Hybrid Multiple Access Scheme Using NOMA and OMA Simultaneously Considering User Request

Tanaka, Fuga; Suganuma, Hirofumi; Maehara, Fumiaki

doi:10.1109/wpmc52694.2021.9700453

Cited by 9 publications

(11 citation statements)

References 13 publications

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“…1, the proposed scheme combines multiple resource patterns with different user requirements, which can enhance the throughput compared to the conventional method based only on the channel condition [5]. In this study, we extended the previous work [7] to the case of multiple transmit antennas because of the recent trend in BS equipment [1,8], and investigated the impact of spatial diversity on the proposed hybrid multiple access scheme.…”

Section: Proposed Schemementioning

confidence: 96%

“…For example, when users with good channel conditions and small desired traffic exist, conventional resource allocation based only on channel conditions provides excessive resources to such users, leading to a reduction in network efficiency. Therefore, we have proposed a flexible resource allocation method that considers the desired user traffic volume as well as the channel conditions for the hybrid multiple access scheme [7]. As shown in Fig.…”

Section: Proposed Schemementioning

confidence: 99%

“…In this context, it is expected to provide instantaneous and flexible resource allocation on the basis of channel conditions, as well as the desired user traffic. Thus, we proposed a resource allocation method for the hybrid multiple access scheme, where the desired user traffic volume and channel conditions are considered for resource allocation [7]. In that study, the proposed scheme was found to successfully improve the system throughput under diversified user traffic.…”

Section: Introductionmentioning

confidence: 99%

“…In that study, the proposed scheme was found to successfully improve the system throughput under diversified user traffic. However, in [7], a single antenna was considered at the base station (BS), and considering recent BSs are generally equipped with multiple antennas [1,8], the effectiveness of the hybrid multiple access scheme is expected to be demonstrated in use of maximum ratio transmission (MRT).…”

Section: Introductionmentioning

confidence: 99%

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Impact of multiple antennas on hybrid multiple access scheme employing NOMA and OMA simultaneously considering user request

2022

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The impact of multiple antennas on a hybrid multiple access scheme was investigated considering the desired user traffic volume as well as channel conditions. In the proposed approach, by using both non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) in the same bandwidth, a resource pattern combined with different user requirements is introduced to effectively meet the demands of diversified wireless services beyond 5G. In this study, maximum ratio transmission (MRT) is applied to NOMA and OMA, considering that recent base stations (BSs) are equipped with multiple antennas. Thus, the spatial diversity gain is considered when calculating the actual throughput used for choosing the best resource pattern. The effectiveness of the proposed scheme is demonstrated through computer simulations by considering the antenna configuration under diversified user traffic for enhanced mobile broadband (eMBB) and ultra-reliable and lowlatency communications (URLLC).

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Section: Proposed Schemementioning

confidence: 96%

Section: Proposed Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Impact of multiple antennas on hybrid multiple access scheme employing NOMA and OMA simultaneously considering user request

2022

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“…In [29], EE is maximized in downlink NOMA systems by using the heuristic resource allocation (Heur-RA) algorithm and optimal resource allocation (Opt-RA) algorithm to solve mixed integer non-linear programming (MINLP) problem under QoS and minimum transmit power constraint. In [30], the authors have proposed an The presentation sequence of the paper is as follows: Section II includes the system model and problem formulation. Section III and IV propose algorithm and simulation results, respectively.…”

Section: A Literature Reviewmentioning

confidence: 99%

Energy Efficient Resource Allocation for H-NOMA Assisted B5G HetNets

et al. 2022

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The resource allocation solution offered based on Non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes are sub-optimal to address the challenging quality of service (QoS) and higher data rate viz-a-viz energy efficiency (EE) requirements in 5th generation (5G) cellular networks. In this work, we maximize the EE using user equipment (UE) clustering (UE-C) with downlink hybrid NOMA (H-NOMA) assisted beyond 5G (B5G) HetNets. We formulate an optimization problem incorporating UE admission in a cluster, UE association with a base station (BS), and power allocation assisted by H-NOMA, i.e., OMA and NOMA schemes in the macro base station (MBS) only and heterogeneous networks (HetNets) environments. The problem formulated is a type of non-linear concave fractional programming (CFP) problem. The Charnes-Cooper transformation (CCT) is applied to the formulated non-linear CFP problem to convert it into a concave optimization, i.e., mixed-integer nonlinear programming (MINLP) problem. A two-phase ϵ-optimal outer approximation algorithm (OAA) is used to solve the MINLP problem. The simulation results show that H-NOMA with HetNets outperforms H-NOMA with MBS only in terms of UE admission, UE association, throughput, and EE. INDEX TERMS UE-clustering, H-NOMA, fractional programming, MINLP, energy efficiency I. INTRODUCTIONT HE rapid growth in the number of mobile user equipment (UE), and heavy data-driven applications, i.e., live video gaming, video streaming, social networking, etc are imposing challenging requirements like minimum delay, higher data rates, spectrum efficiency (SE), and energy efficiency (EE) on the beyond 5th Generation (B5G) cellular networks. This exponential growth in mobile UEs viz-aviz mobile data traffic is adding to a significant increase in the energy consumption in cellular networks. Information communication technology (ICT) is consuming almost 2% of the world's total energy. Energy consumption emits carbon which causes the greenhouse effect. Thus, ICT offering higher data rates, low carbon emission, and EE are the prime considerations in B5G cellular networks. Thus, academia and industry in the wireless communication field must divert their research towards future energy-efficient green cellular networks in B5G networks [1]-[3]. The abbreviations used in this work are defined in Table A1 of Appendix A.Energy-efficient radio resource management techniques are required to satisfy the needs for quality of service (QoS) and higher data rates with minimum energy consumption. EE is the ratio of data rate to the total energy consumed [4], [5].EE can be improved using heterogeneous networks (Het-Nets), which include a macro base station (MBS) and small base stations (SBSs) [6]- [8]. HetNets cover more geographical areas and offer higher data rates and are energy efficient than the conventional MBS-only networks. In HetNets, MBS is large with high transmit power, and SBSs (i.e., femtocell, picocell, etc.) are of small size with low transmit power [9]. A low transmit-powered SBS...

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