Large Number Of Machine-type Communication Devices Research Articles

A Novel Cooperative NOMA Coding for Uplink MTC Networks

In this paper we consider machine-type communications (MTC) in 5G cellular networks for internet-of-thing (IoT) applications, where a large number of MTC devices simultaneously communicate with a base station (BS) over an uplink channel. To overcome the resource-constrained nature of the MTC nodes, we introduce a novel cooperative non-orthogonal multiple access (NOMA) coding scheme for supporting multi-user uplink transmissions with low complexity and signaling overhead, where the assumption of no feedback link hence no channel state information (CSI) available at the transmitting MTC nodes is taken. To gain deep understanding of its performance, we derive close-form analytical expressions on outage probability and diversity-multiplexing tradeoff (DMT) curve in the asymptotic regime of high signal-to-noise ratio (SNR), and optimize the end-to-end performance in terms of the exponential decay rate of expected distortion (ED). The asymptotic analytical result can be translated into a significant SNR gains of practical implementations with general SNR values, which is further confirmed via extensive simulation.

A Dynamic Backoff Window Scheme for Machine-Type Communications in Cyber-Physical Systems

A cyber-physical system (CPS) requires a time-bounded communication process for real-time interaction between the digital world and the physical world so that they can form a tight loop. Using the machine-type communication (MTC) protocol for a large-scale CPS is a good solution. However, the MTC protocol uses a random access (RA) mechanism to solve the radio resource contention problem, but that inevitably causes access delays especially in scenarios when there is a large number of MTC devices. To meet CPS requirement and address this problem, we propose a dynamic backoff window adjustment (DBA) algorithm for a pull-based RA process that can appropriately distribute the failed MTC devices engaged in the backoff window, so as to expedite their contention retrial time interval and achieve increased success probability. Simulation results showed that the DBA algorithm significantly increases the success probability of MTC devices contending for RA, and as well, shortens the mean access delay of the MTC devices. In comparison to the standard RA backoff scheme and a novel dynamic backoff (DB) scheme, the DBA algorithm proved to be more effective and suitable for the CPS to the best of our knowledge.

Throughput-Oriented Non-Orthogonal Random Access Scheme for Massive MTC Networks

Machine-type communications (MTC) technology, which enables direct communications among devices, plays an important role in realizing Internet-of-Things. However, a large number of MTC devices can cause severe collisions. As a result, the network throughput is decreased and the access delay is increased. To address this issue, a throughput-oriented non-orthogonal random access (NORA) scheme is proposed for massive machine-type communications (mMTC) networks. Specifically, by employing the technique of tagged preambles (PAs), multiple MTC devices (MTCDs) choosing the same PA can be distinguished and regarded as a non-orthogonal multiple access (NOMA) group, which enables multiple MTCDs to share the same physical uplink shared channel for transmissions by multiplexing in the power domain. The Sukhatme's classic theory and the characteristic function approach are adopted to formulate an optimization problem. The aim is to maximize the throughput subject to the constraints on the power back-off factor, the number of MTCDs included in a NOMA group, and the successful transmission probability. Based on the particle swarm optimization (PSO) algorithm, the formulated optimization problem is efficiently solved. The derived solution can be used to adjust the access class barring factor such that more MTCDs can obtain the access opportunities. Moreover, a low-complexity suboptimal solution is also developed, which can achieve near-PSO performance under high data rate requirement. Simulation results show that the proposed scheme can efficiently improve the network performance and comparison is made with the existing schemes.

Efficient Random Access Channel Evaluation and Load Estimation in LTE-A With Massive MTC

The deployment of machine-type communications (MTC) together with cellular networks has a great potential to create the ubiquitous Internet-of-Things environment. Nevertheless, the simultaneous activation of a large number of MTC devices (named UEs herein) is a situation difficult to manage at the evolved Node B (eNB). The knowledge of the joint probability distribution function (PDF) of the number of successful and collided access requests within a random access opportunity (RAO) is a crucial piece of information for contriving congestion control schemes. A closed-form expression and an efficient recursion to obtain this joint PDF are derived in this paper. Furthermore, we exploit this PDF to design estimators of the number of contending UEs in an RAO. Our numerical results validate the effectiveness of our recursive formulation and show that its computational cost is considerably lower than that of other related approaches. In addition, our estimators can be used by the eNBs to implement highly efficient congestion control methods.

Efficient Data Forwarding for Machine Type Communications in Internet of Things Networks

The MTC (Machine Type Communications) system is one of the most promising technologies to provide IoT (Internet of Things) applications. The MTC system suffers from congestion due to limited data transmission capacity and burst traffic. The congestion disturbs data delivery, results in an increase of energy consumption due to data retransmission, and finally poses a threat to the providers of IoT applications. In this paper, we focus on the congestion problem and present an efficient data forwarding mechanism to regulate the burst channel access from a large number of MTC devices. To regulate the communication channel access from the devices, we predict the number of devices by separating traffic load into the prediction of the number of devices that newly attempt to have access and the prediction of the number of devices that retry to access the channel. Through simulations, we show that our mechanism improves access success probability and reduces collision probability and access delay.

System-Level Analysis of IEEE 802.11ah Technology for Unsaturated MTC Traffic

Enabling the Internet of Things, machine-type communications (MTC) is a next big thing in wireless innovation. In this work, we concentrate on the attractive benefits offered by the emerging IEEE 802.11ah technology to support a large number of MTC devices with extended communication ranges. We begin with a comprehensive overview of the novel features introduced by the latest IEEE 802.11ah specifications followed by the development of a powerful mathematical framework capturing the essential properties of a massive MTC deployment with unsaturated traffic patterns. Further, we compare our analytical findings for a characteristic MTC scenario against respective system-level simulations across a number of important performance indicators. Our analytical results provide adequate performance predictions even when simulations are challenged by the excessive computational complexity. In addition, we study the novel IEEE 802.11ah mechanisms offering improved support for massive device populations and conclude on their expected performance.

Gateway-assisted two-stage radio access for machine type communication in LTE-Advanced network

In Long Term Evolution-Advanced (LTE-A) network, Machine Type Communication (MTC) provides random access-based communication for automation applications. One of the most critical issues in MTC is the emergence of large number of MTC devices which may send requests to the base station simultaneously, and incur severe collision at the base station. When collision occurs, the data delivery fails, and the message delay accumulates.In this paper, we propose a gateway-assisted two-stage (GATS) radio access scheme to alleviate collision for delay-tolerant MTC applications. In GATS, MTC devices are divided into several groups, where random access in each group (as the first stage) is controlled by a device called MTC gateway. Collision of random access to the base station (as the second stage) is then effectively alleviated. Then we propose analytical model and simulation model to investigate the performance of GATS in terms of utilization of random access slots, access success probability and average message delay. Simulation results show that, by sacrificing a little message delay, GATS scheme significantly improves access success probability. Besides, when the group number increases, the delay becomes smaller.

Timed strategic machine type communications for dual-level future wireless networks

For the next generation wireless networks, machine type communication (MTC) is gaining an enormous interest as a new communication paradigm. MTC is expected to become a cost-effective solution for improving the wireless communication performance. In MTC, one of the most critical issues is to support data transfers among devices without human interaction. In this study, we introduce a new MTC control scheme for the future network infrastructure. To effectively support a large number of MTC devices, we investigate a dual-level interaction mechanism by employing the timed strategy game model. In dynamic wireless network environments, our timed strategic game approach can practically adapt current system conditions while maximizing system performance. Main contribution of this research is to show a way of MTC system modeling based on the competitive and cooperative manner. Finally, numerical simulations illustrate the validity of our game-based approach. Our solution enables a better network resource utilization for heterogeneous traffic services in contrast to existing schemes.

Overload control in the network domain of LTE/LTE-A based machine type communications

It is expected that the LTE network, which includes the Radio Access Network (RAN) and the Core Network (CN) in 3GPP LTE systems, will be overloaded due to the huge number of Machine-Type Communication (MTC) devices in the near future. Overload in the RAN and CN of the LTE may result in congestion occurrence, resource waste, Quality of Service (QoS) degradation and in the worst-case, it will cause service unavailability. In this paper, we have proposed an adaptive mechanism to manage a large number of MTC devices in both RAN and CN of the LTE network. We use Access Class Barring (ACB) scheme to regulate the MTC traffic according to the congestions level in the RAN and CN. We consider a scenario in which two-priority-based classes of MTC devices are contending for the RAN resources. At first, the overload problem in the RAN is formulated to find the number of allowable contending MTC devices of each class taking into account their required QoS. Then, an active load management policy based on additive increase multiplicative decrease rule is proposed to control the incoming load from multiple cells to the CN. To effectively limit the number of MTC devices in both RAN and CN, in the proposed approach, each Evolved Node B updates the ACB factor upon overload detection in the RAN or CN in an adaptive manner. Simulation results show that the proposed mechanism is able to manage overload in the CN and RAN simultaneously.

Energy-Efficient Power and Time-Slot Allocation for Cellular-Enabled Machine Type Communications

Machine type communications (MTCs) over cellular networks pose significant challenges as a result of the large number of MTC devices (MTCDs), small and time controlled data transmissions, and rigorous energy limitation for small size MTCDs. This letter proposes an energy-efficient radio resource allocation (RRA) scheme for cellular-enabled MTCs, where user equipment (UEs) [used for human type communications (HTCs)] are configured as gateways for MTCs. On condition that the latency constraints for MTCs and HTCs are satisfied, our objectives are to minimize the total energy consumption of MTCDs and prolong network lifetime. Comparing with other RRA schemes, simulation results show that the proposed RRA scheme can achieve higher energy-efficiency and, therefore, extend network lifetime in LTE-A cellular networks.

Joint Access Control and Resource Allocation for Concurrent and Massive Access of M2M Devices

Machine-to-machine (M2M) communications, also known as machine-type communications (MTC) in 3GPP LTE systems, provide autonomous connectivity between machines without human intervention to create new service, e.g., the Internet of Things and the smart grid. M2M communications normally involve a large number of MTC devices (MTCDs) to support a variety of sensor applications. Consequently, concurrent and massive access attempts of MTCDs to radio access networks (RANs) may cause intolerable delay, packet loss, and even service unavailability. In this paper, we propose a joint optimal physical random access channel (PRACH) resource allocation and access control mechanism to address the performance degradation caused by concurrent and massive access attempts of MTCDs in LTE systems. We define the notion of random access efficiency and formulate an optimization problem for maximization of the random access efficiency with random access delay constraint. We also propose a dynamic resource allocation and access control algorithm based on estimation of the number of MTCDs for a system with dynamically varying numbers of massive MTCDs. Then, an analytical model is provided using a discrete-time Markov chain for the proposed mechanism. The effectiveness of the proposed algorithm is demonstrated via analysis and simulations. The proposed algorithm was able to maintain the optimal random access efficiency while satisfying the average random access delay requirement of MTCDs to handle massive and dynamic MTCDs per cell.

Dynamic Allocation of Random Access Opportunity for Machine-Type Communication in LTE-Advanced

With the rapid growth of machine-type communications (MTC) devices, the radio access network (RAN) will be overloaded when a large number of MTC devices try to access the radio networks in a short time. In this paper, a combination of a dynamic resource allocation and a random access check mechanism is proposed to solve the overload problems for MTC in LTE-Advanced. An analytical model is presented with the derivation of three metrics, the collision probability, the success probability, and the idle probability to evaluate the method. Simulation and analysis results show the superior performance of the method we proposed to solve the RAN overload problem.

Medium access control techniques in M2M communication: survey and critical review

AbstractMachine‐to‐machine (M2M) communication has received increasing attention in recent year. An M2M network exhibits some salient features such as large number of machines/devices, low data rates, delay tolerant/sensitive, small packets, energy constrained and low or no mobility. A large number of M2M terminals may exist in a small area with many trying to simultaneously and randomly access for channel resources, which will result in overload and access problem. This increased signalling overhead and diverse requirements of machine‐type communication (MTC) devices call for the development of flexible and efficient scheduling and random access techniques. In an M2M scenario, where the network is operating at high offered load with a large number of contending transmitters, distributed random access techniques are more appropriate than centralised scheduling techniques because of less control messages and better channel utilisation. There is a need for comparison of various medium access methods that can be used in the development of an efficient hybrid M2M and human to human network. In this article, we review and compare various scheduling and random access techniques in cellular networks, particularly in Long‐Term Evolution. We also discuss how successful they are to fulfill the unique requirements of M2M communication and networking. Resource management in M2M networks with a large number of MTC devices is also discussed from the access point of view. Energy efficiency, being one of the main challenges of quality‐of‐service‐constrained M2M communication, is also discussed. Minimisation of the energy consumption is tightly bound to channel access and hence considered in the comparison of various medium access control protocols. Finally, some potential research directions related to access control and resource allocation are presented for future work. Copyright © 2014 John Wiley & Sons, Ltd.