A novel RACH mechanism for dense Cellular-IoT deployments

Dama, Sreekanth; Pasca, Thomas Valerrian; Sathya, Vanlin; Kuchi, Kiran

doi:10.1109/wcnc.2016.7564664

Cited by 6 publications

(10 citation statements)

References 6 publications

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“…On the other side cheap, fast, and portable computing devices with ubiquitous wireless connectivity [1,21,34] can revolutionize the personal computing [40] landscape by creating an opportunity to design an unprecedented array of new services and applications. Keeping the same philosophy in mind, we have focused mainly on maximizing the experienced data rate of an end-user by offering increased bandwidth through the coexistence of licensed wireless services (e.g., Long Term Evolution (LTE)) an unlicensed band [83,84,85,86].…”

Section: Macromentioning

confidence: 99%

Heterogenous Networks: From small cells to 5G NR-U

Sathya¹,

Kala²,

Narendran³

2021

Preprint

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With the exponential increase in mobile users, the mobile data demand has grown tremendously. To meet these demands, cellular operators are constantly innovating to enhance the capacity of cellular systems. Consequently, operators have been reusing the licensed spectrum "spatially," by deploying 4G/LTE small cells (e.g., Femto Cells) in the past. However, despite the use of small cells, licensed spectrum will be unable to meet the consistently rising data traffic because of data-intensive applications such as augmented reality/virtual reality (AR/VR) and on-the-go high-definition video streaming. Applications such AR/VR and online gaming not only place extreme data demands on the network, but are also latency-critical. To meet the QoS guarantees, cellular operators have begun leveraging the unlicensed spectrum by coexisting with Wi-Fi in the 5 GHz band. The standardizing body 3GPP, has prescribed cellular standards for fair unlicensed coexistence with Wi-Fi, namely LTE Licensed Assisted Access (LAA), New Radio in unlicensed (NR-U), and NR in Millimeter. The rapid roll-out of LAA deployments in developed nations like the US, offers an opportunity to study and analyze the performance of unlicensed coexistence networks through real-world ground truth. Thus, this paper presents a high-level overview of past, present, and future of the research in small cell and unlicensed coexistence communication technologies. It outlines the vision for future research work in the recently allocated unlicensed spectrum: The 6 GHz band, where the latest Wi-Fi standard, IEEE 802.11ax, will coexist with the latest cellular technology, 5G New Radio (NR) in unlicensed.

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Section: Macromentioning

confidence: 99%

Heterogenous Networks: From small cells to 5G NR-U

Sathya¹,

Kala²,

Narendran³

2021

Preprint

Self Cite

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“…where µ 1 New = (τ c + τ g )ε 1 New , ε 1 New is the new packets arrival rate of each device in the 1st time slot, f N 1 New (·) is the PMF of the number of new arrived packets N 1 New , P 1 is given in (7) of Theorem 1. In (19), (a) is the density of the accumulated packets in the 2nd time slot when a packet is successfully transmitted in the 1st time slot, and (b) is the density of the accumulated packets in the 2nd time slot when the congestion alleviation or the unsuccess transmission occurs in the 1st time slot.…”

Section: A Non-empty Probability T Mmentioning

confidence: 99%

“…According to Poisson approximation and (19), the CDF of the number of packets in the 2nd time slot due to previous accumulated packets N 2 Cum is approximated as…”

Section: A Non-empty Probability T Mmentioning

confidence: 99%

“…In [17], the authors developed a MAC-level model for the four-step RACH procedure to analyze and compare the baseline scheme and the dynamic back-off scheme. In [19], a novel Access Class Barring (ACB) scheme is proposed with a constant association rate. In [20], the authors devolop analytical models for the spatial-randomization ACB scheme and the time-spatial randomization, as well as compare them with the 3GPP specified eNodeB-employed time-randomization ACB scheme.…”

Section: Introductionmentioning

confidence: 99%

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

Jiang

Deng

Kang

et al. 2018

IEEE Trans. Commun.

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Massive Internet of Things (mIoT) has provided an auspicious opportunity to build powerful and ubiquitous connections that faces a plethora of new challenges, where cellular networks are potential solutions due to their high scalability, reliability, and efficiency. The Random Access CHannel (RACH) procedure is the first step of connection establishment between IoT devices and Base Stations (BSs) in the cellular-based mIoT network, where modeling the interactions between static properties of physical layer network and dynamic properties of queue evolving in each IoT device are challenging. To tackle this, we provide a novel traffic-aware spatio-temporal model to analyze RACH in cellular-based mIoT networks, where the physical layer network is modeled and analyzed based on stochastic geometry in the spatial domain, and the queue evolution is analyzed based on probability theory in the time domain.For performance evaluation, we derive the exact expressions for the preamble transmission success probabilities of a randomly chosen IoT device with different RACH schemes in each time slot, which offer insights into effectiveness of each RACH scheme. Our derived analytical results are verified by the realistic simulations capturing the evolution of packets in each IoT device. This mathematical model and analytical framework can be applied to evaluate the performance of other types of RACH schemes in the cellular-based networks by simply integrating its preamble transmission principle.

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“…It was explained in detail that the design rationale and some possible receiver algorithms for narrowband physical random access channel detection and time‐of‐arrival estimation were proposed. Dama et al proposed a novel access barring scheme that gives a constant association rate. These research studies are designed to solve the problem of massive device access but do not consider how to save energy under the nonfrequent data transmission system.…”

Section: Introductionmentioning

confidence: 99%

Energy‐efficient joint power control and resource allocation for cluster‐based NB‐IoT cellular networks

Zhu

Feng

et al. 2017

Trans Emerging Tel Tech

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As a new cellular technology introduced in 3rd Generation Partnership Project (3GPP) Release 13, Narrow‐band Internet of Things (NB‐IoT) provides wide‐area coverage for massive IoT devices. In the perspective of NB‐IoT business applications, it is easily known that energy efficiency is of utmost importance. In this paper, we propose an energy‐efficient joint resource allocation and power control for cluster‐based NB‐IoT cellular networks. The scheme mainly consists of 2 parts, ie, the formation of NB‐IoT device clusters and joint optimization of power and channel allocation. Firstly, by considering the geographical distribution density and the communication capability of NB‐IoT devices, we propose a fast cluster formation scheme to categorize a group of devices into multiple clusters. The cluster head is selected based on the strategy of maximal remaining battery energy due to its higher power consumption than that of clustered devices. Then, a joint optimization of resource and power is proposed for the maximization of energy efficiency of cluster‐based NB‐IoT cellular networks. Exploiting the properties of an objective function, we transform the original nonconvex optimization problem into equivalent 2‐step subproblems. In the first step, the optimal power allocation for any feasible channel reuse assignments is solved by finding the Nash equilibrium point based on noncooperative gaming. In the second step, the resource assignment problem is modeled as bipartite graphs matching and a Hungarian algorithm is used to obtain the perfect matching of channel reusing for maximal energy efficiency. Numerical results demonstrate the remarkable improvements in terms of energy efficiency and device access rate during a period by using the proposed scheme.

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A novel RACH mechanism for dense Cellular-IoT deployments

Cited by 6 publications

References 6 publications

Heterogenous Networks: From small cells to 5G NR-U

Heterogenous Networks: From small cells to 5G NR-U

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

Energy‐efficient joint power control and resource allocation for cluster‐based NB‐IoT cellular networks

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