Random Access Procedure Research Articles

Collision-Aware Resource Access Scheme for LTE-Based Machine-to-Machine Communications

Long-term evolution (LTE) network is considered as the most promising infrastructure to provide efficient connectivity for a large number of autonomous machine-type communications devices (MTCDs). In order to improve the random access (RA) throughput of massive access machine-to-machine (M2M) communications over LTE networks, we propose a collision-aware resource access (CARA) scheme to reduce the collisions on the granted physical resource blocks (PRBs). In CARA, the evolved Node B exploits early collision detection of preambles at the first message and informs the MTCDs in the corresponding random access response (RAR) message if it can detect the collision successfully. The collided MTCDs then contend for PRBs access using an appropriate probability for efficient use of granted PRBs. Analytical and numerical performance evaluations of the CARA show that the RA throughput can be improved in comparison with the traditional RA procedure.

A Group-Based Massive Multiple Access Scheme in Cellular M2M Networks

With the rapid development of machine-to-machine (M2M) applications, there is an explosion in the number of M2M devices emerging in the network. It poses a significant challenge for the network to support random access requests of a huge number of M2M devices. In this paper, we propose a novel group-based random access scheme for cellular M2M communications, where the beamforming technology enhanced by massive multiple-input multiple-output (MIMO) is applied. The key idea of the proposed scheme is that the evolved Node-B (eNB) makes use of multiple beams to divide M2M devices into different groups. Benefited from the spatial selectivity of beams, the interference among different groups is limited, which can efficiently reduce collisions during the random access procedure. Numerical results demonstrate that our proposed group-based random access scheme has the higher access success probability of devices compared with the legacy random access scheme.

Time-division random-access scheme based on coverage level for cellular internet-of-things in 3GPP networks

Cellular internet-of-things (CIoT) systems are recently developed by the third-generation partnership project (3GPP) to support internet-of-things (IoT) services over the conventional mobile-communication infrastructures. The CIoT systems allow a large number of IoT devices to be connected through the random-access procedure, but the concurrent accesses of the massive devices make this procedure heavily competitive. In this article, we present an effective time-division random-access scheme built upon the coverage levels (CLs), where each CIoT device is assigned a CL and categorized based on its radio-channel quality. In our scheme, the random-access loads of device groups having different CLs are distributed into different time periods, which greatly relaxes instantaneous contention and improves random-access performance. To assess the performance of our scheme, we also introduce a mathematical model that expresses and analyzes the states and behaviors of CIoT devices using the Markov chain. Mathematical analysis and simulation results show that our scheme significantly outperforms the conventional scheme (without time-division control) in terms of collision probability, succeeding access rate, and access-blocking probability.

Enhancement of MTC Performance in LTE Networks by Maximizing Random Access Procedure Throughput

Enhancement of MTC Performance in LTE Networks by Maximizing Random Access Procedure Throughput

Modeling of Distributed Queueing-Based Random Access for Machine Type Communications in Mobile Networks

Machine type communications (MTC) devices stay in idle mode to save energy and should perform random access (RA) procedure to obtain radio resources for data transmission. The RA procedure introduces access delay and extra power consumption for the MTC devices. Thus, RA needs to be optimized. In this letter, we develop low complexity analytical models to rapidly estimate maximum access delay and average number of preamble transmissions for distributed queueing-based random access (DQRA) protocol, which improves the performance of standard RA for MTC in LTE. The proposed model can be used to analyze the performance of group paging using DQRA. The performance analysis shows that the proposed analytical models accurately match the simulation results.

Performance Analysis of a Novel Hybrid S-ALOHA/TDMA Protocol for Beta Distributed Massive MTC Access.

Simultaneous random access of massive machine type communications (MTC) devices are expected to cause congestion in the radio access network. Not only the performance of MTC, but the coexisting human to human (H2H) communications would also degrade dramatically without an appropriate medium access control (MAC) protocol. However, most existing solutions focus on the random access procedure without dealing with the sunsequent data transmission procedure. In this paper, we firstly derive a packet size threshold based on the capacity analysis of slotted ALOHA (S-ALOHA) and time division multiple access (TDMA) protocols. Then a novel hybrid S-ALOHA/TDMA MAC protocol (HSTMAC) is presented for massive MTC access, in which the resources are separated for beta distributed machine to machine (M2M) traffic with small size packets and high priority H2H traffic with large size packets. Considering access class barring (ACB) scheme as an overload control method, the system equilibrium under arbitrary retransmission limit is analyzed rigorously, which can provide insights on quality of service (QoS) guarantee. Finally, a dynamic pre-backoff (DPBO) algorithm is designed for load balance by adaptively scattering the highly synchronized M2M traffic over the transmission interval. Numerical and simulation results validate our analysis and show that the HSTMAC protocol is superior to pure S-ALOHA protocol and pure TDMA protocol. The proposed DPBO algorithm can achieve a higher success probability and resource utilization ratio with a much reduced average delay than that of uniform pre-backoff (UPBO) scheme.

On the Accurate Performance Evaluation of the LTE-A Random Access Procedure and the Access Class Barring Scheme

The performance evaluation of the random access (RA) in LTE-A has recently become a major research topic as these networks are expected to play a major role in future 5G networks. Up to now, the key performance indicators (KPIs) of the RA in LTE-A have been obtained either by performing a large number of simulations or by means of analytic models that, oftentimes, sacrifice precision in exchange for simplicity. In this paper, we present an analytical model for the performance evaluation of the LTE-A RA procedure that incorporates the access class barring (ACB) scheme. By means of this model, each and every one of the KPIs suggested by the 3GPP can be obtained with minimal error when compared with results obtained by simulation. To the best of our knowledge, this paper presents the most accurate analytical model, which can be easily adapted to incorporate modifications of network parameters and/or extensions to the LTE-A system. In addition, our model of the ACB scheme can be easily incorporated to other analytic models of similar nature without further modifications.

Formal verification of a radio network random access protocol

SummaryIn this paper, the random access procedure of Universal Mobile Telecommunications System network is investigated. We have proposed a model based on communicating timed automata that represents the main functions related to the random access procedure including the user equipment, the base station (node B or BTS), and the channel. Then, we have used computational tree logic formula to specify the proprieties to be verified. The model and the formulas serve as inputs to the model checker, which is used as a verification engine, ie, UPPAAL and SPIN. The formal verification approach shows that the protocol has several drawbacks that may not be detected by simulation.

Exploiting the Capture Effect to Enhance RACH Performance in Cellular-Based M2M Communications.

Cellular-based machine-to-machine (M2M) communication is expected to facilitate services for the Internet of Things (IoT). However, because cellular networks are designed for human users, they have some limitations. Random access channel (RACH) congestion caused by massive access from M2M devices is one of the biggest factors hindering cellular-based M2M services because the RACH congestion causes random access (RA) throughput degradation and connection failures to the devices. In this paper, we show the possibility exploiting the capture effects, which have been known to have a positive impact on the wireless network system, on RA procedure for improving the RA performance of M2M devices. For this purpose, we analyze an RA procedure using a capture model. Through this analysis, we examine the effects of capture on RA performance and propose an Msg3 power-ramping (Msg3 PR) scheme to increase the capture probability (thereby increasing the RA success probability) even when severe RACH congestion problem occurs. The proposed analysis models are validated using simulations. The results show that the proposed scheme, with proper parameters, further improves the RA throughput and reduces the connection failure probability, by slightly increasing the energy consumption. Finally, we demonstrate the effects of coexistence with other RA-related schemes through simulation results.

Recursive Pseudo-Bayesian Access Class Barring for M2M Communications in LTE Systems

Commercial long-term evolution (LTE) systems adopt an access class barring (ACB) mechanism in the initial random access procedure with multiple preambles in order to accommodate bursty traffic arrivals of machine-type communications. In this paper, we propose two Bayesian ACB algorithms that estimate the number of active machine devices based only on the number of idle preambles in each slot. In the commercial LTE systems, eNodeB cannot instantaneously distinguish if a particular preamble is sent from a single device (i.e., success) or multiple devices (i.e., collision). However, the idle preambles can be instantaneously detected at the base station (BS) in each slot. Numerical results show that the proposed algorithms yield quite similar performance with the ideal ACB algorithm, assuming that the exact number of active devices is known to the eNodeB.

An Early Preamble Collision Detection Scheme Based on Tagged Preambles for Cellular M2M Random Access

In this paper, we propose an early preamble collision detection (e-PACD) scheme at the first step of random access (RA) procedure based on tagged preambles (PAs), which consist of both PA and tag Zadoff–Chu sequences using different root numbers, respectively. The proposed e-PACD scheme enables faster PA collision detection and notification, compared with the conventional RA scheme. Accordingly, it can reduce the RA delay and remove resource wastes which occur at the third step of the conventional RA procedure. The reduced RA delay achieved by the proposed e-PACD scheme can contribute to an ultralow latency requirement in fifth-generation (5G) cellular networks. In addition, the proposed e-PACD scheme enables the eNodeB to monitor the number of RA-attempting nodes (RA load) on each physical RA channel slot. The PACD probability and the RA load monitoring accuracy are mathematically analyzed, and the RA performance enhancement of the proposed scheme is evaluated in terms of RA success probability, average RA delay, and RA resource efficiency, compared with the conventional RA scheme.

Smoothing the Drive: Critical Access for Intelligent Transportation Systems

Long-term evolution (LTE)-based vehicular-to-everything (V2X) service is one of the promising technologies for supporting intelligent transportation systems (ITSs). LTE adopts a request-grant approach for allocating wireless resources. Each user follows a contention-based random access (RA) procedure to transmit its request. However, this procedure may result in unbounded delay if too many users compete for limited RA resources. Therefore, prioritized critical access in the LTE RA procedure is required to differentiate critical V2X services from noncritical ones.

The Random Access Procedure in Long Term Evolution Networks for the Internet of Things

Network connectivity is a key issue in the realization of IoT, and LTE cellular technology is the most promising option for the provisioning of such connectivity. However, in LTE networks, a large number of IoT devices trying to access the medium can overload the RAN. In this article, we review the LTE random access procedure and its support for IoT applications. We also assess the performance of the RAN overload control schemes proposed by 3GPP, taking into consideration the interaction between the random access procedure and packet downlink control channel resource allocation.

First Mile Challenges for Large-Scale IoT

The Internet of Things is large-scale by nature. This is not only manifested by the large number of connected devices, but also by the sheer scale of spatial traffic intensity that must be accommodated, primarily in the uplink direction. To that end, cellular networks are indeed a strong first mile candidate to accommodate the data tsunami to be generated by the IoT. However, IoT devices are required in the cellular paradigm to undergo random access procedures as a precursor to resource allocation. Such procedures impose a major bottleneck that hinders cellular networks' ability to support large-scale IoT. In this article, we shed light on the random access dilemma and present a case study based on experimental data as well as system-level simulations. Accordingly, a case is built for the latent need to revisit random access procedures. A call for action is motivated by listing a few potential remedies and recommendations.

A Non-Orthogonal Resource Allocation Scheme in Spatial Group Based Random Access for Cellular M2M Communications

Cellular machine-to-machine (M2M) communication can be one of the major candidate technologies to develop an Internet of Things (IoT) platform. A massive number of machine nodes access the cellular networks and typically send/receive small-sized data. In this situation, severe random access (RA) overload and radio resource shortage problems may occur if there is no evolution in the conventional cellular system. Focusing on RA, we need a larger number of preambles, as well as a more efficient resource allocation scheme in order to accommodate a significantly large number of RA requests from machine nodes. In this paper, we propose a non-orthogonal resource allocation (NORA) scheme, combined with our spatial group based RA (SGRA) mechanism, in order to provide a sufficiently large number of preambles at the first step of the RA procedure and non-orthogonally allocate physical uplink shared channel resources at the second step of the RA procedure. As a result, the proposed SGRA-NORA scheme can significantly increase the RA success probability, compared with that of the conventional RA scheme.

A multiple power level random access method for M2M communications in LTE‐A network

AbstractAccess control is an effective way to protect the radio access part of Long‐Term Evolution–Advanced (LTE‐A) network from the overload caused by a huge number of Machine‐Type Communication Devices (MTCDs). A class of access control mechanisms is the Access Class Barring (ACB), which regulates the Machine‐to‐Machine (M2M) traffic in accordance with the available Random Access (RA) resources. In this paper, we extend the single power level ACB scheme to a multiple power level method to increase the number of successfully transmitted requests in the case of overload. Our analysis is based on the capture effect in the third step of RA procedure of the LTE‐A system in which one of the transmitted requests by 2 or more co‐tagged MTCDs, MTCDs which use the same preamble in the first step, can be decoded by the evolved–Node B (eNB). We first formulate the power level selection as an optimization problem assuming the perfect capture model without considering MTCDs' energy budget. Then, to take into account MTCDs' energy consumption, the scenario is extended for the signal‐to‐interference ratio–based capture model. In addition, we investigate the advantages of the proposed multiple power level RA method on discriminating the access of MTCDs with different priorities. The numerical results show that using the optimal parameters, the RA throughput can be improved in comparison with the single power level system at the cost of slightly increasing MTCDs' energy consumption and the complexity of RA procedure.

Investigation on random access in a VLC system with multipacket reception in the presence of hidden devices and obstructions

Due to the directionality of light, the hidden device problem and the obstruction cannot be ignored for carrier sense multiple access with collision avoidance (CSMA/CA)-based uplink visible light communication (VLC). In this paper, we introduce multipacket reception (MPR) to handle the hidden device problem in VLC system. We model the traffic of the device with on/off Markov source. With the unsaturated traffic, we formulate a two dimensional (2D) Markov chain to model the CSMA/CA-based slotted random access procedure to evaluate the effects of hidden devices and obstructions on the performance of MPR-aided VLC system, which are mapped into the transition probabilities of the Markov chain. Then, we analyze the throughput and the reception power efficiency (RE) of MPR-aided VLC system with the obstructed optical channel. Numerical results show that the effect is negative when hidden devices or obstructions appear solely. But when they appear simultaneously, they will interact with each other to mitigate the negative effects.

Performance of Dynamic Access Class Barring Method in Cellular M2M Networks

Cellular based machine-to-machine (M2M) systems generate massive number of access requests which create congestion in the cellular network. The contention-based random access procedures are designed for cellular networks which cannot accommodate a large number of M2M traffic. In this paper, a contention-based slotted Aloha random access procedure for M2M network is first analyzed using different performance metrics. The impact of massive M2M traffic over cellular traffic is studied based on different arrival rate, random access opportunity and throughput. Then, an analytical model of selecting a base station (eNB) along with load balancing is developed. Finally, a dynamic access class barring method and RAN level congestion control mechanism by selecting the appropriate eNB is presented and evaluated with M2M traffic. Numerical results show that frame transmission rate influences the selection probability of the base stations. Moreover, the dynamic access class barring parameter along with frame transmission rate improve the overall throughput and access success probability among base stations as well as avoid overload situation in a particular base station.

Uplink access control for machine-type communications in LTE-A networks

Internet of things (IoT) has been considered as one of the most promising technologies over the next decade. One of the basic requirements of IoT is the global communication connectivity between smart objects. LTE-A has been considered as the main communication channel for connecting devices. For this reason, the machine-type communication (MTC) has been defined in the 3GPP LTE-A specification. With the rapid growth of the IoT devices, MTC in LTE-A faces many challenges. The primary design of a LTE-A network is to support the human-type communication (HTC). However, MTC and HTC have different characteristics, such as packet size, traffic arrival rate, and delay tolerance. How to accommodate a large amount of MTC traffic without affecting the grade of service of the HTC is challenging. More specifically, before accessing the LTE-A network, a random access (RA) procedure needs to be performed by a device to synchronize in the uplink of an eNB. Since the number of MTC devices is expected to be much greater than the HTC devices, without suitable access control, the success rate of the RA requests from the HTC devices can be significantly degraded. Therefore, this research aims to design an appropriate RA procedure to relieve this problem. The authors propose an Adaptive RACH Resource Allocation (ARRA) which integrates several control schemes, including a Resource Allocation scheme, an Access Class Barring scheme, and a Priority Device Setting scheme. Simulation results show that the proposed ARRA is able to achieve a higher access success rate and a lower latency for HTC devices while providing a different quality of service to different types of MTC devices.

IoT 서비스를 위한 LTE-A 랜덤 액세스 절차 성능 평가

IoT 서비스를 위한 LTE-A 랜덤 액세스 절차 성능 평가