Coexistence of URLLC and eMBB Services in MIMO-NOMA Systems

Chen, Qimei; Wu, Jing; Wang, Jiajia; Jiang, Hao

doi:10.1109/tvt.2022.3205658

Cited by 18 publications

(14 citation statements)

References 32 publications

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“…Authors in [58] have used a NOMA based puncturing technique in MIMO for solving a co-scheduling or coexistence problem of eMBB and URLLC. A joint power allocation and user selection technique are used to formulate the objective function of maximizing eMBB data rate with satisfying the QoS and latency requirements for URLLC users.…”

Section: Matching Algorithmmentioning

confidence: 99%

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Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Adhikari,

Jaseemuddin,

Anpalagan

2024

IEEE Access

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Next generation of wireless networks are characterized by two main features named Enhanced Mobile Broadband (eMBB) and Ultra Reliable Low Latency Communications (URLLC). These two services can be accommodated in the same wireless infrastructure so that wide range of users, demanding either massive throughput or extremely low latency and high reliability requirements, are directly benefited for providing various mission critical services. Co-existence of eMBB and URLLC services, however, demand highly efficient and less complex resource allocation schemes. In this paper, various resource allocation techniques are studied for the co-existence of eMBB and URLLC traffic to meet the heterogeneous specifications of each class of users. A detailed study on existing resource allocation schemes for simultaneous transmission of eMBB and URLLC services based on network slicing, flexible Transmit Time Interval (TTI), scheduling and distributed and federated learning are provided. Moreover, Machine Learning (ML) aided and Reconfigurable Intelligent Surface (RIS) and UAV assisted resource allocation techniques are also studied in detail. Additionally, this paper identifies some challenges for eMBB and URLLC service accommodation in the same wireless architecture and proposes their possible solution approaches.INDEX TERMS eMBB and URLLC, multiplexing, resource allocation, slicing, transmit time interval, machine learning.

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Section: Matching Algorithmmentioning

confidence: 99%

“…There is only 10% degradation on eMBB throughput. [58] To maximize data rate of eMBB users while satisfying the latency requirements of URLLC users.…”

Section: Joint Link Adaptation and Resource Allocation Policymentioning

confidence: 99%

Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Adhikari,

Jaseemuddin,

Anpalagan

2024

IEEE Access

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“…Gaussian distribution γ mg n ∼ CN (0, 1). The subchannel bandwidth FGSA, =0.5, N=20 FGSA, =1, N=20 FGSA, =5, N=20 FGSA, =10, N=20 EBFSA, N=20 GSAG [23,44], N=20 HAG [45,46], N=20 CDAG [47], N=20 DPAG [33,48], N=20…”

Section: A Simulation Setupmentioning

confidence: 99%

“…The existing user grouping algorithms in NOMA mostly consider a single cell [17], [18], or assume that users associate with the nearest BS [14], [22], which ignores the impact of the computing capability of different MEC-BSs on delay performance. Other joint optimization algorithms for association and grouping mostly assume the number of users in each subchannel has to be consistent [23], [24], which is far from optimal. Thirdly, existing studies on NOMA-assisted IoVT with MEC fail to consider that IoVT visual processing tasks have different priorities [25].…”

Section: Introductionmentioning

confidence: 99%

Joint Transmission and Resource Optimization in NOMA-Assisted IoVT With Mobile Edge Computing

Qin,

Lu,

Chen

et al. 2024

IEEE Trans. Veh. Technol.

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“…This type of connections need low latency and highly reliable message flows to assure road safety and traffic efficiency. Therefore, the fifth generation (5G) communication system needs to support massive user connectivity, high throughput demand, low latency and various enhanced applications [4]. In this regard, some technologies have been adopted as promising solutions for 5G, namely Ultra-Dense Network (UDN) and Non-Orthogonal Multiple Access (NOMA) [5].…”

Section: Introductionmentioning

confidence: 99%

Dynamic Resource Allocation Algorithm for Interference Mitigation based on NOMA in UDN Network operating in both Uplink and Downlink

Bouhamed¹,

Marouane²,

Zerai³

2023

Preprint

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The new notion of Internet of Vehicles (IoV) supports Vehicle-to-Everything (V2X) communications, which play a very important role in 5G systems. Non-orthogonal multiple access (NOMA) and Ultra-Dense-Network (UDN) and are two important technologies to meet the requirements of V2X services with their remarkable capacity. However, the concept of NOMA technology, which allows multiple vehicles to be served by the same resource, can lead to interference between different active users. In addition, the dense deployment of small base stations (SBS) in UDN, causes severe interference and degrades the network performance. To solve these problems, interference mitigation is widely used to avoid interference in NOMA-based UDN. In this paper, we suggested a dynamic resource allocation algorithm named Intra-cell-Inter-cell Interference Mitigation for V2X communication for UDN in uplink and downlink sense (Intra-Inter IMVN). Our algorithm aims to achieve five principals objectives, namely applying the same algorithm for both downlink and uplink modes, reducing the degree of interference, improving network performance in terms of throughput and error rate, minimizing cost and delay when using this alternative, combining dynamic metrics to support many V2X scenarios and requirements, and dealing with two types of interference such as intra-cell interference and inter-cell interference. Simulation results show that our proposed Intra-Inter IMVN algorithm outperforms the other recent approaches taking into account different parameters such as the number of users who can share the same resource and the number of available resource blocks.

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Coexistence of URLLC and eMBB Services in MIMO-NOMA Systems

Cited by 18 publications

References 32 publications

Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Resource Allocation for Co-Existence of eMBB and URLLC Services in 6G Wireless Networks: A Survey

Joint Transmission and Resource Optimization in NOMA-Assisted IoVT With Mobile Edge Computing

Dynamic Resource Allocation Algorithm for Interference Mitigation based on NOMA in UDN Network operating in both Uplink and Downlink

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