Delay Performance of Two-Stage Access in Cellular Internet-of-Things Networks

Kim, Jeemin; Lee, Hyun-Kwan; Kim, Dong-Min; Kim, Seong-Lyun

doi:10.1109/tvt.2017.2776950

Cited by 8 publications

(5 citation statements)

References 21 publications

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“…MPR is suitable to capture the SINR (Signal-to-Interference-plus-Noise-Ratio) based model and is more realistic to model the wireless transmission. Similar assumptions to our work can be found in [5], [9], [22].…”

Section: Introductionsupporting

confidence: 78%

“…Note that when all nodes are transmitting, we can have in total up to M interfering devices at the sink. This assumption in the literature [5], [10], [22].…”

Section: A Network Layer Modelmentioning

confidence: 96%

“…The queues are assumed to have infinite capacity, thus there is no packet dropping. 1 This is a common assumption in the literature, in the IoT context [22].…”

Section: A Network Layer Modelmentioning

confidence: 96%

“…Recently, several works have investigated relaying at the network level [13]- [21]. The deployment of aggregators under network-level cooperation can improve the throughput and delay in IoT networks [22]. However, due to the queueing delay, the stability conditions at the aggregator queues need to be considered.…”

Section: Introductionmentioning

confidence: 99%

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Network-Level Cooperation in Random Access IoT Networks with Aggregators

Παππάς

Dimitriou

Chen

2018

2018 30th International Teletraffic Congress (ITC 30)

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In this work, we consider a random access IoT wireless network assisted by two aggregators. The nodes and the aggregators are transmitting in a random access manner under slotted time, the aggregators use network-level cooperation. We assume that all the nodes are sharing the same wireless channel to transmit their data to a common destination. The aggregators with out-of-band full duplex capability, are equipped with queues to store data packets that are transmitted by the network nodes and relaying them to the destination node. We characterize the throughput performance of the IoT network. In addition, we obtain the stability conditions for the queues at the aggregators and the average delay of the packets.

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Section: Introductionsupporting

confidence: 78%

“…Note that when all nodes are transmitting, we can have in total up to M interfering devices at the sink. This assumption in the literature [5], [10], [22].…”

Section: A Network Layer Modelmentioning

confidence: 96%

“…The queues are assumed to have infinite capacity, thus there is no packet dropping. 1 This is a common assumption in the literature, in the IoT context [22].…”

Section: A Network Layer Modelmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Network-Level Cooperation in Random Access IoT Networks with Aggregators

Παππάς

Dimitriou

Chen

2018

2018 30th International Teletraffic Congress (ITC 30)

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“…These IoT devices are located in isolated areas that do not get coverage from MBSs. The dual-hop IoT network is targeted to enhance the coverage, energy consumption, transmission delay, and reliability of IoT devices by receiving and sending data from and to (relatively) closer relays instead of farther MBSs [8]- [11].…”

Section: Introductionmentioning

confidence: 99%

Meta Distribution of SIR in Dual-Hop Internet-of-Things (IoT) Networks

Ibrahim

Tabassum

Nguyen

2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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This paper characterizes the meta distribution of the downlink signal-to-interference ratio (SIR) attained at a typical Internet-of-Things (IoT) device in a dual-hop IoT network. The IoT device associates with either a serving macro base station (MBS) for direct transmissions or associates with a decode and forward (DF) relay for dual-hop transmissions, depending on the biased received signal power criterion. In contrast to the conventional success probability, the meta distribution is the distribution of the conditional success probability (CSP), which is conditioned on the locations of the wireless transmitters. The meta distribution is a fine-grained performance metric that captures important network performance metrics such as the coverage probability and the mean local delay as its special cases. Specifically, we derive the moments of the CSP in order to calculate analytic expressions for the meta distribution. Further, we derive mathematical expressions for special cases such as the mean local delay, variance of the CSP, and success probability of a typical IoT device and typical relay with different offloading biases. We take in consideration in our analysis the association probabilities of IoT devices. Finally, we investigate the impact of increasing the relay density on the mean local delay using numerical results.Index Terms-Meta distribution, dual-hop Internet of things, ultra-reliable and low-latency communication (URLLC), 5G cellular networks, stochastic geometry.

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