METIS is the EU flagship 5G project with the objective of laying the foundation for 5G systems and building consensus prior to standardization. The METIS overall approach toward 5G builds on the evolution of existing technologies complemented by new radio concepts that are designed to meet the new and challenging requirements of use cases today?s radio access networks cannot support. The integration of these new radio concepts, such as massive MIMO, ultra dense networks, moving networks, and device-to-device, ultra reliable, and massive machine communications, will allow 5G to support the expected increase in mobile data volume while broadening the range of application domains that mobile communications can support beyond 2020. In this article, we describe the scenarios identified for the purpose of driving the 5G research direction. Furthermore, we give initial directions for the technology components (e.g., link level components, multinode/multiantenna, multi-RAT, and multi-layer networks and spectrum handling) that will allow the fulfillment of the requirements of the identified 5G scenarios.

Scenarios for 5G mobile and wireless communications: the vision of the METIS project

Recently, wireless technologies have been growing actively all around the world. In the context of wireless technology, fifth-generation (5G) technology has become a most challenging and interesting topic in wireless research. This article provides an overview of the Internet of Things (IoT) in 5G wireless systems. IoT in the 5G system will be a game changer in the future generation. It will open a door for new wireless architecture and smart services. Recent cellular network LTE (4G) will not be sufficient and efficient to meet the demands of multiple device connectivity and high data rate, more bandwidth, low-latency quality of service (QoS), and low interference. To address these challenges, we consider 5G as the most promising technology. We provide a detailed overview of challenges and vision of various communication industries in 5G IoT systems. The different layers in 5G IoT systems are discussed in detail. This article provides a comprehensive review on emerging and enabling technologies related to the 5G system that enables IoT. We consider the technology drivers for 5G wireless technology, such as 5G new radio (NR), multiple-input–multiple-output antenna with the beamformation technology, mm-wave commutation technology, heterogeneous networks (HetNets), the role of augmented reality (AR) in IoT, which are discussed in detail. We also provide a review on low-power wide-area networks (LPWANs), security challenges, and its control measure in the 5G IoT scenario. This article introduces the role of AR in the 5G IoT scenario. This article also discusses the research gaps and future directions. The focus is also on application areas of IoT in 5G systems. We, therefore, outline some of the important research directions in 5G IoT.

A Comprehensive Survey on Internet of Things (IoT) Toward 5G Wireless Systems

This article provides some fundamental indications about wireless communications beyond LTE/LTE-A (5G), representing the key findings of the European research project 5GNOW. We start with identifying the drivers for making the transition to 5G networks. Just to name one, the advent of the Internet of Things and its integration with conventional human-initiated transmissions creates a need for a fundamental system redesign. Then we make clear that the strict paradigm of synchronism and orthogonality as applied in LTE prevents efficiency and scalability. We challenge this paradigm and propose new key PHY layer technology components such as a unified frame structure, multicarrier waveform design including a filtering functionality, sparse signal processing mechanisms, a robustness framework, and transmissions with very short latency. These components enable indeed an efficient and scalable air interface supporting the highly varying set of requirements originating from the 5G drivers.

5GNOW: non-orthogonal, asynchronous waveforms for future mobile applications

MTC are expected to play an essential role within future 5G systems. In the FP7 project METIS, MTC has been further classified into mMTC and uMTC. While mMTC is about wireless connectivity to tens of billions of machinetype terminals, uMTC is about availability, low latency, and high reliability. The main challenge in mMTC is scalable and efficient connectivity for a massive number of devices sending very short packets, which is not done adequately in cellular systems designed for human-type communications. Furthermore, mMTC solutions need to enable wide area coverage and deep indoor penetration while having low cost and being energy-efficient. In this article, we introduce the PHY and MAC layer solutions developed within METIS to address this challenge.

Massive machine-type communications in 5g: physical and MAC-layer solutions

Space-Time Block Coding for Wireless Communications

The fifth generation of cellular communication systems is foreseen to enable a multitude of new applications and use cases with very different requirements. A new 5G multi-service air interface needs to enhance broadband performance as well as provide new levels of reliability, latency, and supported number of users. In this paper, we focus on the massive Machine Type Communications (mMTC) service within a multi-service air interface. Specifically, we present an overview of different physical and medium access techniques to address the problem of a massive number of access attempts in mMTC and discuss the protocol performance of these solutions in a common evaluation framework.

Towards Massive Connectivity Support for Scalable mMTC Communications in 5G Networks

With the expected growth of machine-to-machine communication, new requirements for future communication systems have to be considered. More specifically, the sporadic nature of machine-to-machine communication, low data rates, small packets and a large number of nodes necessitate low overhead communication schemes that do not require extended control signaling for resource allocation and management. Assuming a star topology with a central aggregation node that processes all sensor information, one possibility to reduce control signaling is the estimation of sensor node activity.

In this paper, we discuss the application of greedy algorithms from the field of compressive sensing in a channel coded code division multiple access context to facilitate a joint detection of sensor node activity and transmitted data. To this end, a short introduction to compressive sensing theory and algorithms will be given. The main focus, however, will be on implications of this new approach. Especially, we consider the activity detection, which strongly determines the performance of the overall system. We show that the performance on a system level is dominated by the missed detection rate in comparison with the false alarm rate. Furthermore, we will discuss the incorporation of activity-aware channel coding into this setup to extend the physical layer detection capabilities to code-aided joint detection of data and activity. Copyright © 2013 John Wiley & Sons, Ltd.

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Compressive sensing based multi-user detection for machine-to-machine communication

Machine-to-Machine communication requires new physical layer concepts to meet future requirements. In previous works it has already been shown that Compressive Sensing (CS) detectors are capable of jointly detecting both activity and data in Multi-User Detection (MUD). To date, the investigations on CS based MUD have omitted the channel estimation and assumed perfect channel knowledge. However, in practical applications the channel also has to be estimated, such that the joint detection of activity and data has to be extended by channel estimation. Therefore, in this paper we investigate how to adapt several approaches to channel estimation, such that they are suitable for this joint detection and estimation. Further, we provide simulation results, showing that low overhead channel estimation can be achieved, with only a small loss in detection accuracy compared to CS based MUD for perfect channel state information.

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Exploiting Sparsity in Channel and Data Estimation for Sporadic Multi-User Communication

Massive Machine Type Communication is seen as one major driver for the research of new physical layer technologies for future communication systems. To handle massive access, the main challenges are avoiding control signaling overhead, low complexity data processing per sensor, supporting of diverse but rather low data rates and a flexible and scalable access. To address all these challenges, we propose a combination of compressed sensing based detection known as Compressed Sensing based Multi User Detection (CS-MUD) with multicarrier access schemes. We name this novel combination Multicarrier CS-MUD (MCSM). Previous investigations on CS-MUD facilitates massive direct random access by exploiting the signal sparsity caused by sporadic sensor activity. The new combined scheme MCSM with its flexibility in accessing time frequency resources additionally allows for either reducing the number of subcarriers or shortening the multicarrier symbol duration, i.e., we gain a high spectral efficiency. Simulation results are given to show the performance of the proposed scheme.

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Carsten Bockelmann

Papers

Massive machine-type communications in 5g: physical and MAC-layer solutions

Towards Massive Connectivity Support for Scalable mMTC Communications in 5G Networks

Compressive sensing based multi-user detection for machine-to-machine communication

Exploiting Sparsity in Channel and Data Estimation for Sporadic Multi-User Communication

Compressive Sensing Multi-User Detection for Multicarrier Systems in Sporadic Machine Type Communication