Dense deployment of small cells operating on different frequency bands based on multiple technologies provides a fundamental way to face the imminent thousand-fold traffic augmentation. This heterogeneous network (HetNet) architecture enables efficient traffic offloading among different tiers and technologies. However, research on multi-tier HetNets where various tiers share the same microwave spectrum has been well-addressed over the past years. Therefore, our work is targeted towards novel multi-tier HetNets with disparate spectrum (microwave and millimeter wave). In fact, despite the huge capacity brought by millimeter-wave technology, the latter will fail to provide universal coverage, especially indoor, and so mmWave will inevitably co-exist with a traditional sub-6GHz cellular network. In this work, we propose a coordinated user association and spectrum allocation by resorting to non-cooperative game theory. In fact, in such an arduous context, efficient distributed solutions are imperative. Extensive simulation results show the precedence of our coordinated approach in comparison with state-of-the-art heuristics. Moreover, we evaluate the impact of various network parameters, such as mmWave density, cell load, and user distribution and density, offering valuable guidelines into practical 5G HetNet design. Finally, we assess the benefit brought by massive MIMO for mmWave in such a highly heterogeneous setting.

The Internet of Things (IoT) is paving the way to becoming necessary in numerous aspects of people’s lives. IoT is becoming integrated in many domains, such as medical, industrial, and personal. Recent years have witnessed the creation of many IoT technologies that differ not only in their applications and use cases but also in standards. The absence of universally accepted standards and the variety of technologies are only some challenges the IoT market faces. Other challenges include the constrained nature of most IoT devices, the diverse identification schemes, the inadequate security mechanisms, and the lack of interoperability between different technologies. The Domain Name System (DNS) persisted throughout the years as the Internet’s naming service and accumulated more trust from users with the introduction of its security extensions. DNS could be utilized to address some of the challenges the IoT market faces. However, using DNS for IoT applications might jeopardize DNS infrastructure. In this survey, we study the coexistence of DNS and IoT. We define IoT, present its architecture and discuss its main challenges. We then introduce DNS and its function; we discuss its security and privacy drawbacks and the extensions standardized to address them. We further discuss the uses of DNS in IoT environments to address some of IoT’s challenges and the impact these uses might have on DNS.

Due to highly variant traffic in downlink (DL) and uplink (UL) in heterogeneous networks (HetNets), dynamic time-division duplexing (TDD) is proposed to dynamically allocate UL and DL resources. Under the same circumstances, downlink and uplink decoupled access (DUDA) is introduced to balance between UL and DL transmissions and to further improve the system performance. Rather than belonging to a specific cell, a mobile user can receive the downlink traffic from one base station (BS) and send uplink traffic through another BS. In this paper, we analytically investigate a joint TDD and DUDA statistical model with multiple small cells deployment. This model is based on a geometric probability approach. Taking all possible TDD subframes combinations between the macro and small cells, coupled and decoupled cell associations strategies are investigated in details. We derive analytical expressions for the capacity and the interference, considering a network of one macro cell and multiple small cells. We build on the derived capacity expressions to measure the decoupling gain and thus, identify the location of the interferer small cell where the decoupled mode maintains a higher gain in both DL and UL. Monte-Carlo simulations results are presented to validate the accuracy of the statistical model.

Edge Computing provides an effective solution for relieving IoT devices from the burden of handling Machine Learning (ML) tasks. Further, given the limited storage capacity of these devices, they can only accommodate a restricted amount of data for training, resulting in higher error rates for ML predictions. To address this limitation, IoT devices can leverage Edge Computing and collaborate in the learning process through a designated peer acting as an Edge device. However, the transmission of offloaded tasks over a wireless access network poses challenges in terms of time and energy consumption. Consequently, although collaborative learning can diminish the variance of the learned model, it introduces a communication cost, dependent on the chosen Edge device. In light of these considerations, this paper introduces a coalition formation game that proposes a distributed Federated Learning approach, where devices autonomously and efficiently select the most suitable Edge device, aiming to minimize both their learning error and communication cost.

In this paper, we aim to tackle the challenges of resource block scheduling and power allocation in the context of multi-cell full-duplex wireless networks. This is a more realistic setting than the single cell scenario, and it better envisions how full-duplex wireless communications could eventually be implemented. We propose an optimal queue-aware joint scheduling and power allocation algorithm for full-duplex wireless networks in a multi-cell scenario. Because of its mathematical intractability, we decouple the problem and solve it for scheduling first, and for power allocation second. We consider both indoor and outdoor scenarios and show that the gains of multi-cell full-duplex wireless networks, with respect to their half-duplex counter-parts, are not always prevalent. Furthermore, we highlight the importance of inter-cell cooperation when it comes to scheduling resources and show that depending on the scenario at hand, interference mitigation from inter-cell cooperation can improve the performance of user equipment in terms of throughput and waiting delay. Finally, we show that power allocation can improve user equipment throughput with its efficiency being tied to the deployment scenario at hand.