A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

Singh, Upendra N.; Dua, Amit; Tanwar, Sudeep; Kumar, Neeraj; Alazab, Mamoun

doi:10.1109/access.2021.3100541

Cited by 14 publications

(5 citation statements)

References 141 publications

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“…If a packet's metric is the highest, the UE gets the top priority and can transmit its data first when resources are available. These metric functions can be categorized according to a number of criteria, including input parameters, objectives, service targets, and optimization goals (see [43][44][45][46][47]). The various prioritization systems are expressed as follows:…”

Section: Prioritization Schemesmentioning

confidence: 99%

Advancing NB-IoT Communication: Performance Analysis and Novel Gap-Aware Hybrid Scheduling for Delay-Sensitive Devices

TRABELSI,

GONTARA,

BOUGHARRIOU

et al. 2024

Preprint

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The explosive growth of Internet of Things (IoT) applications has driven the development of specialized communication technologies to cater to diverse device needs. Narrowband IoT (NB-IoT) is a promising low-power wide-area network (LPWAN) technology designed to support massive machine-type communication (MTC) with tolerant delay transmission. However, MTC presents new challenges for NB-IoT, especially in meeting the very low latency and high reliability requirements. It is important to understand which techniques, such as scheduling and resource allocation, enable low-delay applications to meet their goals. To accomplish these tasks, this paper uses realistic simulations within a variety of traffic scenarios, focusing on scheduling uplink data and resource allocation management. We discuss (1) the components contributing to the Quality of Service (QoS) for NB-IoT devices, (2) evaluate the performance of prioritized scheduling schemes and resource unit (RU) configuration for uplink transmission modes, point out potential improvements to reduce the latency for delay-sensitive devices, and (3) implement and evaluate a novel hybrid scheduling solution called the Gap Aware Hybrid Scheduling (GAHUS) Algorithm. We have developed a solution to enhance network efficiency and prioritize sensitive-delay devices to meet their QoS requirements. Using methods like simulations, comparisons, and performance evaluations, we have demonstrated the effectiveness of our approach in assigning free resource gaps created during long uplink transmissions. GAHUS enables handling massive MTC traffic while ensuring reliable performance for delay-sensitive devices by minimizing rejections and delays.

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Section: Prioritization Schemesmentioning

confidence: 99%

Advancing NB-IoT Communication: Performance Analysis and Novel Gap-Aware Hybrid Scheduling for Delay-Sensitive Devices

TRABELSI,

GONTARA,

BOUGHARRIOU

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…But, it is critical because MTC is naturally applicable to a broad range of new intelligent services, like healthcare, utilities, manufacturing, transportation, and consumer products 11 . Hence, these serve as critical facilitators of the IoT 12 . Indeed, by 2026, the IoT market will be worth trillions due to the connectivity of an exponential number of MT devices for communication and data sharing purposes 13 .…”

Section: Introductionmentioning

confidence: 99%

“…11 Hence, these serve as critical facilitators of the IoT. 12 Indeed, by 2026, the IoT market will be worth trillions due to the connectivity of an exponential number of MT devices for communication and data sharing purposes. 13 With the increasing adoption of the IoT and its requirement to accommodate a diverse and sometimes competing list of goals, 14 MTC is projected to occupy a dominating role in networks.…”

Section: Introductionmentioning

confidence: 99%

An intelligent resource allocation strategy for machine type communication environment

Sharmila,

Satyanarayana

2023

Int J Communication

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SummaryMobile communication has multiplied in many digital intelligent applications. The machine‐type communication (MTC) services have afforded flexible communication facilities considering those facilities. However, high energy consumption and poor data rate have made the MTC a complex system. So, the resource allocation strategy has been introduced by different procedures such as neural models, optimization, and mathematical models. But, in some cases, these algorithms have recorded high complexity and high resource requirement. Hence, the present research article has planned to develop a novel Chimp‐based Extreme Neural Model (CbENM) for allocating the desired optimal resource for each machine user. Moreover, the resources were assigned based on the task completion deadline. Before the resource allocation process, the active state users were predicted by analyzing their data rate and deadlines. Finally, the desired resources were allocated to each user, and the performance was validated. The presented model has a lower delay bond rate and a high data aggregate rate.

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“…Therefore, it is adopted in the long-term evolution of upstream wireless standards. It is also adopted in new 5G communication networks such as machine-to-machine communications and green communications [13,14].…”

Section: Introductionmentioning

confidence: 99%

IQM Mitigation Algorithm with Channel Awareness for Upstream SC-FDMA Systems in the Context of Dual-Hop Broadcasts

2023

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A challenging issue for single carrier frequency division multiple access (SC-FDMA) transmissions is in-phase and quadrature-phase mismatch (IQM). There has been prior reporting on this issue; however, it has always been in the setting of single-hop broadcasts. This study explored the problem of IQM in multiple users upstream SC-FDMA networks within the framework of amplify-and-forward (AF) dual-hop transmissions. We got closer to realistic scenarios by supposing that each node in the network creates its own IQM. Moreover, we profited from the channel decoders that are included in most wireless standards to provide a valuable aid to the offered estimator. A mathematical analysis revealed that IQM originating from all nodes can be merged into channel coefficients to provide so-called effective channel coefficients. This eliminates the requirement for a chain of algorithms to be employed at each node to estimate and adjust for IQM, as well as the algorithms needed to evaluate channel coefficients between the base station and each node in the network. A theoretical investigation showed that the maximum likelihood (ML) solution to the effective channel coefficients estimation is too complicated to be applied in reality. Alternatively, we employed a simple methodology relying on the space-alternating generalized expectation maximization (SAGE) process to determine the ML predictions of the required parameters. The proposed approach incorporates a feedback loop in which the estimator and the channel decoder exchange information to boost one another’s efficiency. Furthermore, we detail how to execute data detection by making use of the predicted effective channel coefficients. The simulation results verify the effectiveness of the proposed approach and show that it outperforms the current methods.

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A Survey on LTE/LTE-A Radio Resource Allocation Techniques for Machine-to-Machine Communication for B5G Networks

Cited by 14 publications

References 141 publications

Advancing NB-IoT Communication: Performance Analysis and Novel Gap-Aware Hybrid Scheduling for Delay-Sensitive Devices

Advancing NB-IoT Communication: Performance Analysis and Novel Gap-Aware Hybrid Scheduling for Delay-Sensitive Devices

An intelligent resource allocation strategy for machine type communication environment

IQM Mitigation Algorithm with Channel Awareness for Upstream SC-FDMA Systems in the Context of Dual-Hop Broadcasts

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