Future 5G/6G cellular Internet of Things (CIoT) technologies need to be able to multiplex a number of traffic types having different arrival patterns, resource requirements, and directions. To this aim, the random access (RA) and data transmission (DT) phases in such technologies should be appropriately optimized. In this paper, we develop a computationally efficient and accurate model accounting for both RA and DT phases and the different nature of traffic types in uplink and downlink directions. We establish the stability criterion for the considered system and then utilize this model to optimize resources allocated to RA and DT phases under different traffic loads in uplink and downlink directions. We show that the proposed model provides accurate assessment of the delay at both RA and DT phases with an error of less than 1%, while its fully analytical structure makes it computationally efficient. Our results also indicate that modern CIoT system are not optimized for different load conditions and even a 5 % decrease in the amount of resources allocated to RA or DT phase changes the supported packet arrival rate by up to 80 %. The model developed in this paper allows optimal tuning RA and DT phases for any offered load conditions in the uplink and downlink directions.

5G New Radio (NR) millimeter wave (mmWave) and future sub-terahertz (sub-THz) 6G systems are designed for rate-greedy multimedia applications. Such applications often utilize rate adaptation allowing to vary the rate according to the network conditions. Unreliable nature of these bands subject to blockage may induce persistent user behavior resulting in repeated attempts (retrials) to continue the service. These effects may lead to the loss of sessions during the service and service provisioning at reduced rate. In this paper, by using the stochastic geometry and queuing theory, we characterize performance of adaptive rate-greedy applications at mmWave/sub-THz base stations. We consider user- and system-centric performance including new and ongoing session drop probabilities, resource utilization, and the amount of wasted resources. Our results show that the user persistence improves the new and ongoing session drop probabilities: making two retrials brings both down by$20-70$% while for fully persistent behavior the gain is 300%. The impact is more pronounced in underloaded system conditions. User persistence also increases the usage of system resources by$20-40$% and decreases the percentage of wasted resources by two/three times. However, these gains come at the expense of decreased successful session completion probability without retrials negatively affecting the overall user experience.

To alleviate the impact of outages caused by dynamic blockage of propagation paths in millimeter wave (mmWave) systems, 3GPP has proposed multi-connectivity operation, where user equipment (UE) maintains simultaneous links to both sub-6 GHz and mmWave BSs. We address one of the most challenging prospective deployments – multi-lane street deployment with intra- and inter-RAT multi-connectivity. By utilizing the mixture of analytical and simulation tools, we first characterize the outage characteristics at mmWave layer. These characteristics further serve as an input to the queuing model characterizing service performance of sub-6 GHz BS serving sub-6 GHz and temporarily offloaded mmWave sessions and implementing traffic protection strategies. Our numerical results show that the use of inter-RAT multi-connectivity to offload mmWave sessions decreases sub-6 GHz session rate multiple times while utilizing multi-connectivity at the mmWave layer allows to partially compensate it. Traffic “jam” road conditions affect the sub-6 GHz session rate reducing it by approximately 20% compared to “normal” road traffic conditions. Furthermore, reserving shares of resources to sub-6 GHz and mmWave traffic favors “heavy-weight” mmWave sessions. On the other hand, individual session resource allocation leads to fair performance. However, this option induces the trade-off between the attained rate and the session drop probability.

Blockage of millimeter-wave (mmWave) radio propagation paths in dense mobile scenarios requires advanced techniques to preserve session continuity in 5G New Radio (NR) systems. In this work, we employ the tools of stochastic geometry and queuing theory as well as rely on 3GPP cluster-based propagation modeling to formulate a mathematical framework, which captures session-level service dynamics of user equipment (UE) that supports multi-band operation. Accordingly, the sub-6 GHz NR base station (BS) is used to temporarily serve the sessions with strict throughput requirements that experience an outage at the mmWave NR BSs. We derive user- and system-centric key performance indicators, including new and ongoing session drop probabilities as well as radio resource utilization. Our numerical results confirm that the use of microwave BSs to serve mmWave sessions is only feasible in light traffic conditions. Particularly, the presence of throughput-hungry mmWave traffic increases the session drop probability at the sub-6 GHz band as well as decreases its utilization. Further, the support of sub-6 GHz radio may not improve the mmWave BS resource utilization, as many mmWave sessions are dropped during their service as a consequence of frequent blockage-induced outage situations.

The intermittent millimeter-wave radio links as a result of human-body blockage are an inherent feature of the 5G New Radio (NR) technology by 3GPP. To improve session continuity in these emerging systems, two mechanisms have recently been proposed, namely, multi-connectivity and guard bandwidth. The former allows to establish multiple spatially-diverse connections and switch between them dynamically, while the latter reserves a fraction of system bandwidth for sessions changing their state from non-blocked to blocked, which ensures that the ongoing sessions have priority over the new ones. In this paper, we assess the joint performance of these two schemes for the user- and system-centric metrics of interest. Our numerical results reveal that the multi-connectivity operation alone may not suffice to increase the ongoing session drop probability considerably. On the other hand, the use of guard bandwidth significantly improves session continuity by somewhat compromising new session drop probability and system resource utilization. Surprisingly, the 5G NR system implementing both these techniques inherits their drawbacks. However, complementing it with an initial AP selection procedure effectively alleviates these limitations by maximizing the system resource utilization, while still providing sufficient flexibility to enable the desired trade-off between new and ongoing session drop probabilities.

The Internet of Things (IoT) undergoes a fundamental transformation by augmenting its conventional sensor network deployments with more advanced and mobile devices, such as connected and self-driving cars. This fusion of embedded and automotive domains promises to deliver unprecedented mutual benefits, where vehicles will receive timely updates from their proximate sensors while assisting them in delivering their sensory data to the remote network infrastructure. In this paper, we put forward the vision of opportunistic crowdsensing applications, in which the ubiquitous deployments of low-cost and battery-constrained IoT sensors take advantage of more capable and energy-abundant vehicle-mounted mobile relays. In particular, we consider the use of the emerging narrowband IoT radio technology recently ratified by 3GPP and offering efficient means for underlying wireless connectivity. Our rigorous mathematical analysis supported with comprehensive system-level evaluations reveals the effects of vehicle-based relays on the important metrics of interest, such as connection reliability, transmission latency, and communication energy efficiency. These systematic findings advocate for an extensive utilization of vehicular relays as part of the next-generation IoT ecosystem.