A resource allocation scheme for device-to-device communications using LTE-A uplink resources

Gu, Jaheon; Yoon, Hee-Woong; Lee, Jungha; Bae, Sueng Jae; Chung, Min Young

doi:10.1016/j.pmcj.2015.02.004

Cited by 19 publications

(10 citation statements)

References 15 publications

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“…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. A resource allocation scheme is proposed in [15] that considers the constraints of SC-FDMA for assigning LTE radio resources to device-to-device (D2D) communication more efficiently. The proposed scheme in [15] determines the transmission power of D2D user equipments (DUEs) in order to guarantee certain performance of cellular user equipments (CUEs).…”

Section: A Related Workmentioning

confidence: 99%

“…A resource allocation scheme is proposed in [15] that considers the constraints of SC-FDMA for assigning LTE radio resources to device-to-device (D2D) communication more efficiently. The proposed scheme in [15] determines the transmission power of D2D user equipments (DUEs) in order to guarantee certain performance of cellular user equipments (CUEs). Then, this schemes, couples a CUE and a D2D as a resource sharing pair (RSP) and allocate the subchannels based on well-known proportional fairness (PF) scheduling algorithm.…”

Section: A Related Workmentioning

confidence: 99%

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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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Section: A Related Workmentioning

confidence: 99%

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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“…In the uplink RB allocation, a constraint that needs to be satisfied is that, if more than one RBs are allocated to a user, these should be contiguous according to the SC-FDMA requirements [16]. In order to apply a multiple-RB allocation optimization framework for D2D users, an additive decision variable needs to be defined:…”

Section: B Multiple-rb Sharing For D2ds In Virtualized Environmentsmentioning

confidence: 99%

Optimal Virtualized Resource Slicing for Device-to-Device Communications

Vlachos

Friderikos

2014

2015 IEEE Global Communications Conference (GLOBECOM)

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The Device-to-Device (D2D) communication principle is envisaged to become the key enabler of direct localized communication between mobile nodes that will propel a plethora of novel location-based services. On parallel efforts, virtualization of the Radio Access Network (RAN) is rising as a primal technology for emerging and future wireless networks in which multiple mobile network providers can dynamically share underlying radio resources based on the physical infrastructure. In essence, this work shortens the gap between these two important areas by proposing a set of optimization problem formulations to extend previous works on RAN virtualization and explicitly provide resource slicing for D2D communications. To this end, we aim to yield upper bounds on network performance by devising optimal D2D resource slicing via mathematical programming formulations. In addition, sub-optimal low complexity algorithms, amenable to practical (real-time) implementation, are detailed. Via a wide set of numerical investigations, we show that the proposed solution achieves significant gains in terms of system throughput compared to previous related resource slicing techniques which are D2D oblivious.

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“…The wireless connectivity between machines has been extended by the human-to-human (H2H) communications and machine-to-machine (M2M) communications in cellular networks (CNs). 3 By the third-generation partnership project, the machine-type communication (MTC) is also called M2M communications as a key standardization body. 4,5 MTC is generally utilized for transportation systems, healthcare, smart metering, and monitoring systems.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective cooperative swarm intelligence algorithm for uplink resource allocation in LTE‐A networks

Moses¹,

Balakrishnan²

2019

Trans Emerging Tel Tech

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Nowadays, Long-Term Evolution Advanced (LTE-A) network is the primary innovation in 4G networks. The LTE-A networks convey exceptional data rates and low latency for few sorts of application. Sometimes, in LTE-A, the multiobjective uplink resource allocation is the perplexing optimization problem, and this problem is considered as 0-1 multiobjective knapsack trouble. In order to overcome this trouble, a multiobjective cooperative swarm intelligence algorithm for resource allocation is proposed in this paper. In our proposed work, hybrid firefly algorithm (FFA) and particle swarm optimization (PSO) algorithm are utilized to solve 0-1 multiobjective knapsack problem. Initially, a priority and urgency factor (urgency of packets)-based user ranking and quantifying scheme is designed for scheduling process. After the scheduling process, the resource allocations employ three objective functions, such as maximization of resource utilization, maximization of quality of service (QoS), and interference minimization. The optimization problem is overcome by using the hybrid FFA and PSO algorithm. The experimental outcomes demonstrate that it has the best QoS and less interference in the resource allocation in LTE-A network than state-of-art methods in the proposed strategy.Trans Emerging Tel Tech. 2019;30:e3748.wileyonlinelibrary.com/journal/ett

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A resource allocation scheme for device-to-device communications using LTE-A uplink resources

Cited by 19 publications

References 15 publications

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

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

Optimal Virtualized Resource Slicing for Device-to-Device Communications

Multiobjective cooperative swarm intelligence algorithm for uplink resource allocation in LTE‐A networks

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