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Ambient radio frequency (RF) energy harvesting is widely promoted as an enabler for wireless-power Internet of Things (IoT) networks. This article jointly characterizes energy harvesting and packet transmissions in grant-free opportunistic uplink IoT networks energized via harvesting downlink energy. To do that, a joint queuing theory and stochastic geometry model is utilized to develop a spatio-temporal analytical model. Particularly, the harvested energy and packet transmission success probability are characterized using tools from stochastic geometry. Moreover, each device is modeled using a two-dimensional discrete-time Markov chain (DTMC). Such two dimensions are utilized to jointly track the scavenged/depleted energy to/from the batteries along with the arrival/departure of packets to/from devices buffers over time. Consequently, the adopted queuing model represents the devices as spatially interacting queues. To that end, the network performance is assessed in light of the packet throughput, the average delay, and the average buffer size. The effect of base stations (BSs) densification is discussed and several design insights are provided. The results show that the parameters for uplink power control and opportunistic channel access should be jointly optimized to maximize average network packet throughput, and hence, minimize delay. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

The unrelenting increase in the population of mobile users and their traffic demands drive cellular network operators to densify their network infrastructure. Network densification shrinks the footprint of base stations (BSs) and reduces the number of users associated with each BS, leading to an improved spatial frequency reuse and spectral efficiency, and thus, higher network capacity. However, the densification gain comes at the expense of higher handover rates and network control overhead. Hence, user’s mobility can diminish or even nullifies the foreseen densification gain. In this context, splitting the control plane ( $C$ -plane) and user plane ( $U$ -plane) is proposed as a potential solution to harvest densification gain with reduced cost in terms of handover rate and network control overhead. In this paper, we use stochastic geometry to develop a tractable mobility-aware model for a two-tier downlink cellular network with ultra-dense small cells and $C$ -plane/ $U$ -plane split architecture. The developed model is then used to quantify the effect of mobility on the foreseen densification gain with and without $C$ -plane/ $U$ -plane split. To this end, we shed light on the handover problem in dense cellular environments, show scenarios where the network fails to support certain mobility profiles, and obtain network design insights. [ABSTRACT FROM PUBLISHER]

Full-duplex (FD) communication is optimistically promoted to double the spectral efficiency if sufficient self-interference cancellation (SIC) is achieved. However, this is not true when deploying FD-communication in a large-scale setup due to the induced mutual interference. Therefore, a large-scale study is necessary to draw legitimate conclusions about gains associated with FD-communication. This paper studies the FD operation for underlay device-to-device (D2D) communication sharing the uplink resources in cellular networks. We propose a disjoint fine-tuned selection criterion for the D2D and FD modes of operation. Then, we develop a tractable analytical paradigm, based on stochastic geometry, to calculate the outage probability and rate for cellular and D2D users. The results reveal that even in the case of perfect SIC, due to the increased interference injected to the network by FD-D2D communication, having all proximity UEs transmit in FD-D2D is not beneficial for the network. However, if the system parameters are carefully tuned, non-trivial network spectral-efficiency gains (64% shown) can be harvested. We also investigate the effects of imperfect SIC and D2D-link distance distribution on the harvested FD gains. [ABSTRACT FROM PUBLISHER]

Backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band full-duplex (FD) communication, FD base stations (BSs) should support half-duplex (HD) users’ equipment (UEs) without sacrificing the foreseen FD gains. This paper presents flexible and tractable modeling framework for multi-tier cellular networks with FD BSs and FD/HD UEs. The presented model is based on stochastic geometry and accounts for the intrinsic vulnerability of uplink transmissions. The results show that FD UEs are not necessarily required to harvest rate gains from FD BSs. In particular, the results show that adding FD UEs to FD BSs offers a maximum of 5% rate gain over FD BSs and HD UEs case if multi-user diversity is exploited, which is a marginal gain compared with the burden required to implement FD transceivers at the UEs’ side. To this end, we shed light on practical scenarios where HD UEs operation with FD BSs outperforms the operation when both the BSs and UEs are FD and we find a closed-form expression for the critical value of the self-interference attenuation power required for the FD UEs to outperform HD UEs. [ABSTRACT FROM AUTHOR]