Random Access Analysis for Massive IoT Networks Under a New Spatio-Temporal Model: A Stochastic Geometry Approach

Jiang, Nan; Deng, Yansha; Kang, Xin; Nallanathan, Arumugam

doi:10.1109/tcomm.2018.2854275

Cited by 92 publications

(88 citation statements)

References 38 publications

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“…Thus, SWIPT from a multiantenna TX has increased potential in providing continuous replenishment of the drained energy. However, novel low complexity designs are needed to optimize the harvested power fairness among IoT nodes, while meeting their Quality of Service (QoS) demands [19], [20].…”

Section: Introductionmentioning

confidence: 99%

Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting

Mishra

Alexandropoulos

2018

IEEE Internet Things J.

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Enabling technologies for energy sustainable Internet of Things (IoT) are of paramount importance since the proliferation of high data communication demands of low power network devices. In this paper, we consider a Multiple Input Single Output (MISO) multicasting IoT system comprising of a multiantenna Transmitter (TX) simultaneously transferring information and power to low power and data hungry IoT Receivers (RXs). Each IoT device is assumed to be equipped with Power Splitting (PS) hardware that enables Energy Harvesting (EH) and imposes an individual Quality of Service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO Simultaneous Wireless Information and Power Transfer (SWIPT) multicasting IoT system with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic Radio Frequency (RF) EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent semi-definite relaxation formulation and then prove it possesses unique global optimality. We also derive tight upper and lower bounds on the globally optimal solution that are exploited in obtaining low complexity algorithmic implementations for the targeted joint design. Analytical expressions for the optimal TX beamforming directions, power allocation, and IoT PS ratios are also presented. Our representative numerical results including comparisons with benchmark designs corroborate the usefulness of proposed framework and provide useful insights on the interplay of critical system parameters.

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Section: Introductionmentioning

confidence: 99%

Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting

Mishra

Alexandropoulos

2018

IEEE Internet Things J.

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“…The work in [23] addresses downlink scheduling, which does not involve an RA-SR phase because the BS encloses the data queue and is responsible for scheduling. The work in [24], [25] analyzes the Random Access CHannel (RACH) performance in cellular-based IoT networks which does not involve EA-Tx phase for data transmission. The UL scenario where the data queue is at the device side is considered in [26].…”

Section: A Related Workmentioning

confidence: 99%

Spatiotemporal Model for Uplink IoT Traffic: Scheduling and Random Access Paradox

Gharbieh

ElSawy

Yang

et al. 2018

IEEE Trans. Wireless Commun.

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The Internet-of-things (IoT) is the paradigm where anything will be connected. There are two main approaches to handle the surge in the uplink (UL) traffic the IoT is expected to generate, namely, Scheduled UL (SC-UL) and random access uplink (RA-UL) transmissions. SC-UL is perceived as a viable tool to control Quality-of-Service (QoS) levels while entailing some overhead in the scheduling request prior to any UL transmission. On the other hand, RA-UL is a simple single-phase transmission strategy. While this obviously eliminates scheduling overheads, very little is known about how scalable RA-UL is. At this critical junction, there is a dire need to analyze the scalability of these two paradigms.To that end, this paper develops a spatiotemporal mathematical framework to analyze and assess the performance of SC-UL and RA-UL. The developed paradigm jointly utilizes stochastic geometry and queueing theory. Based on such a framework, we show that the answer to the "scheduling vs. random access paradox" actually depends on the operational scenario. Particularly, RA-UL scheme offers low access delays but suffers from limited scalability, i.e., cannot support a large number of IoT devices.On the other hand, SC-UL transmission is better suited for higher device intensities and traffic rates.

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“…In our previous work [21], we provided a novel spatiotemporal mathematical framework to analyze the preamble tranmission success probability of mIoT network, where the queue evolution of IoT devices is modelled via probability theory (i.e., a new approach is developed to track the queue evolution, which is different from [19,20]), and the SINR outage of preamble transmission is studied using stochastic geometry. Due to the page limitation, we only focused on deriving the preamble transmission success probability as the first work in analyzing RA procedure using stochastic geometry and probability theory, and left the collision problem as the future work.…”

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confidence: 99%

“…Due to the page limitation, we only focused on deriving the preamble transmission success probability as the first work in analyzing RA procedure using stochastic geometry and probability theory, and left the collision problem as the future work. In this work, different from [19][20][21], we take into account the SINR outage events as well as the collision events at the BS in evaluating the success RA. The contributions of this paper can be summarized in the following:…”

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confidence: 99%

“…• We extendedly study the ACB and back-off BO schemes analyzed in our previous work [21] by taking into account collision, and we also analyze two hybrid schemes, namely, the hybrid ACB and back-off (ACB&BO) scheme, and the hybrid power ramping and back-off (PR&BO) scheme. We derive the exact expressions for the RA success probability in each time slot with these schemes, and our results show that the PR&BO scheme outperforms all other schemes in all traffic scenarios.…”

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confidence: 99%

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Analyzing Random Access Collisions in Massive IoT Networks

Jiang

Deng

Nallanathan

et al. 2018

IEEE Trans. Wireless Commun.

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This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see Abstract-The cellular-based infrastructure is regarded as one of potential solutions for massive Internet of Things (mIoT), where the Random Access (RA) procedure is used for requesting channel resources in the uplink data transmission. Due to the nature of mIoT network with the sporadic uplink transmissions of a large amount of IoT devices, massive concurrent channel resource requests lead to a high probability of RA failure. To relieve the congestion during the RA in mIoT networks, we model RA procedure, and analyze as well as evaluate the performance improvement due to different RA schemes, including power ramping (PR), back-off (BO), access class barring (ACB), hybrid ACB and back-off schemes (ACB&BO), and hybrid power ramping and back-off (PR&BO). To do so, we develop a traffic-aware spatio-temporal model for the contention-based RA analysis in the mIoT network, where the signal-to-noiseplus-interference ratio (SINR) outage and collision events jointly determine the traffic evolution and the RA success probability. Compared with existing literature only modelled collision from single cell perspective, we model both SINR outage and the collision from the network perspective. Based on this analytical model, we derive the analytical expression for the RA success probabilities to show the effectiveness of different RA schemes. We also derive the average queue lengths and the average waiting delays of each RA scheme to evaluate the packets accumulation status and packets serving efficiency. Our results show that our proposed PR&BO scheme outperforms other schemes in heavy traffic scenario in terms of the RA success probability, the average queue length, and the average waiting delay.

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Random Access Analysis for Massive IoT Networks Under a New Spatio-Temporal Model: A Stochastic Geometry Approach

Cited by 92 publications

References 38 publications

Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting

Energy Sustainable IoT With Individual QoS Constraints Through MISO SWIPT Multicasting

Spatiotemporal Model for Uplink IoT Traffic: Scheduling and Random Access Paradox

Analyzing Random Access Collisions in Massive IoT Networks

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