Modeling and Analysis of Random Access Channels With Bursty Arrivals in OFDMA Wireless Networks

Wei, Chia-Hung; Bianchi, Giuseppe; Cheng, Ray-Guang

doi:10.1109/twc.2014.2377121

Cited by 99 publications

(105 citation statements)

References 12 publications

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“…As analyzed in other studies [5,6,8,12] (or, the conventional case in shown Figure 6), the RA throughput is maximized when the number of accesses is same as the preamble size, i.e., n = V. However, if the Msg3 PR is used, the number of throughput-maximizing arrivals increases significantly. This result further demonstrates that, because of the capture effect on the RA procedure, optimization is needed if diverse RACH congestion-control schemes, such as ACB or M2M-specific back-off, are used.…”

Section: The Consequences Of the Capture Effect And Its Propertiesmentioning

confidence: 72%

“…We formulated analysis models of the RA procedure considering the capture effect. Previous studies [4][5][6][12][13][14] adopted the collision model to analyze the RA procedure and assumed that the RA performance degradation due to the collisions of the preambles (Msg 1) could not be prevented. However, we provide an RA analysis model that considers the capture effect.…”

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confidence: 99%

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

Kim

Lee

2017

Preprint

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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 a 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 scheme through simulation result.

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Section: The Consequences Of the Capture Effect And Its Propertiesmentioning

confidence: 72%

mentioning

confidence: 99%

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

Kim

Lee

2017

Preprint

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“…The assumption that business models follow homogeneous Poisson or Bernoulli process is difficult to extend to application scenes of NBIoT. In combination with 3GPP beta type business model, approximate form of PDF for random access latency, is given in [34] by estimating the maximum retransmission times for terminals with successful access through mean value of latency. In [35], the lower bound for random access latency is deduced through approximate beta distribution of piecewise linear function, but the effect of maximum retransmission times is not taken into consideration.…”

Section: Related Workmentioning

confidence: 99%

RADB: Random Access with Differentiated Barring for Latency‐Constrained Applications in NB‐IoT Network

Miao

Tian

Cheng

et al. 2018

Wireless Communications and Mobile Computing

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With the development of LPWA (Low Power Wide Area) technology, the emerging NB-IoT (Narrowband Internet of Things) technology is becoming popular with wide area and low-data-rate services. In order to achieve objectives such as huge amount of connection and wide area coverage within NB-IoT, the problem of network congestion generated by random access of numerous devices should be solved. In this paper, we first introduce the background of NB-IoT and investigate the research on random access optimization algorithm. Then we summarize relevant features of NB-IoT uplink and narrowband physical random access channel and design random access with differentiated barring (RADB), which can improve the insufficiency of traditional dynamic access class barring method. At last, the algorithms proposed in this paper are realized with established NB-IoT model using OPNET Modeler platform, and simulations are conducted. The simulation results show that RADB is able to effectively solve preamble request conflict generated by random access of numerous devices and preferentially provide efficient and reliable random access for latency-sensitive devices.

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“…In this section, we describe our model for sLTE-U connection establishment, which is based on the works of Bianchi [18] and Wei et. al [19]. In III-A, we explain the Markov chain model for the Wi-Fi/sLTE-U contention, and in III-B, we outline the performance model of preamble contention on RACH.…”

Section: System Modelmentioning

confidence: 99%

“…To analyze the performance of preamble contention, we apply a simplified drift approximation model proposed by Wei et al [19]. We consider discrete time divided into PRACH slots.…”

Section: Preamble Contention Modelmentioning

confidence: 99%

On Random Access Channel Performance and M2M Support in Standalone LTE Unlicensed

Schrader¹,

Vilgelm

Kellerer

2017

GLOBECOM 2017 - 2017 IEEE Global Communications Conference

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Abstract-Next generation telecommunication systems are required to efficiently support orders of magnitude larger amount of devices per cell than the current LTE networks. This requirement is causing major design challenges for the Random Access Channel (RACH), especially for Machine-to-Machine (M2M) applications. On the other hand, due to the increasing spectrum demands, LTE vendors are exploring unlicensed spectrum. For example, MulteFire has been recently standardized as an LTEbased technology for standalone deployment in unlicensed 5GHz frequency bands. It is reasonable to expect that the coexistence with Wi-Fi and standalone LTE in the unlicensed spectrum, will amplify Random Access problem and worsen RACH performance. Henceforth, in this paper, we quantify the Wi-Fi-LTE coexistence and its impact on the RACH performance. We consider a synchronized activation of a large amount of UEs in an MulteFire/LTE unlicensed cell, and analyze the time it takes to connect all of them to the base station. Our results confirm that the presence of Wi-Fi substantially degrades RACH performance, with an increase of almost 50% per additional Wi-Fi station. Furthermore, we illustrate applications of our evaluation for RACH resource dimensioning and network planning.

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Modeling and Analysis of Random Access Channels With Bursty Arrivals in OFDMA Wireless Networks

Cited by 99 publications

References 12 publications

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

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

RADB: Random Access with Differentiated Barring for Latency‐Constrained Applications in NB‐IoT Network

On Random Access Channel Performance and M2M Support in Standalone LTE Unlicensed

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