5G makes it possible to reach to very low latency and very high reliability for different use cases. However, it is not clear how mobility procedures would impact the latency and the reliability of these use cases. Therefore, in this paper, we investigate how a packet flows through 5G RAN Protocol Stack and precisely how handovers affect that flow. Later, we present simulation studies conducted under three different scenarios, Future Railway Mobile Communications System Scenario (a high speed train use case that requires very high reliability), a highway scenario for C-V2X communications and an FR2 Urban Scenario for XR use cases. Our findings indicate that optimizing for handover interruption time can improve reliability up to 0.0094% in the FRMCS scenario, up to 0.045% in the Highway scenario, and up to 0.0071% in the FR2 scenario, underlining the importance of mobility procedures for use cases that require very high reliability, up to 99.9999%.

GSM-R (GSM for Railways) is a 2$G$-based standardized ground-to-train communications system that enabled interoperability across different countries. However, as a 2G-based system, it is nearing its lifetime and therefore, it will be replaced with 5G-based Future Railway Mobile Communications System (FRMCS). FRMCS is expected to bring in new use cases that demand low latency and high reliability. However, from a mobility perspective, it is not clear how the low latency and high reliability will be achieved. This paper investigates the effect of handover procedure on latency and reliability and analyzes which use cases of FRMCS can be satisfied using baseline handover. We also sweep through different handover parameter configurations and analyze their effect on mobility performance. Then, we analyze the effect of mobility performance on packet latency and reliability. Our results show that, with baseline handover, Standard Data Communications Scenario is met and optimizing for baseline handover performance can reduce latency by up to 18.5%, indicating that optimizing for mobility performance is crucial in FRMCS.

In this paper we investigate the inter-cell uplink RACH interference in a cellular network. The preamble transmission of a UE towards its serving cell can be received by the neighbouring cells. This is called a phantom preamble. The gNB that receives a phantom preamble transmits a random access response but no MSG3 is received in return, as the UE is not monitoring PDCCH of that gNB. Thus, the phantom preamble causes wasted PDCCH transmission, and we show with our simulations that this can happen up to 20% of all preamble transmissions, that can create a huge waste of downlink resources depending on the RACH load. In conclusion we indicate how the phantom preamble can be turned in to an advantage to obtain and maintain timing advance for the UEs on cell edge.

In this paper, we study binary tree-algorithms that exploit a combination of multi-packet reception (MPR) and successive interference cancellation (SIC), which so far has not been considered in the literature. Specifically, we assume that the receiver is capable of successfully decoding any collision of up to and including$K$concurrent packet transmissions and can perform SIC along the tree. We show a number of novel results for this type of tree algorithms. We first derive the basic performance parameters, which are the expected length of the collision resolution interval and the throughput normalized with$K$, conditioned on the number of contending users. We then analyze their asymptotic behaviour, identifying an oscillatory component that amplifies as$K$increases. In the next step, we derive the maximum stable throughput (MST) for the gated and windowed access assuming Poisson arrivals. We show that for windowed access, the bound on MST normalized with$K$increases with$K$. Finally, we discuss practical issues related to implementation of such scheme, as well as compare it to slotted ALOHA-based schemes that exploit both$K$-MPR and SIC.

In the above article, the authors propose$d$-ary SICTA and derive the expected conditional length of the collision resolution interval, optimal splitting probability and the maximum stable throughput (MST) for$d \geq 2$under stationary ergodic packet arrivals. In this correction, we show that the premise of the analysis for$d > 2$and consequentially the results presented for$d > 2$do not hold.

5G radio access network (RAN) slicing envisions a solution to flexibly deploy heterogeneous services as slices sharing the same infrastructure. However, this level of flexibility renders slice isolation challenging, mainly due to the stochastic nature of wireless resources. In the state-of-the-art, RAN slicing algorithm’s efficiency with respect to slice isolation is related to the ability of meeting individual slice requirements. However, mostly an aggregated slice performance guarantee is considered instead of per user guarantees. Hence, state-of-the-art approaches might not always provide the satisfaction of all users within a slice. Indeed, our results demonstrate that if user requirements within a slice are not included in the RAN slicing algorithm, the per user quality-of-service (QoS) may not be fulfilled. In this paper, we investigate the definition of slice isolation as the ability to satisfy individual users’ throughput within slices, in a frequency selective, multi-cell wireless scenario with focus on maximizing slices’ throughput. Our problem is tackled with a Lyapunov optimization approach, which proves to always achieve slice isolation. Our results show that our solution does not only achieve 100% user QoS guarantees compared to 50% achieved in the state-of-the-art, but also doubles the throughput with increasing number of BSs.

Network edge environments like in-flight or in-train communications utilize satellite-terrestrial integrated networks. These networks however suffer from limited backhaul and cache resources, leading to sustainability issues due to increasing traffic demands. The problem becomes more challenging for 5G ecosystems, where applications have distinct requirements, rendering the management and orchestration of conventional satellite-terrestrial networks harder. Therefore, software-defined networking and edge network slicing are envisioned to enhance resource management and increase flexibility of resource allocation. However, the complexity of management and orchestration increases in cases where service providers, allocated to a slice, do not share information about their users with the infrastructure providers, due to privacy or other concerns. To incorporate the aspect of slice collaboration, we define network slices with respect to their willingness of sharing user traffic statistics with the infrastructure provider. Taking in-flight entertainment and connectivity services (IFECS) as an interesting 5G use-case, we introduce a system model mimicking the practical deployment of slicing for aircrafts using satellites. We propose a mixed integer non linear program that aims at maximizing the number of slices served. Utilizing our model we evaluate the deployment cost of slices with respect to cache and backhaul resources. Our results show that uncooperative slices have a lower selection probability. Nonetheless, we demonstrate that if the slice cost is paid by slice owners, uncooperative slices increase their chances of being served by 33%. Overall, cooperative slicing can revolutionize the IFECS system as it accommodates 200% more slices compared to uncooperative slicing.

The current cellular standardization for 5G is working towards wireless advances to enable further productivity for industrial automation. However, this development will take several years. Meanwhile, the capabilities of the currently available standards should be pushed to their limits. To this end, in this work, we present results from the first inter-slot successive interference cancellation testbed using commercial off the shelf IEEE 802.15.4 sensors. Through our implementation, we have measured a throughput of 0.72 packets per slot which doubles the currently used contention-based access, Slotted ALOHA, with a limit of 0.36 packets per slot. The hardware effects of the boards, which degrade the successive interference cancellation performance from the theoretical limit of 1 packet per slot, are modeled and validated through measurements. We also propose a model that can be used to calculate the expected successive interference cancellation throughput with the specific hardware available in a factory. Furthermore, our proposed model should replace the perfect physical layer assumptions for researchers to design new MAC algorithms taking practical limitations into account.

Age of information (AoI) measures information freshness at the receiver. AoI may provide insights into quality of service in communication systems. For this reason, it has been used as a cross-layer metric for wireless communication protocols. In this work, we employ AoI to calculate penalty functions for a centralized resource scheduling problem. We consider a single wireless link shared by multiple, heterogeneous control systems where each sub-system has a time-varying packet loss probability. Sub-systems are competing for network resources to improve the accuracy of their remote estimation process. In order to cope with the dynamically changing conditions of the wireless link, we define a finite horizon age-penalty minimization problem and propose a scheduler that takes optimal decisions by looking H slots into the future. The proposed algorithm has a worst-case complexity that grows exponentially with H. However, by narrowing down our search space within the constrained set of actions, we are able to decrease the complexity significantly without losing optimality. On the contrary, we show by simulations that the benefit of increasing H w.r.t. remote state estimation performance diminishes after a certain H value.

In this paper, we analyze binary-tree algorithms in a setup in which the receiver can perform multi-packet reception (MPR) of up to and including K packets simultaneously. The analysis addresses both traffic-independent performance as well as performance under Poisson arrivals. For the former case, we show that the throughput, when normalized with respect to the assumed linear increase in resources required to achieve K-MPR capability, tends to the same value that holds for the single-reception setup. However, when coupled with Poisson arrivals in the windowed access scheme, the normalized throughput increases with K, and we present evidence that it asymptotically tends to 1. We also provide performance results for the modified tree algorithm with K-MPR in the clipped access scheme. To the best of our knowledge, this is the first paper that provides an analytical treatment and a number of fundamental insights in the performance of tree-algorithms with MPR.

We consider the distributed resource selection problem in Vehicle-to-vehicle (V2V) communication in the absence of a base station. Each vehicle autonomously selects transmission resources from a pool of shared resources to disseminate Cooperative Awareness Messages (CAMs). This is a consensus problem where each vehicle has to select a unique resource. The problem becomes more challenging when---due to mobility---the number of vehicles in vicinity of each other is changing dynamically. In a congested scenario, allocation of unique resources for each vehicle becomes infeasible and a congested resource allocation strategy has to be developed. The standardized approach in 5G, namely semi-persistent scheduling (SPS) suffers from effects caused by spatial distribution of the vehicles. In our approach, we turn this into an advantage. We propose a novel Distributed Resource Allocation mechanism using multi-agent reinforcement Learning (DIRAL) which builds on a unique state representation. One challenging issue is to cope with the non-stationarity introduced by concurrently learning agents which causes convergence problems in multi-agent learning systems. We aimed to tackle non-stationarity with unique state representation. Specifically, we deploy view-based positional distribution as a state representation to tackle non-stationarity and perform complex joint behavior in a distributed fashion. Our results showed that DIRAL improves PRR by 20% compared to SPS in challenging congested scenarios.

The upcoming industrial revolution requires deployment of critical wireless sensor networks for automation and monitoring purposes. However, the reliability of the wireless communication is rendered unpredictable by mobile elements in the communication environment such as humans or mobile robots which lead to dynamically changing radio environments. Changes in the wireless channel can be monitored with frequent pilot transmission. However, that would stress the battery life of sensors. In this work a new wireless channel estimation technique, Veni Vidi Dixi, VVD, is proposed. VVD leverages the redundant information in depth images obtained from the surveillance camera(s) in the communication environment and utilizes Convolutional Neural Networks (CNNs) to map the depth images of the communication environment to complex wireless channel estimations. VVD increases the wireless communication reliability without the need for frequent pilot transmission and with no additional complexity on the receiver. The proposed method is tested by conducting measurements in an indoor environment with a single mobile human. Up to authors' best knowledge our work is the first to obtain complex wireless channel estimation from only depth images without any pilot transmission. The collected wireless trace, depth images and codes are publicly available.

Enabling closed control loops via wireless communication has attracted a lot of interest recently and is investigated under the name cyber-physical systems. Under cyber-physical systems one challenging scenario is multiple loops sharing a wireless medium, and the age of the control information has to be minimized without sacrificing reliability to guarantee the control stability. The number of transmitting devices depends on the control parameters thus, it is stochastic. Wireless uplink resource allocation given low latency constraints for unknown number of devices is a hard problem. For this problem, random access is the most prominent way to minimize latency, but reliability is sacrificed. However, as reliability is also critical for such applications, improved random access algorithms with hard latency guarantees are needed. Currently available random access algorithms with hard latency guarantees have low throughput and some of them are limited to low number of active devices. In this work, we provide a high-throughput random access algorithm with hard latency-constraints (SICQTA) that scales to any number of active devices. This algorithm, making use of feedback, has a varying throughput between 0.69 and 1 depending on the number of devices, which is unprecedented in the state of the art up to our best knowledge.

Enabling autonomous driving and industrial automation with wireless networks poses many challenges, which are typically abstracted through reliability and latency requirements. One of the main contributors to latency in cellular networks is the reservation-based access, which involves lengthy and resource-inefficient signaling exchanges. An alternative is to use grant-free access, in which there is no resource reservation. A handful of recent works investigated how to fulfill reliability and latency requirements with different flavors of grant-free solutions. However, the resource efficiency, i.e., the throughput, has been only the secondary focus. In this work, we formulate the throughput of grant-free access under reliability-latency constraints, when the actual number of arrived users or only the arrival distribution are known. We investigate how these different levels of knowledge about the arrival process influence throughput performance of framed slotted ALOHA with K-multipacket reception, for the Poisson and Beta arrivals. We show that the throughput under reliability-latency requirements can be significantly improved for the higher expected load of the access network, if the actual number of arrived users is known. This insight motivates the use of techniques for the estimation of the number of arrived users, as this knowledge is not readily available in grant-free access. We also asses the impact of estimation error, showing that for high reliability-latency requirements the gains in throughput are still considerable.

Automation is a key part of the new industrial revolution, that will be enabled by the deployment of thousands of sensors and actuators. The flexible deployment of these devices requires wireless connectivity which is labeled as industrial internet of things, IIoT. The sporadic activity pattern of IIoT devices naturally suggest the use of random access techniques, albeit posing new and unexplored challenges for the current wireless networks. On top of the demand for new access protocols, the latency-reliability requirements further challenge the existing random access protocols. In this work we investigate the adaptation of a well known modern random access algorithm, Irregular Repetition Slotted ALOHA (IRSA) to IIoT in 5G New Radio. The key contribution of the paper is the proposed system level protocol, Adaptive-Multichannel IRSA, that can fulfill the latency-reliability requirements. On top of this, the definition and solution of the resource allocation problem as a resource efficiency optimization guarantees that the algorithm minimizes the system resources. We show that for a set of specific requirements, AMC-IRSA can fulfill the requirements in a lot resource efficient manner. Lastly, we analyze most critical parameters to consider for integration of IRSA for 5G NR.

The problem of wireless M2M communication is twofold: the reliability aspect and the scalability aspect. The solution to this problem demands a delay constrained random access protocol. To this end, we propose admission control based traffic-agnostic delay-constrained random access (AC/DC-RA) protocol. Our main contribution is enabling the stochastic delay constraints agnostic to the traffic, such that the stochastic delay constraint is valid with respect to a varying number of arrivals. We achieve this with an admission control decision that uses a novel collision estimation algorithm for an active number of arrivals per contention resource. We use an adaptive contention resolution algorithm to react to the varying number of arrivals. Using these tools, the admission control solves the stability problem. We show with simulations that the AC/DC-RA provide stochastic delay constrained random access in a traffic agnostic way to sustain a stable performance against Poisson and Beta arrivals without any modification to the protocol.

Emerging technologies enforce strict requirements on future wireless networks such as massive connectivity that cannot be supported with scheduled access. Contention based Non-Orthogonal Multiple Access is a novel technique to overcome strict massive connectivity requirements by efficient use of wireless resources. However, most of the solutions proposed in this direction assumes different loads which would degrade the performance significantly if they would not hold. To stress these assumptions a resource efficiency metric is defined and state of the art solutions are evaluated for varying load regarding this metric. It is shown that the resource efficiency problem in the state of the art can be improved with multiplicity estimation, and hence, we propose Multiplicity estimating Random Access protocol, that adapts to the dynamic loads. This adaptation is evaluated through analytical calculation against the state of the art and it is shown that resource efficiency against with a slight decrease in the metric any load from 1 up to > 103users is supported. In addition, we show how this protocol can be dimensioned and integrated to contention based NOMA.

Industrial control systems are foreseen to operate over hybrid wired/wireless networks. While the controller will be deployed in the wired network, sensors and actuators will be deployed in a wireless sensor network (WSN). To support QoS for control systems, an end-to-end delay bound and a target reliability must be provided in both wireless and wired domains. However, for industrial WSNs, guaranteeing reliability is a challenging task because of low-power communications and the harsh wireless environment. In this work, we present the first QoS framework for arbitrary hybrid wired/wireless networks, which guarantees that the delay bound and the target reliability of each application are provided. As part of this framework, we propose the first reliability-based scheduler for WSN able to achieve a target reliability in the presence of dynamic interference. Simulations of the proposed scheduler prove its suitability in different interference scenarios and motivate further work.

Guaranteeing reliability in highly interfered environments is a challenging requirement of current and future wireless applications. A promising state-of-the-art solution for low-power wireless technologies, e.g., wireless sensor networks (WSNs), is frequency hopping aided with black- and white-listing of channels. Both methods, although increase reliability, sacrifice frequency resources. Extensive measurements of channels' packet drop probabilities show that interfered channels are not fully blocked. Motivated by this discovery, we propose the whitening - a methodology for reliable hopping sequence design without resource sacrifice. We model the efficiency of interfered ISM band channels, and study the gains and trade-offs of applying whitening in different scenarios. Application reliability is achieved by granting re-transmissions within a time deadline. Simulations and measurements, performed on the exemplary use case of Time Slotted Channel Hopping WSNs, show that the proposed methods outperform state-of-the-art solutions in the presence of interference in terms of reliability.

In this paper we analyze a distributed packet drop decision, the deadline based discard DbD, in a lossy wireless sensor network environment. We point out that if the non-stale packet success rate is the single utility function for low latency high reliability applications then we can use the packet delay to evaluate the usefulness under the scope of deadline. The technique results in no decrease in utility function but possible gains. In case the metric is used in a centralized perspective, it even provides gains through decrease in expected serving times of a packet. We show analytically and simulatively that, it is possible to reduce energy consumption, increase resource usage and decrease required buffer size in both distributed and central view. A practical example for energy saving with actual wireless sensor data is also given as a conclusion.