associates the UEs in an energy-efficient way, while considering both access and BH energy consumption in UL and DL. We evaluate the proposed algorithm performance and we show that it can achieve significantly higher energy efficiency than the reference approaches, while maintaining high spectral efficiency and low UE power consumption.

To meet the ever-increasing traffic demands, future cellular networks are about to include a plethora of small cells (SCs), with user equipments (UEs) being able of communicating via multiple bands. Given that SCs are expected to be eventually as close as 50 m apart, some of them will not have a direct connection to the core network, and thus will forward their traffic to the neighboring SCs until they reach it. In such architectures, the user association problem becomes challenging with backhaul (BH) energy consumption playing a key role. Thus, in this paper, we study the user association problem aiming at maximizing the network energy efficiency. The problem is formulated as an optimization problem, which is NP-hard. Therefore, we propose a cognitive heuristic algorithm that exploits context-aware information (i.e., UE measurements and requirements, the HetNet architecture knowledge and the available spectrum resources of each base station (BS)) to associate the UEs in an energy-efficient way, while considering both the access and the BH energy consumption. We evaluate the performance of the proposed algorithm under two study-case scenarios and we prove that it achieves significantly higher energy efficiency than the reference algorithms, while maintaining high spectral efficiency.

In this paper, we evaluate a novel contention-aware channel selection algorithm that focuses on energy efficiency improvement of a secondary network (SN) in a scenario where other non-cooperating SNs are also using the primary resources. We present a detailed energy efficiency analysis and we study how the time between two consecutive sensing periods affects the energy efficiency. Our analysis proves that a categorization of the idle channels based on their contention level and the selection of the less contended ones can result in up to 70% gain in energy efficiency. The model is further evaluated through simulations.