Marco Centenaro

Long-range communications in unlicensed bands: the rising stars in the IoT and smart city scenarios

Connectivity is probably the most basic building block of the IoT paradigm. Up to now, the two main approaches to provide data access to things have been based on either multihop mesh networks using short-range communication technologies in the unlicensed spectrum, or long-range legacy cellular technologies, mainly 2G/GSM/GPRS, operating in the corresponding licensed frequency bands. Recently, these reference models have been challenged by a new type of wireless connectivity, characterized by low-rate, long-range transmission technologies in the unlicensed sub-gigahertz frequency bands, used to realize access networks with star topology referred to as low-power WANs (LPWANs). In this article, we introduce this new approach to provide connectivity in the IoT scenario, discussing its advantages over the established paradigms in terms of efficiency, effectiveness, and architectural design, particularly for typical smart city applications.

M2M massive access in LTE: RACH performance evaluation in a Smart City scenario

Several studies assert that the random access procedure of the Long Term Evolution (LTE) cellular standard may not be effective whenever a massive number of simultaneous connection attempts are performed by terminals, as may happen in a typical Internet of Things or Smart City scenario. Nevertheless, simulation studies in real deployment scenarios are missing because many system-level simulators do not implement the LTE random access procedure in detail. In this paper, we propose a patch for the LTE module of ns-3, one of the most prominent open-source network simulators, to improve the accuracy of the routine that simulates the LTE Random Access Channel (RACH). The patched version of the random access procedure is compared with the default one and the issues arising from massive simultaneous access from mobile terminals in LTE are assessed via a simulation campaign.

Performance evaluation of LoRa networks in a smart city scenario

Low-Power Wide Area Networks (LPWANs) are continuously gaining momentum as fundamental enablers of the Internet of Things (IoT) paradigm. These networks provide longrange coverage to end nodes, exploiting license-free frequency bands. The focus of this work is on one of the most prominent LPWAN technologies: LoRa™. We implemented a new ns-3 module to study the performance of a LoRa-based IoT network in a typical urban scenario. Simulation results show that a LoRa network can scale well, achieving packet success rates above 95% in presence of a number of end devices in the order of 104.

A study on M2M traffic and its impact on cellular networks

Machine-Type Communication is essential to make the Internet of Things real. This new kind of communication, however, entails a lot of challenges that need to be addressed, especially for what concerns the integration between the human-triggered traffic, i.e., the traffic generated by the people through smartphones and tablets, and machine-triggered traffic, i.e., the data that are autonomously generated by Machine-Type Devices, in the next generation cellular networks, i.e., the 5G. These two types of traffic are completely different, but while the former has been widely studied and appropriately modeled, the latter is still lacking a generally accepted model. In this paper, after a brief survey on traffic models that have been proposed by the academic and the standardization community, we propose and test a general framework to evaluate the performance of a generic cellular network architecture in the context of joint human-triggered and machine-triggered traffic.

Energy-based anchor node selection for IoT physical layer authentication

We consider a cellular Internet of things (CIoT) network where many source nodes aim at exchanging messages with a single concentrator node. To this end, they are assisted by anchor nodes that are trusted and securely connected with the concentrator node. In this context, we aim at providing a message authentication scheme based on the characteristics of the channel between the source nodes and the anchor nodes. According to this approach, the anchor nodes estimate the channel to source nodes in an initially externally authenticated fashion, while forthcoming messages are authenticated by comparing the current channel estimate with the initial estimate. Moreover, assuming that the anchor nodes have a limited energy availability, we derive suitable scheduling policies for the activation of the anchor nodes for authentication purposes. In particular, we aim at maximizing the anchors lifespan while guaranteeing given false alarm and missed detection probabilities of the authentication process. The performance of the proposed authentication protocols is evaluated in a typical CIoT scenario.

A Comparison of Energy-Efficient HARQ Protocols for M2M Communication in the Finite Block-Length Regime

Hybrid Automatic Repeat reQuest (HARQ) techniques are largely used in the context of wireless communications systems especially in the last few years, being employed in the latest cellular systems, including the Long Term Evolution (LTE) standard. Such schemes have been widely studied in literature; however, in this paper we are interested in applying the results of Polyanskiy-Poor-Verdù on the finite block-length regime, comparing the performance of Type-I and Type-II HARQ schemes in the context of green communication, i.e., in a scenario in which the energy efficiency is a key performance indicator. A prominent example of this context is the Machine-to-Machine (M2M) communication, which is foreseen to play a fundamental role as an enabler of the Internet of Things (IoT) paradigm. We derive a novel, optimal, power allocation strategy and we provide simulation results showing that a minimum 40% energy saving can be achieved if we enable packet combining at the receiver side.

Analysis of small packet traffic support in LTE

One of the most important features of the next generation cellular network, commonly referred to as 5G, is the native support of Internet of Things (IoT) traffic, in order to overcome the issues of the actual cellular standard, the Long Term Evolution (LTE), in managing this kind of traffic. However, the IoT market growth is so fast that a seamless integration of IoT traffic from 4G to 5G should be provided. In this context, first of all we tailor the LTE physical channels to the case of small packet traffic. Then, we design a mathematical framework to analyze the performance of two possible variants of the LTE radio access protocol to efficiently support the IoT.

Comparison of Collision-Free and Contention-Based Radio Access Protocols for the Internet of Things

The fifth-generation (5G) cellular networks will face the challenge of integrating the traditional broadband services with the Internet of Things (IoT), which is characterized by sporadic uplink transmissions of small data packets. Indeed, the access procedure of the previous generation cellular network (4G) is not able to support IoT traffic efficiently, because it requires a large amount of signaling for the connection setup before the actual data transmission. In this context, we introduce two innovative radio access protocols for sporadic transmissions of small data packets, which are suitable for 5G networks, because they provide a resource-efficient packet delivery exploiting a connectionless approach. The core of this paper resides in the derivation of an analytical framework to evaluate the performance of all the aforementioned protocols. The final goal is the comparison between 4G and 5G radio access solutions employing both our analytical framework and computer simulations. The performance evaluation results show the benefits of the protocols envisioned for 5G in terms of signaling overhead and access latency.

Impact of correlated primary transmissions on the design of a cognitive radio inference engine

We consider sensing for cognitive network users, in particular focusing on a scenario where a primary user (PU) and a secondary user (SU) operate on the same frequency band. The SU is interested in identifying transmission opportunities when the PU is silent. We investigate how this sensing performed by the SU can be improved through modeling the PU transmission pattern with increasing accuracy. In particular, we are interested in evaluating the impact of correlation in PUs transmissions. Therefore, we assume that the real behavior of the PU follows a Markov chain, used to model correlation in its activity, and we discuss how the maximum likelihood estimation of the SU can be subsequently improved by adding more information about this underlying process. In this way, the estimate can evolve into a maximum a-posteriori criterion, and furthermore knowledge about the whole Markov chain can be exploited. Also, we investigate the practical setup of training periods of variable length used to estimate the PUs parameters.

HARQ in LTE uplink: A simple and effective modification suitable for low mobility users

In this paper a Bayesian approach to increase the throughput and reduce the latency of the Hybrid-ARQ processes in the Long Term Evolution uplink is proposed. The performance of the enhanced system is evaluated and compared to the standard one using a theoretical framework based on the Accumulated Mutual Information and the theory of Markov chains. The proposed modification is simple to implement in real systems and it is shown to be effective, especially in low mobility scenarios.