One of the main challenges slowing the deployment of airborne base stations (BSs) using unmanned aerial vehicles (UAVs) is the limited on-board energy and flight time. One potential solution to such problem, is to provide the UAV with power supply through a tether that connects the UAV to the ground. In this paper, we study the optimal placement of tethered UAVs (TUAVs) to minimize the average path-loss between the TUAV and a receiver located on the ground. Given that the tether has a maximum length, and the launching point of the TUAV (the starting point of the tether) is placed on a rooftop, the TUAV is only allowed to hover within a specific hovering region. Beside the maximum tether length, this hovering region also depends on the heights of the buildings surrounding the rooftop, which requires the inclination angle of the tether not to be below a given minimum value, in order to avoid tangling and ensure safety. We first formulate the optimization problem for such setup and provide some useful insights on its solution. Next, we derive upper and lower bounds for the optimal values of the tether length and inclination angle. We also propose a suboptimal closed-form solution for the tether length and its inclination angle that is based on maximizing the line-of-sight probability. Finally, we derive the probability distribution of the minimum inclination angle of the tether length. We show that its mean value varies depending on the environment from 10° in suburban environments to 31° in high rise urban environments. Our numerical results show that the derived upper and lower bounds on the optimal values of the tether length and inclination angle lead to tight suboptimal values of the average path-loss that are only 0 - 3 dBs above the minimum value.

In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices, several orders of magnitude compared to today's networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, this paper proposes two D2D clustering schemes, namely, random-based clustering and channel-gain-based clustering. Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, this paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, this paper discusses the implementation algorithm and some potential implementation issues and remedies.

The Internet-of-Things (IoT) is the paradigm where anything will be connected. There are two main approaches to handle the surge in uplink (UL) traffic that the IoT is expected to generate, namely, scheduled UL (SC-UL) and random access uplink (RA-UL) transmissions. SC-UL is perceived as a viable tool to control quality-of-service levels while entailing some overhead in the scheduling request prior to any UL transmission. On the other hand, RA-UL is a simple single-phase transmission strategy. While this obviously eliminates scheduling overheads, very little is known about the scalability of RA-UL. At this critical junction, there is a dire need to analyze the scalability of these two paradigms. To that end, this paper develops a spatiotemporal mathematical framework to analyze and assess the performance of SC-UL and RA-UL. The developed paradigm jointly utilizes stochastic geometry and queuing theory. Based on such a framework, we show that the answer to the scheduling versus random access paradox actually depends on the operational scenario. Particularly, the RA-UL scheme offers low access delays but suffers from limited scalability, i.e., cannot support a large number of IoT devices. On the other hand, SC-UL transmission is better suited for higher device intensities and traffic rates.

In one of the several manifestations, 5G networks are required to accommodate a massive number of devices; an order of magnitude compared to today's networks. At the same time, 5G networks will have to observe stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion over random access resources in the cellular uplink. Indeed, congestion drags along delay problems. In this paper, the use of network-orchestrated device-to-device (D2D) relaying is advocated for the mitigation of random access congestion. In particular, it is shown that D2D relaying reduces access delay only at high device densities but is rather an overkill for lower densities. For the sake of an objective evaluation, the overhead of device clustering protocols must be accounted for. As such, this paper provides protocol designers with benchmarks on how much protocol overhead can be tolerated. The feasibility of D2D relaying is demonstrated via extensive system-level simulations run on a super computer and based on a foundation of real-life networks parameters.

With the proliferation of the Internet-of-things (IoT), there is an undeniable consensus that cellular LTE networks will have to support a dramatically larger number of uplink connections. This is true since most of the devices to be added incur machine-type communications which is dominantly upstream. Can current LTE network withstand this challenge? To answer this question, the joint performance of random access process and the uplink data transmission should be investigated. These two problems have been classically treated in the literature in a disjoint fashion. In this paper, they are jointly analyzed as an inseparable couple. To do that, a tandem queuing model is adopted whereby devices are represented as spatially interacting queues. The interaction between queues is governed by the mutual inter-cell and intra-cell interference. To that end, a joint stochastic geometry and queueing theory model is exploited to study this problem and a spatiotemporal analytical model is developed accordingly. Network stability and scalability are two prime performance criteria for performance assessment. In light of these two criteria, the developed model is poised to offer valuable insights into efficient access and resource allocation strategies.

The Internet of Things (IoT) is large scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.

The Internet of Things (IoT) is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the high volumes of traffic that must be accommodated. Cellular networks are indeed a natural candidate for the data tsunami the IoT is expected to generate in conjunction with legacy human-type traffic. However, the random access process for scheduling request represents a major bottleneck to support IoT via LTE cellular networks. Accordingly, this paper develops a mathematical framework to model and study the random access channel (RACH) scalability to accommodate IoT traffic. The developed model is based on stochastic geometry and discrete time Markov chains (DTMC) to account for different access strategies and possible sources of inter-cell and intra-cell interferences. To this end, the developed model is utilized to assess and compare three different access strategies, which incorporate a combination of transmission persistency, back-off, and power ramping. The analysis and the results showcased herewith clearly illustrate the vulnerability of the random access procedure as the IoT intensity grows. Finally, the paper offers insights into effective scenarios for each transmission strategy in terms of IoT intensity and RACH detection thresholds.

In this paper, we promote the use of multihop networking in the context of large-scale Internet of Things (IoT). Recognizing concerns related to the scalability of classical multihop routing and medium access techniques, we advocate the use of blind cooperation in conjunction with multihop communications. However, we show that blind cooperation is actually inefficient unless power control is applied. Inefficiency in this paper is projected in terms of the transport rate normalized to energy consumption. To that end, we propose an uncoordinated power control mechanism whereby each device in a blind cooperative cluster randomly adjusts its transmit power level. We derive an upper bound on the mean transmit power that must be observed at each device. We also devise a practical mechanism for each device to infer about the size of its neighborhood, a requirement necessary for the operation of the power control scheme. Finally, we assess the performance of the developed power control mechanism and demonstrate how it consistently outperforms the point-to-point case.

Beaconless position-based forwarding protocols have recently evolved as a promising solution for packet forwarding in wireless sensor networks. Quite a few variants of this class of forwarding protocols have been proposed over the years. One common observation is that they have all been evaluated from the perspective of a single node. Although useful, but a solid understanding of the end-to-end performance is still necessary. In this paper, we shed light on the end-to-end performance of beaconless position-based protocols along three distinct dimensions: energy, latency, and back-off probability. The latter is used as a direct indicator of the network's transport capacity. Consequently, we are able to provide an elaborate response to the question: what does it really cost to deliver a packet in a wireless sensor network using position-based beaconless forwarding protocols? In responding to this question, we highlighted the different performance tradeoffs inherent to beaconless position-based protocols. Furthermore, some operational recommendations are also provided.

Beaconless position-based forwarding protocols have recently evolved as a promising solution for packet forwarding in wireless sensor networks. However, as the node density grows, the overhead incurred in the process of relay selection grows significantly. As such, end-to-end performance in terms of energy and latency is adversely impacted. With the motivation of developing a packet forwarding mechanism that is tolerant to variation in node density, an alternative position-based protocol is proposed in this paper. In contrast to existing beaconless protocols, the proposed protocol is designed such that it eliminates the need for potential relays to undergo a relay selection process. Rather, any eligible relay may decide to forward the packet ahead, thus significantly reducing the underlying overhead. The operation of the proposed protocol is empowered by exploiting favorable features of orthogonal frequency division multiplexing (OFDM) at the physical layer. The end-to-end performance of the proposed protocol is evaluated against existing beaconless position-based protocols analytically and as well by means of simulations. The proposed protocol is demonstrated in this paper to be more efficient. In particular, it is shown that for the same amount of energy the proposed protocol transports one bit from source to destination much quicker.

Beaconless position-based forwarding protocols have recently evolved as a promising solution for packet forwarding in wireless sensor networks. However, as the network density grows, the overhead incurred grows significantly. As such, end-to-end energy and delay performance is adversely impacted. Motivated by the need for a forwarding mechanism that is more tolerant to growth in node density, an alternative position-based protocol is proposed in this paper. The protocol is designed such that it completely eliminates the need for potential relays to undergo a relay election process. Rather, any eligible relay may decide to forward the packet ahead, thus significantly reducing the overhead. The operation of the proposed protocol is empowered by exploiting favorable features of orthogonal frequency division multiplexing (OFDM) at the physical layer. End-to-end performance is evaluated here against existing beaconless protocols. It is demonstrated that the proposed protocol is more efficient since it is able to offer lower end-to-end delay for the same amount of energy consumption.

Digital audio broadcast (DAB) systems are considered for delivery of audio information to users in heavily attended sporting, cultural, and amusement events [1]. A unique property of such events is the high density of users. A direct result of this property is the high spatial fading correlation. This in fact may be taken into advantage to enhance the reception quality at DAB terminals. In this paper, a cooperative communication scheme is proposed in which DAB terminals are provided with the capability to relay the audio transmission using an Amplify- and-Forward (AF) strategy. The proposed scheme is shown to provide significant performance enhancements. Analysis results provided in this paper also suggest that considerable reductions in power consumption at DAB terminals may be also attained using the proposed scheme.

The performance of a multihop wireless network is typically affected by the interference caused by transmissions in the same network. In a statistical fading environment, the interference effects become harder to predict. Information sources in a multihop wireless network can improve throughput and delay performance of data streams by implementing interference-aware packet injection mechanisms. Forcing packets to wait at the head of queues and coordinating packet injections among different sources enable effective control of co-packet interference. In this paper, throughput and delay performance in interference-limited multi-hop networks is analyzed. Using non-linear probabilistic hopping models, waiting times which jointly optimize the performance are derived. Optimally coordinated injection strategies are also investigated as functions of the number of information sources and their separations. Obtained results provide guidelines for the placement of relay nodes in multihop wireless networks.