Efficient Resource Allocation in SCMA-Enabled Device-to-Device Communication for 5G Networks

Sultana, Ajmery; Woungang, Isaac; Anpalagan, Alagan; Zhao, Lian; Ferdouse, Lilatul

doi:10.1109/tvt.2020.2983569

Cited by 30 publications

(20 citation statements)

References 34 publications

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“…The algorithms for PD‐NOMA and SCMA are similar to the ones in References 14,18, respectively, albeit the EE resource allocation proposed in this work. Furthermore, we incorporate resource allocation schemes of References 27,31 in the comparative analysis. Particularly, the CA and UP algorithms in PD‐SCMA are compared with the modified matching game and submodularity approach‐based CA, while PA is compared with the SCA‐based DC method of PA in Reference 27.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…Particularly, the CA and UP algorithms in PD‐SCMA are compared with the modified matching game and submodularity approach‐based CA, while PA is compared with the SCA‐based DC method of PA in Reference 27. In addition, the proposed EE schemes are compared with the resource management schemes in D2D enabled cellular hybrid network of Reference 31, albeit for a downlink system. Here, SCOA algorithm is compared with the proposed CA based on equal power allocation, interference constraint and minimum data rate constraint, OMSP algorithm with RACBS‐D2D and lastly, QAPA with GWF algorithm.…”

Section: Simulation Results and Discussionmentioning

confidence: 99%

“…An opportunistic scheduling approach where cellular users are allocated CBs based on the available CSI is developed in Reference 30. A D2D enabled cellular hybrid network based on SCMA and efficient resource management schemes are proposed in Reference 31. Particularly in a downlink system, CBs are assigned cellular users (CUs) by initially assuming equal PA, interference constraint, minimum data rate constraint.…”

Section: Introductionmentioning

confidence: 99%

“…These hybrid schemes greatly limit network interference, improve spectral and energy efficiency. A modified dual decomposition‐based EE analytical resource allocation (DDEEARA) optimization algorithm employing a parametric transformation from the Dinkelbach method and Lagrange dual decomposition for system EE performance evaluation is proposed. Even though this approach has been used extensively in literature, 34,43,44 its application to multiple parameters (CA, UP, PA) is not trivial since it has been developed and results generated. Comparative results between the simulation‐based JEERA algorithm and the analytical‐based DDEEARA algorithm, the proposed CA, UP, and PA schemes vs resource allocation schemes of References 27,31 and lastly, PD‐SCMA vs SCMA and PD‐NOMA. Results show significant energy efficiency performance improvement of the proposed PD‐SCMA system over the conventional SCMA and PD‐NOMA.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

Chege

Walingo

2020

Trans Emerging Tel Tech

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Modern 5G heterogeneous networks (HetNets) require hybrid multiple access technology for optimal performance. The feasibility of a hybrid power domain sparse code nonorthogonal multiple access (PD‐SCMA) that integrates both power domain nonorthogonal multiple access (PD‐NOMA) and sparse code multiple access (SCMA) for an uplink hierarchical HetNet system is demonstrated. Hybrid schemes namely: Successive Codebook Ordering Assignment (SCOA) for codebook assignment (CA), opportunistic MUE‐SUE pairing (OMSP) for user pairing (UP), and a QoS‐aware power allocation (QAPA) for power allocation (PA) are developed. The SCOA algorithm is based on channel quality ordering metric, OMSP algorithm is based on channel quality diversity and pairing interference metric while the QAPA algorithm features a QoS awareness metric. A joint energy efficiency (EE) resource allocation (JEERA) algorithm that iteratively performs CA, UP, and PA for small cell user equipment (SUE) and the macro user equipment (MUE) to limit interference, improve spectral and energy efficiency is presented. The problem is formulated as a mixed integer nonconvex system EE resource allocation optimization for the small cells under QoS constraints of minimum sum‐rate, interference temperature, maximum power, and SCMA structure for a hybrid low complexity joint SIC‐Log‐MPA receiver. A modified near‐optimal dual decomposition analytical methodology featuring Dinkelbach fractional transformations is utilized to assess the system's performance on an imperfect wireless channel. Through numerical results, the proposed schemes are shown to improve the EE of the small cells in comparison with the prevalent schemes.

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Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Simulation Results and Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

Chege

Walingo

2020

Trans Emerging Tel Tech

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“…Besides the codebook and detector designs, the SE of SCMA-based systems can be improved using resource sharing and UE association in dense-device networks [89,90]. First, the SCMA was employed to enhance the SE in device-to-device (D2D) communication systems, where D2D pairs are allowed to share the same codebook with cellular UEs, and thus the resource allocation and interference management are considered [91][92][93][94]. Kim et al,in [91], proposed a two-stage method based on the combination of graph theory and inner approximation.…”

Section: Ue Associationsmentioning

confidence: 99%

A Survey on Non-Orthogonal Multiple Access: From the Perspective of Spectral Efficiency and Energy Efficiency

et al. 2020

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Non-orthogonal multiple access (NOMA) is a promising technology for next-generation wireless networks with emerging demands on low latency, high throughput, and massive connectivity. Unlike orthogonal multiple access, NOMA allows multiple users to share the same radio resources, which significantly improves spectral efficiency (SE). To achieve green wireless communications for numerous networked devices, NOMA helps reduce energy consumption while satisfying rate fairness and quality-of-experience requirements. The goal of this paper is to introduce the innovative approaches for NOMA in terms of the SE and energy efficiency, and discuss emerging technologies involved with NOMA. Further, its challenges and future research directions are highlighted.

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Joint power allocation and channel assignment for device‐to‐device communication using the Hungarian model and enhanced hybrid Red Fox‐Harris Hawks Optimization

Yoganathan¹,

PS²,

Anitha³

et al. 2023

Int J Communication

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Multihop device-to-device (D2D) communication is a promising advancement since it allows wireless users in close proximity to communicate directly with one another without using base stations (BSs). With two nearby users, this technology intends to keep up with the accelerating development of mobile devices and the rising demands of local traffic loads. High-data-rate shortrange transmission is made possible by this paradigm, which also lowers network backhaul expenses while improving end-user experience, spectral efficiency (SE) and network coverage. In order to maximize the cell's overall sum rates, this article examines the problem of selecting the optimal M-D2D linkages and cellular users (CUs) to form spectrum-sharing partners while taking quality of service (QoS) and energy efficiency (EE) needs into consideration.This study examines the use of a channel assignment system and a power allocation technique to manage interference in D2D communication scenarios involving many hops (more than one hop). The suggested channel assignment approach is based on the Hungarian method, but the power allocation system is based on the time-efficient enhanced Harris hawks optimization (HHO) and red fox (RF) algorithms. A genetic algorithm (GA)-based methodology and various baseline approaches are used to compare the effectiveness of the suggested system. Because it combines exploitation and exploration using a memory-based local search methodology and a perturbation mechanism, the suggested approach outperforms the GA in simulations. The results clearly demonstrate that the suggested method increases EE by up to 13% by producing the appropriate channel and power assignment for CUs and M-D2D users.

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Efficient Resource Allocation in SCMA-Enabled Device-to-Device Communication for 5G Networks

Cited by 30 publications

References 34 publications

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

Energy efficient resource allocation for uplink hybrid power domain sparse code nonorthogonal multiple access heterogeneous networks with statistical channel estimation

A Survey on Non-Orthogonal Multiple Access: From the Perspective of Spectral Efficiency and Energy Efficiency

Joint power allocation and channel assignment for device‐to‐device communication using the Hungarian model and enhanced hybrid Red Fox‐Harris Hawks Optimization

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