5G mMTC Research Articles

Resource allocation for UAV-assisted 5G mMTC slicing networks using deep reinforcement learning

The Internet of Things (IoT) application scenarios is becoming extensive due to the quick evolution of smart devices with fifth-generation (5G) network slicing technologies. Hence, IoTs are becoming significantly important in 5G/6G networks. However, communication with IoT devices is more sensitive in disasters because the network depends on the main power supply and devices are fragile. In this paper, we consider Unmanned Aerial Vehicles (UAV) as a flying base station (BS) for the emergency communication system with 5G mMTC Network Slicing to improve the quality of user experience. The UAV-assisted mMTC creates a base station selection method to maximize the system energy efficiency. Then, the system model is reduced to the stochastic optimization-based problem using Markov Decision Process (MDP) theory. We propose a reinforcement learning-based dueling-deep-Q-networks (DDQN) technique to maximise energy efficiency and resource allocation. We compare the proposed model with DQN and Q-Learning models and found that the proposed DDQN-based model performs better for resource allocation in terms of low transmission power and maximum energy efficiency.

Repetition with Learning Approaches in Massive Machine Type Communications

In the 5G massive machine type communication (mMTC) scenario, user equipment with poor signal quality requires numerous repetitions to compensate for the additional signal attenuation. However, an excessive number of repetitions consumes additional wireless resources, decreasing the transmission rate, and increasing the energy consumption. An insufficient number of repetitions prevents the successful deciphering of the data by the receivers, leading to a high bit error rate. The present study developed adaptive repetition approaches with the k-nearest neighbor (KNN) and support vector machine (SVM) to substantially increase network transmission efficacy for the enhanced machine type communication (eMTC) system in the 5G mMTC scenario. The simulation results showed that the proposed repetition with the learning approach effectively improved the probability of successful transmission, the resource utilization, the average number of repetitions, and the average energy consumption. It is therefore more suitable for the eMTC system in the mMTC scenario than the common lookup table.

An Improved Random Access Scheme Using Directional Beams for 5G Massive Machine-Type Communications

In the 5th generation (5G) massive machine-type communication (mMTC), random access is the limiting factor of performance because there may be massive user equipments (UEs) up to 1 million unit competing for the access opportunities. Existing random access schemes in the 4th generation (4G) or 5G systems are not able to handle such large amount of concurrent random access requests. This paper proposes a random access scheme based on directional beams, which offers a new spatial degree of freedom to improve the random access performance in 5G mMTC. In this scheme, a cell is divided into beam zones in space domain. UEs in different beam zones choose a certain physical random access channel (PRACH) resource with different probability. When preamble collision occurs, uplink radio resource is allocated to the beam zone which has low collision probability. We provide theoretical performance analysis of the proposed scheme using different performance metrics. Comparisons are carried out between the proposed and several existing random access schemes. The proposed scheme can be easily deployed without any modification to 5G framework. Existing random access optimizing algorithms can also be applied to the proposed scheme.

DECT-2020 New Radio: The Next Step toward 5G Massive Machine-Type Communications

Massive machine type communications (mMTC) is one of the cornerstone services that must be supported by 5G systems. 3GPP has already introduced LTE-M and NB-IoT, referred to as cellular IoT (CIoT), in 3GPP Releases 13, 14, and 15, and submitted these technologies as part of 3GPP's IMT-2020 technology submission to ITU-R. Even though NB-IoT and LTE-M have been shown to satisfy 5G mMTC requirements, it is expected that these CIoT solutions will not address all aspects of IoT and ongoing digitalization, including the support for direct communication between “things” with flexible deployments, different business models, as well as support for even higher node densities and enhanced coverage. In this article, we first describe the Digital Enhanced Cordless Tele-communications (DECT) DECT-2020 standard recently published by ETSI for mMTC communications. We then evaluate its performance and compare it to the existing low-power wide area network solutions, showing that it outperforms those in terms of supported density of nodes while keeping delay and loss guarantees at the required level.

Constellation Shared Multiple Access - A Noma Scheme for Increased User Capacity in 5G MMTC

While the legacy cyclic prefix orthogonal frequency division multiple access is retained as the preferred multiple access scheme for 5G enhanced mobile broadband the research is now focussed on the multiple access schemes for massive machine type communication (mMTC) and ultra-reliable low latency communication .Though orthogonal multiple access schemes provide simple reception, they limit number of simultaneous user equipment as against the primary requirement of mMTC. On the other hand, the various non-orthogonal multiple access schemes which have been proposed so far as the likely solution, need complex successive interference cancellation receivers. So a simplified scheme named constellation shared multiple access is proposed here which substantially increases the number of simultaneous users to be served within a single resource block (RB) in LTE or 5G New Radio, thus aiding the massive connectivity requirement of mMTC. This is achieved by differentiating among the users in constellation domain. Moreover, the simple architecture compatible with 5G eMBB makes it a strong contender multiple access contender for 5G mMTC.

Energy Minimized Computation Offloading With Popularity-Based Cooperation in 5G mMTC Networks

Due to enhancements in Internet of Things (IoT) technology, users can now control numerous IoT devices that are integrated for a system (e.g., smart building management system, smart factory, etc.) through mobile user equipment (UE). As the number of controllable IoT devices increases, the amount of data that needs to be processed has increased along with the energy consumption. Since many IoT devices and most UEs are battery operated, minimizing the energy consumption is very important. One solution is to have a multiaccess edge computing (MEC) system conduct the computation instead of the IoT devices and UEs to help save their energy. In this article, an energy-optimized offloading approach that uses MEC computing support to process cooperative tasks is investigated. An optimization problem model is developed to minimize the energy consumption of IoT devices and UEs that have service delay limits. The numerical results demonstrate that the proposed IoT and UE popularity-based energy optimization (IPEO) scheme provides a better performance compared to the conventional MEC offloading methods.

NB-IoT and LTE-M towards massive MTC: Complete performance evaluation for 5G mMTC

Since the emerging 5G wireless network is expected to significantly revolutionize thefield of communication, its standardization and design should regard the internet ofthings (IoT) among the main orientations. Also, emerging IoT applications introducenew requirements other than throughput to support massive machine-type commu-nication (mMTC) where small data packets are occasionally sent. Therefore, moreimportance is attached to coverage, latency, power consumption, and connection den-sity. For this purpose, the third generation partnership project (3GPP) has introducedtwo novel cellular IoT technologies supporting mMTC, known as NB-IoT and LTE-M. This paper aims to determine the system configuration and deployment required forNB-IoT and LTE-M technologies to fully meet the 5G mMTC requirements in termsof coverage, throughput, latency, battery life, and connection density. An overview ofthese technologies and their design principles is also described. A complete evalua-tion of NB-IoT and LTE-M performance against 5G mMTC requirements is presented,and it is shown that these requirements can be met but only under certain conditionsregarding system configuration and deployment. This is followed by a performancecomparative analysis, which is mainly conducted to determine the limits and suitableuse cases of each technology.

Is Satellite Ahead of Terrestrial in Deploying NOMA for Massive Machine-Type Communications?

Non-orthogonal multiple access (NOMA) technologies are considered key technologies for terrestrial 5G massive machine-type communications (mMTC) applications. It is less known that NOMA techniques were pioneered about ten years ago in the satellite domain to match the growing demand for mMTC services. This paper presents the key features of the first NOMA-based satellite network, presenting not only the underlying technical solutions and measured performance but also the related deployment over the Eutelsat satellite fleet. In particular, we describe the specific ground segment developments for the user terminals and the gateway station. It is shown that the developed solution, based on an Enhanced Spread ALOHA random access technique, achieves an unprecedented throughput, scalability and service cost and is well matched to several mMTC satellite use cases. The ongoing R&D lines covering both the ground segment capabilities enhancement and the extension to satellite on-board packet demodulation are also outlined. These pioneering NOMA satellite technology developments and in-the-field deployments open up the possibility of developing and exploiting 5G mMTC satellite- and terrestrial-based systems in a synergic and interoperable architecture.

HARQ-Based Grant-Free NOMA for mMTC Uplink

Massive machine-type communication (mMTC) is one of the most rewarding and at the same time challenging components in the fifth-generation (5G) cellular solutions supporting the Internet of Things (IoT). The 5G mMTC is considering the use of a combination of two key mMTC enabling technologies-grant-free (GF) transmission and nonorthogonal multiple-access (NOMA), called GF-NOMA, which can potentially exploit the advantages of both schemes. A primary challenge in GF-NOMA is to reduce the packet drop rate. Owing to the decentralized nature of the GF schemes and the lack of control over user equipment, only hybrid automatic repeat request (HARQ) Type I has been employed for enhancing the reliability of GF-NOMA so far. In this article, uplink GF-NOMA transmission schemes using HARQ Type III are proposed. Two types of packet combining-1) chase combining and 2) incremental redundancy combining are considered. Moreover, we introduce a GF single-transmission (GFST) scheme where all redundancy versions of the packet are transmitted in one shot. We present a comprehensive evaluation of both the GF and the conventional grant-based methods in mMTC scenarios and demonstrate the superiority of our proposed methods over the existing ones.

Toward the Standardization of Grant-Free Operation and the Associated NOMA Strategies in 3GPP

The dramatic increase in Internet traffic to and from wireless devices poses significant challenges for network operators. While the current growth of traffic is mostly due to consumers communicating more frequently and larger amounts of data over the wireless infrastructure, much of the future growth is predicted to originate from non-human-operated devices or so-called IoT communication. The 3GPP standardization activities toward 5G cellular systems envisages two IoT-centric scenarios: mMTC and URLLC. In this article, we quantify the advantages of grant-free operation for 5G mMTC using latency, signaling overhead, and power consumption aspects. We propose the high-level design of a new grant-free state of operation and explain its interaction with the legacy LTE operating states. We also describe promising grantfree NOMA solutions with respect to synchronization and HARQ, and resource collision handling procedures. Our discussion and proposal relate closely to the current 5G standardization activities in 3GPP and highlight solutions that can easily be integrated into the current LTE framework.

Neighbor-aware multiple access protocol for 5G mMTC applications

To overcome the inter-carrier interference (ICI) of orthogonal frequency division multiplexing (OFDM) systems subject to unknown carrier frequency offset (CFO) and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis (ICA). Taking into account statistical independence of subcarriers' signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation (BSS) framework. In this paper, the ICA-based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.

Neighbor-aware multiple access protocol for 5G mMTC applications

To overcome the inter-carrier interference (ICI) of orthogonal frequency division multiplexing (OFDM) systems subject to unknown carrier frequency offset (CFO) and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis (ICA). Taking into account statistical independence of subcarriers' signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation (BSS) framework. In this paper, the ICA-based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique