In Release 13 the Third Generation Partnership Project (3GPP) developed the Narrowband Internet of Things (NB-IoT). It is a cellular technology providing wireless connectivity to machine-type services and applications. In 3GPP Releases 14 and 15, NB-IoT evolved to meet the requirements defined for a fifth generation (5G) communications system in 3GPP and in the International Telecommunications Union Radiocommunication (ITU-R) sector. This paper introduces NB IoT in the context of 3GPP's recent work on 5G. It presents the ITU-R International Mobile Telecommunication 2020 (IMT 2020) and 3GPP 5G performance requirements. A complete evaluation of the NB IoT performance for each of these requirements is presented, and it is shown that NB IoT meets the 5G performance requirements for massive IoT (mIoT) services.

Future automotive systems are expected to significantly benefit from a range of diverse mechanisms and capabilities that will be offered by the emerging fifth-generation (5G) cellular technology. In particular, one of the most prominent 5G use cases is represented by the Vehicle-to-Everything (V2X) context, which aims to enhance people's driving experience with collective safety and infotainment applications (e.g., autonomous driving, driver assistance, and contextual information). To achieve the requirements of better reliability, lower latency, and higher data rate, the use of extremely high frequencies (known as millimeter-wave, mmWave) is envisioned as an efficient solution. In fact, very high numbers of sensors deployed on vehicles introduce a serious challenge for the initial access procedure due to likely collisions in case of massive connection attempts. For that reason, the goal of this work is to offer improvements to the reliability of the initial access procedure for 5G mmWave cellular in massive V2X communications scenarios. In doing so, we propose to exploit redundant preamble transmissions in order to faster acquire a data transmission opportunity. Our obtained results indicate that by sending multiple replicas of a random access preamble the success probability to transmit at the first attempt is at least twice higher than that with the legacy approaches where a single random access preamble is being sent.

In this paper, we propose a simple and practical method to analyze multi-channel random-access systems with a large number of machine-to-machine (M2M) devices, which helps determine the average data access latency, as well as characterize the system stability region. The proposed methodology can be applied to random-access 3GPP LTE channels and delivers the system-optimal retransmission probability for M2M data access, which is a key parameter for highly-populated industry-grade systems with stringent data access latency requirements. The presented numerical results compare our proposed retransmission control solution against a heuristic device-centric retransmission control procedure and quantify the respective performance gains.

LTE Release 13 has introduced coverage enhancement (CE) mode "CE Mode B" to support MTC deployments that require medium-to-large CE, compared to the baseline LTE coverage for voice communications. In this paper, we describe the operation of CE Mode B for the supported physical data and control channels, and study the dimensioning of this mode for each of these channels. We provide link-level simulation results for CE Mode B, which illustrate the possibility of MTC operation at a coupling loss up to 160 dB. Further, we study the achievable uplink capacity in terms of the blocking probability of new scheduling requests. Finally for a few representative scenarios, we show that the existing LTE configurations can provide sufficient uplink capacity.

In this paper, we address the emerging concept of Machine-Type Communications (MTC), where unattended wireless devices send their data over the Long Term Evolution (LTE) cellular network. In particular, we emphasize that future MTC deployments are expected to feature a very large number of devices, whereas the data from a particular device may be infrequent and small. Currently, LTE is not optimized for such traffic and its data transmission schemes are not MTC-specific. To improve the efficiency of small data access, we propose a novel contention-based LTE transmission (COBALT) mechanism and evaluate its performance with both analysis and protocol-level simulations. When compared against existing alternatives, our data access scheme is demonstrated to improve network resource consumption, device energy efficiency, and mean data access delay. We conclude that COBALT has the potential for supporting massive MTC deployments based on the future releases of the LTE technology.

The random linear fountain (RLF) is an efficient form of fountain coding with an expected overhead of only 1.6 packets. Because of increasing computational complexity, however, it cannot be directly used for large message sizes. In this paper, we study the performance penalty of dividing the data into k parts which are coded using the RLF. To ease the performance problem, we propose the use of macropackets which are generated by using LT-coding over the different parts of divided RLF. We calculate the decoding probabilities for k = 2 and 3 and compare the results to the overhead obtained using the combination of divided RLF and data carousel. The results indicate that while the use of macropackets improves the performance over the divided RLF, still better performance is obtained by data carousel in the case of low channel loss rate.

Fountain codes provide an efficient way to transfer information over erasure channels. We give an exact performance analysis of a specific type of fountain codes, called LT codes, when the message length N is small. Two different approaches are developed. In a Markov chain approach the state space explosion, even with reduction based on permutation isomorphism, limits the analysis to very short messages, N < 4. An alternative combinatorial method allows recursive calculation of the probability of decoding after N received packets. The recursion can be solved symbolically for values of N < 10 and numerically up to N ap30. Examples of optimization results give insight into the nature of the problem. In particular, we argue that a few conditions are sufficient to define an almost optimal LT encoding.