A mechanism for uplink packet scheduler in LTE network in the context of machine-to-machine communication

Maia, Adyson M.; Vieira, Dário; Castro, Miguel; Ghamri‐Doudane, Yacine

doi:10.1109/glocom.2014.7037228

Cited by 16 publications

(13 citation statements)

References 14 publications

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“…Many studies have addressed radio resource allocation for M2M devices in LTE/LTE-A technology [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

“…Authors in [29] proposed a scheduling approach for M2M devices. This mechanism uses the current and past information about resource allocations, channel quality and QoS requirements to control the impact of M2M and H2H communication and to ensure fairness in resource allocation.…”

Section: Related Workmentioning

confidence: 99%

“…This mechanism uses the current and past information about resource allocations, channel quality and QoS requirements to control the impact of M2M and H2H communication and to ensure fairness in resource allocation. Maia et al [29] propose extending the nine QoS classes defined in [31] which are adapted only to H2H applications, by adding new classes for M2M communication. Their propositional scheduler consists of two phases.…”

Section: Related Workmentioning

confidence: 99%

“…In the second phase, available resources are divided equally between selected M2M devices. The propositional mechanism in [29] allows one to satisfy the QoS requirements and ensure fairness in resource allocations, but it does not reduce the consumed energy for M2M devices.…”

Section: Related Workmentioning

confidence: 99%

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Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Rekhissa

Belleudy

Bessaguet³

2019

Sensors

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Machine-to-machine (M2M) communication consists of the communication between intelligent devices without human intervention. Long term evolution (LTE) and Long-term evolution-advanced (LTE-A) cellular networks technologies are excellent candidates to support M2M communication as they offer high data rates, low latencies, high capacities and more flexibility. However, M2M communication over LTE/LTE-A networks faces some challenges. One of these challenges is the management of resource radios especially on the uplink. LTE schedulers should be able to meet the needs of M2M devices, such as power management and the support of large number of devices, in addition to handling both human-to-human (H2H) and M2M communications. Motivated by the fundamental requirement of extending the battery lives of M2M devices and managing an LTE network system, including both M2M devices and H2H users, in this paper, two channel-aware scheduling algorithms on the uplink are proposed. Both of them consider the coexistence of H2H and M2M communications and aim to reduce energy consumption in M2M devices. The first algorithm, called FDPS-carrier-by-carrier modified (CBC-M), takes into account channel quality and power consumption while allocating radio resources. Our second algorithm, recursive maximum expansion modified (RME-M), offers a balance between delay requirement and energy consumption. Depending on the system requirements, RME-M considers both channel quality and system deadlines in an adjustable manner according to M2M devices needs. Simulation results show that the proposed schedulers outperform the round-robin scheduler in terms of energy efficiency and have better cell spectral efficiency.

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“…Many studies have addressed radio resource allocation for M2M devices in LTE/LTE-A technology [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29].…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Energy Efficient Resource Allocation for M2M Devices in LTE/LTE-A

Rekhissa

Belleudy

Bessaguet³

2019

Sensors

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“…In addition, a variable chunk size based method is proposed in [12] to allocate resource blocks (RBs) to a user. The papers of [13] and [14] introduced a packet scheduling mechanism for LTE networks with M2M communications. The proposed approach uses the system's current information to classify and prioritize data traffics to reduce the impact of M2M communications on H2H beside considering the QoS and fairness by adjusting the congestion level.…”

Section: A Related Workmentioning

confidence: 99%

Delay-sensitive resource allocation for relay-aided M2M communication over LTE-advanced networks

Mardani

Mohebi

Maham

et al. 2017

2017 IEEE Symposium on Computers and Communications (ISCC)

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Machine-to-machine (M2M) communications consist of a large number of smart devices that communicate automatically without human intervention. The Third-Generation Partnership Project (3GPP) Long-Term Evolution (LTE) and LTE-Advanced (LTE-A), due to some features such as IP connectivity and scalability, are ready-to-use infrastructures for the M2M communications implementation. In the next generation of cellular networks with M2M devices, radio resource allocation is a major issue. In order to solve the issue, this paper addresses the efficient resource block (RB) allocation problem for different relay-aided cellular and M2M user equipments (UEs) to maximize the end-to-end data rate under different constraints of Single Carrier Frequency Division Multiple Access (SC-FDMA). The proposed solution also satisfies the maximum power budget, the minimum data rate and statistical QoS delay requirements for prioritizing different traffics under total power constraint. Numerical results demonstrate the effectiveness of the proposed scheme.

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