A random-access algorithm based on statistics waiting in LTE-M system

Zhao, Yifeng; Yang, Huayu; Li, Kai; Huang, Lianfen; Shi, M.; Zhang, Meng

doi:10.1109/iccse.2017.8085491

Cited by 4 publications

(5 citation statements)

References 8 publications

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“…Resource Allocation techniques. An enhanced random access algorithm was introduced in [150], in order to reduce the power consumption of devices. LTE-M defines two access modes:…”

Section: Drxshortcycletimermentioning

confidence: 99%

“…Sleep/wake-up techniques [149] Resource Allocation techniques [150] Sleep/wake-up techniques [151] Sleep/wake-up techniques [152][153][154][155][156][157] Data Reduction techniques [158] Network techniques [159] Resource Allocation techniques [160,161] Figure 8. Energy efficiency techniques for cIoT technologies [149][150][151][152][153][154][155][156][157][158][159][160][161].…”

Section: Ciot Lte-m Ec-gsm-iot Nb-iotmentioning

confidence: 99%

“…The contention-based random access procedure presented in [150] is based on timeslotted ALOHA. The energy consumption is divided into three parts: receiving and sending (non-sleep) and sleep energy consumption.…”

mentioning

confidence: 99%

“…If there is a data frame that arrives at a time slot, it can be retransmitted only at the beginning of the next time slot. The scheme proposed in [150] is based on the principle that when a new slot arrives, the device that has initiated the access will receive a broadcast signal, containing the success rate of the last time slot. If the last time slot access has a low success, the device selects another access slot that has a higher success probability.…”

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confidence: 99%

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Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

et al. 2021

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In the last years, the Internet of Things (IoT) has emerged as a key application context in the design and evolution of technologies in the transition toward a 5G ecosystem. More and more IoT technologies have entered the market and represent important enablers in the deployment of networks of interconnected devices. As network and spatial device densities grow, energy efficiency and consumption are becoming an important aspect in analyzing the performance and suitability of different technologies. In this framework, this survey presents an extensive review of IoT technologies, including both Low-Power Short-Area Networks (LPSANs) and Low-Power Wide-Area Networks (LPWANs), from the perspective of energy efficiency and power consumption. Existing consumption models and energy efficiency mechanisms are categorized, analyzed and discussed, in order to highlight the main trends proposed in literature and standards toward achieving energy-efficient IoT networks. Current limitations and open challenges are also discussed, aiming at highlighting new possible research directions.

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“…Resource Allocation techniques. An enhanced random access algorithm was introduced in [150], in order to reduce the power consumption of devices. LTE-M defines two access modes:…”

Section: Drxshortcycletimermentioning

confidence: 99%

Section: Ciot Lte-m Ec-gsm-iot Nb-iotmentioning

confidence: 99%

mentioning

confidence: 99%

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confidence: 99%

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Energy Efficiency in Short and Wide-Area IoT Technologies—A Survey

et al. 2021

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“…In few previous studies, 17,18 a series of effective methods for network congestion and overload are also summarized and analyzed, like the typical access class barring (ACB), evolved access barring (EAB), back-off scheme, and resource separation scheme (RSS). Zhao et al 19 proposed a random-access algorithm based on statistics waiting for energy saving. In addition, few authors [20][21][22] designed and analyzed the distributed queuing-based random-access (DQRA) protocol.…”

Section: Related Workmentioning

confidence: 99%

Autonomous and adaptive congestion control for machine-type communication in cellular network

Pan

Wen

et al. 2019

International Journal of Distributed Sensor Networks

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Machine-type communications have suffered serious congestion, overload, and poor quality of service problems in cellular networks, since the cellular networks are designed for human-to-human communications. Moreover, current solutions just focus on the congestion for single base station and cannot adaptively work in the dynamic and complex conditions. In this article, we provide an autonomous and adaptive attractor-selection-based congestion control scheme for massive access from machine-type communication devices based on the resource separation scheme. First, we introduce a feasible and self-adaptive extended attractor-selection mechanism to decide which base station to be chosen. Simultaneously, an effective estimation algorithm for the traffic load of base stations is also designed to represent the network traffic load without frequent information exchanges among devices or base stations. With the available access resources and estimated traffic load taken into consideration, massive access attempts can receive the decisions via the broadcast and adaptively choose proper stations for alleviation of the congestion and overload. Finally, simulation results show that the proposed attractor-selection-based congestion control scheme achieves better performance in terms of average access delay, collision probability, and throughput of the whole system, adaptively accommodating to unpredictable environments under cellular networks.

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