The aim of this paper is to illustrate the Control Plane functionalities, strategies, and procedures in the Next Generation Central Offices, which are crucial traffic aggregation points close to the subscribers. The Next Generation Central Offices are becoming integral part of the next generation networks and for this reason the management and control of its internal resources is essential. Initially, the paper explains the Next Generation Central Offices system architecture and its placement within an end-to-end network. Then, it details the use cases and their quantitative analysis, taking into consideration a dense urban area in Paris city, for estimating the downlink and uplink throughput and latency related requirements. Based on these estimations, the paper defines the Next Generation Central Office Control Plane requirements, along with its functional architecture and its internal functional blocks, detailing their specific roles and interactions to meet the bandwidth and latency demands. Finally, the paper describes an early software prototype implementation based on ETSI TeraFlow SDN, highlighting the software extensions implemented for the support of the Next Generation Central Office Control Plane functionalities, strategies, and procedures. The paper concludes with the next steps for the future work, consisting of the integration with an actual Next Generation Central Office and a field trial experiment in an end-to-end network.

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.

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$12\mu\mathrm{s}$.

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.

In this paper, we describe a network coding scheme for the Broadcast Erasure Channel with multiple unicast stochastic flows, for a single source transmitting packets to N users with per-slot ACK/NACK feedback. This scheme performs only binary (XOR) operations and involves a network of queues, along with special rules for coding and moving packets among the queues, that ensure instantaneous decodability. Additionally, for the scheme to work, one has to specify which packets to select for encoding at each time, based on the received feedback. Contrary to prior work where this packet selection was explicitly specified a priori, we employ a backpressure-type policy that makes the selection based only on queue backlogs. We next provide a stability region outer bound for arbitrary N and erasure patterns and show that this bound effectively coincides with a bound on the system's information-theoretic capacity region (accounting for idle slots). Finally, for N=4 and i.i.d. erasures, we provide a policy that achieves the stability outer bound and employs the proposed XOR scheme using a restricted set of coding rules.

We study the case of a three-user broadcast erasure channel with multiple unicast traffic sessions, where feedback from the users is fed back to the transmitter in the form of positive acknowledgment (ACK)/negative acknowledgment (NACK) messages. The capacity region of this system has been recently derived and two capacity-achieving coding algorithms employing intersession linear network coding have been proposed. Since these algorithms suffer from large computational complexity and decoding delay, our aim, in this paper, is to design a coding algorithm with reduced computational complexity and a low decoding delay that achieves a comparable rate region to the former algorithms. We exclusively consider algorithms that require no knowledge of channel statistics, only perform XOR operations among the packets, and allow for instantaneous decoding by any receiver that successfully receives a packet. We present such an algorithm, named IXOR, which operates on a specially constructed network of virtual queues and, through intelligent packet combining, achieves the capacity under a general condition, which is satisfied in the following settings: spatially independent identically distributed erasure channels with arbitrary values of erasure probability; and spatially independent erasure channels where the maximum erasure probability does not exceed 8/9.

In this paper we describe a network coding scheme for the Broadcast Erasure Channel with multiple unicast stochastic flows, for the case of a single source transmitting packets to N users, where per-slot feedback is fed back to the transmitter in the form of ACK/NACK messages. This scheme performs only binary (XOR) operations and includes special rules for coding packets that ensure instantaneous decodability. Drawing on the results of network stability under statistical overhearing, we provide a stabilizing policy using this coding scheme. Furthermore, we show that, for N = 4 and i.i.d. erasure events, the stability region of such a system effectively coincides with its information-theoretic capacity region, and provide a stabilizing policy that employs this XOR-based scheme.

Current security systems often rely on the adversary's computational limitations. Wireless networks offer the opportunity for a different, complementary kind of security, which relies on the adversary's limited network presence (i.e., that the adversary cannot be located at many different points in the network at the same time). We present a system that leverages this opportunity to enable n wireless nodes to create a shared secret S, in a way that an eavesdropper, Eve, obtains very little information on S. Our system consists of two steps: (1) The nodes transmit packets following a special pattern, such that Eve learns very little about a given fraction of the transmitted packets. This is achieved through a combination of beam forming (from many different sources) and wiretap codes. (2) The nodes participate in a protocol that reshuffles the information known to each node, such that the nodes end up sharing a secret that Eve knows very little about. Our protocol is easily implementable in existing wireless devices and scales well with the number of nodes; these properties are achieved through a combination of public feedback, broadcasting, and network coding. We evaluate our system through a 5-node testbed. We demonstrate that a group of wireless nodes can generate thousands of new shared secret bits per second, with their secrecy being independent of the adversary's computational capabilities.

We consider the N-user broadcast erasure channel with N unicast sessions (one for each user) where receiver feedback is regularly sent to the transmitter in the form of ACK/NACK messages. We first provide a generic outer bound to the capacity of this system; we then propose a virtual-queue-based inter-session mixing coding algorithm, determine its rate region, and show that it achieves capacity under certain conditions on channel statistics, assuming that instantaneous feedback is known to all users. Removing this assumption results in a rate region that asymptotically differs from the outer bound by 1 bit as L → ∞, where L is the number of bits per packet (packet length). For the case of arbitrary channel statistics, we present a modification of the previous algorithm whose rate region is identical to the outer bound for N = 3, when instant feedback is known to all users, and differs from the bound by 1 bit as L → ∞, when the three users know only their own ACK. The proposed algorithms do not require any prior knowledge of channel statistics.

We consider the N-user memoryless broadcast erasure channel with N unicast sessions (one for each user) where receiver feedback is sent to the transmitter in the form of ACK/NACK messages. We first provide a generic outer bound to the capacity of this system; using concepts from network coding, we then propose a session-mixing coding algorithm applied on specially constructed and maintained virtual queues (at the transmitter side), determine its throughput region and show that it achieves capacity under certain conditions on channel statistics (assuming that instantaneous feedback is known to all users). The algorithm requires no knowledge of channel statistics or future events.

We consider the problem of cross-layer resource allocation for wireless networks operating with rechargeable batteries under general arrival, channel state and recharge processes. The objective is to maximize total system utility, defined as a function of the long-term rate achieved per link, while satisfying energy and power constraints. A policy with decoupled admission control and power allocation decisions is proposed that achieves asymptotic optimality for sufficiently large battery capacity to maximum transmission power ratio (explicit bounds are provided). We present first a downlink resource allocation scenario; the analysis is then extended to multihop networks. The policy is evaluated via simulations and is seen to perform very well even in the non-asymptotic regime. This policy is particularly suitable for sensor networks, which typically satisfy the asymptotic conditions required by our methodology.

We consider a noise-limited wireless sensor network that consists of battery-operated nodes which can route information to a mobile sink in a multi-hop fashion. The problem of maximizing the network's lifetime, defined as the period of time during which the network can route a feasible flow to each sink location subject to power/energy constraints, is cast into a linear program, reduced into a simpler equivalent form and solved via dual decomposition. The unknowns are the sink sojourn times and the routing flow vector for each sink location. The presence of a mobile sink presents new challenges but the problem structure can still be exploited to find the optimal solution. A distributed algorithm based on the subgradient method and using the sink as leader is proposed and its performance is evaluated through simulation for random networks. The algorithm's requirements in memory are also provided.

We examine the performance of a dual-hop nonregenerative system with adjustable relay gain, subject to power constraints. An optimization problem is formulated and solved algorithmically for the binary phase-shift keying bit-error rate utility. The model allows for arbitrary channel statistics. Emphasis is placed on the relation between the optimal solutions obtained when observing the channels of either the first or both hops, as well as the comparison with easily implementable heuristic policies. Numerical results indicate that simple heuristics perform well for a wide range of signal-to-noise ratio (SNR), except for certain high-SNR cases. Finally, the effect of independent channel assumption on system performance is evaluated.

This paper examines the performance of a dualhop, noise-limited, non-regenerative system where the relay gain is allowed to vary as an unknown deterministic function of the channel states, subject to instantaneous (i.e. peak) and average power constraints, the latter directly affecting battery lifetime in wireless systems. A convex optimization problem, in terms of a generic performance metric, is formulated and solved algorithmically for the Signal-to-Noise Ratio (SNR), Shannon rate and BPSK Bit-Error-Rate (BER) utilities. The presented model allows for arbitrary statistics of the fading channels, including correlation between them. Special emphasis is placed on the relation between the optimal solutions obtained when observing the channels of either the first or both hops. The regions in channel state space where zero and full power is allocated are determined in closed form, with numerical results being presented for the Shannon rate and BER utilities. It is observed that, for sufficiently high first hop SNR, monitoring both channels instead of just the first hop can lead to a significant performance increase.