Millimeter wave communications are essential for modern wireless networks. It supports high data rates but suffers from severe path loss, which requires precise beam alignment to maintain reliable links. This beam management is particularly challenging in highly dynamic scenarios such as vehicle-to-infrastructure, and several methods have been presented. In this work, we propose a deep learning-based beam tracking framework based on sequential prediction using recurrent neural networks with an autoregressive inference strategy that reduces measurement overhead. The proposed architecture can support deep learning models trained for both classification and regression. In contrast to many existing studies that evaluate beam tracking under predominantly line-of-sight (LOS) conditions, our work explicitly includes highly challenging non-LOS scenarios - with up to 50% non-LOS incidence in certain datasets - to rigorously assess model robustness. Experimental results demonstrate that our approach maintains high top- K accuracy, even under adverse conditions, while reducing the beam measurement overhead by up to 66%.

In this article, we propose a novel formulation that jointly considers the Virtualized Network Function (VNF) placement at the Radio Access Network (RAN) nodes and the resource allocation for the Transport Network (TN) of sliced and disaggregated RANs. Unlike most works in the literature that address these network aspects separately, we propose a joint approach. Our proposal ensures an end-to-end delay bound for the Ultra-Reliable and Low-Latency Communications (URLLC) use case in an Industry 4.0 scenario, while simultaneously considering the number of admitted User Equipments (UEs), the transmission rate allocation per slice, the functional split of RAN nodes, and the routing paths in the TN. We use Network Calculus (NC) theory to calculate delay along the TN connecting disaggregated RANs deploying network functions at the Radio Unit (RU), Distributed Unit (DU), and Central Unit (CU) nodes. The maximum end-to-end delay is modeled as a constraint in the optimization-based formulation that maximizes the number of admissible flows meeting strict Quality of Service (QoS) requirements, while also taking into account the deployment and operational costs of disaggregated RANs. In this approach, we propose a strategy based on real data from one of the world’s leading Mobile Network Operators (MNOs) to derive coherent estimations to the weights of the proposed objective function. The optimization model leverages a Flexible Functional Split (FFS) approach to provide a new degree of freedom to the resource allocation strategy. Simulation results reveal that, due to its non-linear nature, there is no trivial solution to the proposed optimization problem. Simulation results also show that our proposal guarantees a maximum delay for URLLC use cases in Industry 4.0 while satisfying bandwidth requirements for enhanced Mobile Broadband (eMBB) services.

A key challenge related to Radio Access Network (RAN) slicing is deciding how to efficiently map radio resources from the physical radio to realise RAN slices, known as the virtual wireless network embedding problem. To the best of our knowledge, this is the first paper to model and derive an analytical solution for embedding heterogeneous RAN slices with different waveforms, numerologies and Radio Access Technologies (RATs) with resources isolated down to the Physical (PHY) layer, ultimately enabling secure technology-agnostic RAN as a Service (RANaaS). First, we assess how current virtual wireless network embedding solutions model the allocation of radio resources to realise RAN slices. Then, we propose a graph-based model for embedding heterogeneous RAN slices that considers the guard bands required to ensure isolation in the frequency domain. This approach is transparent to the type and granularity of radio resources of each RAN slice, and can be extended to support RAN slices with new waveforms, numerologies and RATs. Next, we introduce a resource management optimisation problem solved at the Network Provider (NP) to determine the optimal embedding of RAN slices that maximises the total useful bandwidth occupied by tenants; and we propose three different heuristic algorithms to obtain solutions in near real-time. We compare their performance against the analytical solution using different metrics, and our results show that the best heuristic depends on the NP’s business model, e.g., using the Greedy Algorithm (GA) to increase resource utilisation or the Nearest Neighbour Algorithm (NNA) to increase the number of allocated RAN slices.

The 60 GHz mmWave unlicensed band has a very large spectrum available, divided into four orthogonal channels, which allows up to 7 Gbps data rate. On the other side, the propagation in the 60 GHz band is subject to severe path loss attenuation, which can be mitigated using highly directional antennas. This high directionality brings a new challenge to neighbor discovery; the devices now need to know the exact neighbors’ physical location to successfully communicate with them. In order to expedite the neighbor discovery process, multiband protocols have been proposed in the literature in which a separate band is used for the exchange of control messages in an omnidirectional mode. Nonetheless, these proposals suffer from the control channel bottleneck problem due to the numerous messages that need to be exchanged in this channel. In this work, we propose a scheme that divides the network nodes in clusters and for each cluster we allocate one separate control channel and also a separate mmWave channel for beamforming only. The former separation allows decreasing the number of control messages exchanged in each control channel, and the latter allows the simultaneously execution of multiple beamforming. In conjunction to this clustering scheme, we propose a multiband protocol in which only the cluster leader performs beamforming and uses the control channel to propagate the information obtained during this process. We compare the existing protocols with our proposed clustering protocol in terms of average transmission time, overhead, and accuracy of neighbor discovery information.

Cognitive radios (CRs) are a promising solution for the spectrum scarcity problem. These radios access the spectrum in an opportunistic manner in order to take advantage of frequency bands, i.e. channels, left unused by primary users while not interfering with them. This opportunistic access model requires CRs to switch among channels searching for new opportunities and making contact with their neighbors to exchange the information needed for spectrum management. This search process, known as rendezvous (RV), is termed blind RV when it does not use a common control channel (CCC) or a centralized solution. Several algorithms have been proposed to deal with the blind RV problem. However, most of them do not deal with broadcast transmissions, that is, when a CR wants to exchange information with all its neighboring nodes. This paper proposes a broadcast mechanism that operates on top of different one-to-one RV algorithms but being agnostic to the one in use, i.e., any such mechanism can be combined with it. Simulation results show that the proposed mechanism achieves a favorable performance while inheriting the good properties of the underlying one-to-one RV algorithm.

This work investigates the problem of channel sensing order used by a cognitive multichannel network, where each user is able to perform primary user detection on only one channel at a time. The sensing order indicates the sequence of channels sensed by the secondary users when searching for an available channel. When using an optimal sensing order, the secondary user can find faster a free channel with high quality. Brute-force algorithms may be used to find the optimal sensing order. However, this approach requires great computational effort. Even in scenarios where the secondary user knows the probability of each channel being available, the sensing order where the most available channels are sensed first is not ideal when using adaptive modulation. Therefore, we propose an approach using reinforcement learning to search dynamically for the optimal sensing order. Through simulations, we evaluated our proposal and compared its performance with other mechanisms, and the results obtained are close to the optimal value provided by the brute-force and superior to the other mechanisms in most of the scenarios.

Cognitive radios (CRs) are devices that access spectrum opportunistically taking advantage of unused portions of licensed spectrum. Therefore, depending on the licensed radios activity, cognitive devices may suffer from constant communication disruptions or even lack of opportunities in the access of the spectrum. To solve this problem, we propose a new paradigm of interaction between 802.11 radios and CRs to build hybrid mesh networks. In this architecture every node has 802.11 interfaces, which offer minimum spectrum access guarantees, and some special nodes possess additional CR interfaces, which may be opportunistically used to create cognitive shortcut links. These shortcuts improve the hybrid network performance reducing the number of hops in routes and alleviating spectrum sharing in 802.11 channels. In order to create these shortcuts, we propose a shortcut discovering and selecting mechanism that presents a good performance when compared to an optimal case.

Increasing the capacity of wireless mesh networks has motivated numerous studies. In this context, link scheduling has been one of the most investigated mechanisms. However, the isolated use of scheduling mechanisms does not guarantee a significant increase in capacity independently of the routes followed by traffic. For this reason, the use of cross-layer optimization techniques involving joint use of scheduling and routing has been recommended in the literature. This paper demonstrates the loss of efficiency caused by the lack of interaction between these two mechanisms. Then, a joint mechanism is proposed, evaluated and compared through simulations. Results show the gains obtained by using this approach.

The IEEE 802.11e standard is intended to support applications with QoS requirements. However, such provisioning cannot be achieved when the network load is high. This paper introduces a new control mechanism which dynamically tunes the parameters of the 802.11e contention-based access method. The proposed mechanism aims at providing QoS as well as ameliorating the problem of delay asymmetry.

As the size of mobile self-organizing networks increases, the efficiency of location services must increase as well so that addressing/routing scalability does not become an issue. In this paper, we propose a novel architecture, called Twins, tailored for self-organizing networks. Twins architecture involves addressing and locating nodes in large networks, forwarding packets between them, and managing in the presence of mobility/topology changes. Twins defines a logical multidimensional space for addressing and forwarding, while location service and management operations make use of a one-dimensional space. To improve scalability and performance, forwarding is hop-by-hop with greedy next-hop choice and the location service uses a rendezvous paradigm to distribute information among nodes. In this paper, we describe the Twins architecture and present a performance evaluation to assess scalability, fairness in the overhead distribution among nodes, and routing robustness.

The need for efficient location mechanisms is an important issue in scalable self-organizing networks. Existing solutions are inherently dependent on the spatial distribution of nodes in the topology. This leads to limitations that go against the principles of self-organization. In this paper, we propose Twins, an easily-managed location service for self-organizing networks. Twins defines a logical multidimensional space that is a strict mathematical representation of the network geographic space. This representation is obtained through Hilbert space-filling curves. The geographic space is used for addressing and routing, while localization is based on the curve. Control messages are routed based on the logical structure while data packets are routed in a hop-by-hop basis with greedy next-hop choice. In this paper, we evaluate the Twins management operations in terms of fairness of space sharing and logical/geographic distances between nodes and their location servers. Our results show that Twins assures a fair distribution of control overhead and scales well with the number of nodes.

The paper presents the ALCA (asymmetric link collision avoidance) protocol, which was designed to deal with a known deficiency of basic schemes for power control in IEEE 802.11 ad hoc networks. The performance of ALCA is investigated and results indicate that ALCA outperforms a known solution to the problem while being a considerably less complex solution.

The deployment of a geographic location service for Internet hosts enables a whole new class of location-aware applications. We focus on a technique that infers host locations using delay measurements to geographically distributed landmarks, which are hosts with a known geographic location. The problem we deal with is where to place such landmarks and the probe machines that perform the delay measurements. We propose a demographic placement approach to improve the representativeness of each landmark with respect to the hosts to be located. Results show that a relatively small number of landmarks is sufficient to cover the most part of hosts to be located. For a fixed number of landmarks, the demographic approach reduces the distances from most hosts to the nearest landmark. Considering the probe machines, we show that they have to be sparsely placed to avoid gathering redundant data.

This paper compares TCP loss recovery mechanisms that were proposed by the IETF to overcome TCP Reno lack of ability to recover efficiently from multiple losses in a single transmission window. The TCP extensions: NewReno, SACK and limited transmit, are compared under different traffic scenarios.

This paper proposes the Tribe protocol, an indirect routing strategy for wireless self-organizing networks. The protocol is intended to be applied in environments with large number of users, where mobility is taken into account, and the correct operation of the system does not require the support of a fixed (wired or wireless) infrastructure. In Tribe, nodes build a network infrastructure which describes the node's relative location according to the current node's neighborhood. Furthermore, routing is unique and completely independent of any global connectivity ensured by a network-level routing protocol. The architecture is generic, self-organizing, and independent of IP-like addressing limitations.

This paper investigates the joint use of push-out mechanisms with random early detection (RED)-like discarding policies to support service differentiation in the Internet. The efficiency and the degree of differentiation of a complete sharing with push-out, a RIO (RED with in/out) and a RIO with push-out queues are assessed. Results indicate that push-out used jointly with RED-like policies does not improve the performance.

The differentiated services architecture has been proposed to offer quality of service in the Internet. Most works on DiffServ (DS) handles QoS guarantees in a per node basis, which assumes that assuring QoS in a single node also leads to the desired QoS in the entire DS domain. Nevertheless, this is not always true. This paper proposes a framework that offers QoS in a DS domain using policy-based management and fuzzy logic techniques. The QoS controller reconfigures all DS nodes according to ingress traffic and domain policies. Policy based management is used in this framework to provide QoS in the DS domain, controlling heterogeneous equipments of different manufacturers. The performance and functionalities of a prototype are shown by simulation of a voice over IP application in different DS topologies.

The need to offer different service levels on the Internet has encouraged the research in differentiated services (diffserv or DS) (K. Nichols et al., 1998; S. Blake et al., 1998). The article analyses the behavior and evaluates the performance of a fair traffic marker implementation, called Fair Marker (FM), as proposed by H. Kim (1999). The implementation exploits the duality between buffer allocation and token consumption in a token bucket marker in order to enforce fairness among different flows originated from the same subscriber network in a differentiated services (diffserv) domain. The results obtained show that fairness can be achieved when parameters are correctly set. We establish well-defined guidelines to help configure the FM parameters. The results also show that the FM cannot provide fairness in the allocation of excess bandwidth. In order to overcome this problem, we present an extension to the original proposal called Three-Color Fair Marker (TCFM). As an additional contribution, marking strategies proposals are discussed and classified.