Optimizing Resource Allocation for 6G NOMA-Enabled Cooperative Vehicular Networks

Ali, Zain; Khan, Wali Ullah; Ihsan, Asim; Waqar, Omer; Sidhu, Guftaar Ahmad Sardar; Kumar, Neeraj

doi:10.1109/ojits.2021.3107347

Cited by 16 publications

(8 citation statements)

References 48 publications

(55 reference statements)

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“…• Need to apply different algorithms for resource allocation in various users Ali et al 24 KKT, NOMAenabled cooperative vehicular networks…”

Section: Adopted Methodologymentioning

confidence: 99%

“…In this searching phase, the best position is calculated in Equation (18). From Equation (18), the exact search position of the bald eagle is derived and the calculation is given in Equations ( 19)- (24), where P m denotes the mean bald eagle's position, P n denotes the new position of bald eagles…”

Section: Analytic Model Of Proposed Hybrid Optimization Algorithmmentioning

confidence: 99%

“…In 2021, Ali et al 24 concentrate on the ability to provide great spectrum efficiency, exhibit user fairness, and provide free access to 6G vehicle networks, the NOMA model has attracted a lot of interest in recent years. For an integrated vehicular network with NOMA assistance, a new optimization framework is proposed in this research.…”

Section: Related Workmentioning

confidence: 99%

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Resource allocation in paired users: Optimization‐assisted user grouping for fairness improvement of NOMA

Louis,

Dalton

2024

Int J Communication

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SummaryThe solution of resource allocation is based on NOMA and OMA structures that are suboptimal to satisfy the demanding QoS and higher data rate requirements compared to EE requirements in 5G cellular networks. In this work, the resource allocation problem in the hybrid MC‐NOMA system is solved. The system achieves the trade‐off between spectral and energy efficiency (EE) with the lowest rate of user requirements. The system's resource allocation, including power allocation, is considered the crucial factor and is identified as a single‐objective problem. The suggested work focuses on user pairing and allocation on paired users following processing. The user grouping is designed to connect near‐ and far‐users with high C3 to increase the fairness of NOMA. As a result, this work considers multiple goals, such as C3 maximization, spectrum efficiency, and energy efficiency. This paper aims to present a novel hybrid optimization model with the combination of coati and bald eagle optimization algorithms, to solve the defined optimization problem. The experimental results show that the suggested system outperforms the conventional algorithms by evaluating different performance measures such as channel correlation, spectrum efficiency, energy efficiency, and power allocation.

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“…• Need to apply different algorithms for resource allocation in various users Ali et al 24 KKT, NOMAenabled cooperative vehicular networks…”

Section: Adopted Methodologymentioning

confidence: 99%

Section: Analytic Model Of Proposed Hybrid Optimization Algorithmmentioning

confidence: 99%

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Resource allocation in paired users: Optimization‐assisted user grouping for fairness improvement of NOMA

Louis,

Dalton

2024

Int J Communication

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“…The NOMA is a technique that can be applied to existing resources efficiently without affecting the users QoS [111] by increasing the number of served subscribers. The NOMA is proposed as a candidate technique to satisfy the stringent requirements of 6G networks [112]. By broadcasting data at the same time and frequency but with different power levels or by allocating codes, it enables users to consume resources efficiently without affecting the users QoS [111] by increasing the number of served subscribers.…”

Section: ) Non-orthogonal Multiple Access (Noma)mentioning

confidence: 99%

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Alhaj,

Jamlos,

Manap

et al. 2024

IEEE Access

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The fifth-generation (5G) wireless communications have been deployed in many countries with the following features: wireless networks at 20 Gbps as peak data rate, a latency of 1 ms, reliability of 99.999%, maximum mobility of 500 km/h, a bandwidth of 1 GHz, and a capacity of 10 6 up to Mbps/m 2 . Nonetheless, the rapid growth of applications, such as extended/virtual reality (XR/VR), online gaming, telemedicine, cloud computing, smart cities, the Internet of Everything (IoE), and others, demand lower latency, higher data rates, ubiquitous coverage, and better reliability. These higher requirements are the main problems that have challenged 5G while concurrently encouraging researchers and practitioners to introduce viable solutions. In this review paper, the sixth-generation (6G) technology could solve the 5G limitations, achieve higher requirements, and support future applications. The integration of multiple access techniques, terahertz (THz), visible light communications (VLC), ultra-massive multiple-input multiple-output (um-MIMO), hybrid networks, cell-free massive MIMO, and artificial intelligence (AI)/machine learning (ML) have been proposed for 6G. The main contributions of this paper are a comprehensive review of the 6G vision, KPIs (key performance indicators), and advanced potential technologies proposed with operation principles. Besides, this paper reviewed multiple access and modulation techniques, concentrating on Filter-Bank Multicarrier (FBMC) as a potential technology for 6G. This paper ends by discussing potential applications with challenges and lessons identified from prior studies to pave the path for future research.

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“…With the CF approach, the signal is compressed and sent to the target location(s), whereas with the CpF however does not requires CSI and exploits signal couplings produced by the channel to remove noise noise and mitigate interference at the relays thereby reducing the number of relays required. Resource allocation optimization has been analyzed using the above coding schemes in [45,[50][51][52][53][54][55][56][57][58][59][60] in order to improve CR-NOMA performance. Majority of the CR-NOMA performance evaluations (OP, achievable rate, BER, etc.)…”

Section: Performance Of Cr-noma With Cbsm Channel Modelmentioning

confidence: 99%

Performance of Cooperative Relay NOMA with Large Antenna Transmitters

et al. 2022

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The potential of the Non-Orthogonal Multiple Access (NOMA) approach for wireless communications in the fifth generation (5G) and beyond can not be underestimated. This is because users with favorable channel conditions can serve as relays to improve system performance by employing Successive Interference Cancellation (SIC). Lately, the combination of NOMA and the cooperative relay has attracted the interest of researchers. The analysis of cooperative relay NOMA (CR-NOMA) with a massive multiple-input multiple-output (mMIMO) system is mainly based on theoretical channel models such as the correlated-based stochastic channel model (CBSM) even though the geometric-based stochastic channel model (GBSM) has been found to provide better, practical and realistic channel properties. This, in our view, is due to computational challenges. Again, the performance of CR-NOMA systems using the GBSM channel model with large antenna transmitters and network coding schemes has attracted little attention in academia. Therefore, the need to study mMIMO CR-NOMA that considers channel properties such as path-loss, delay profile and tilt angle has become vital. Furthermore, the co-existing of large antenna transmitters with coding schemes needs further investigation. In this paper, we study the performance of a two-stage mMIMO CR-NOMA network where the transmitter is represented as a uniform rectangular array (URA) or cylindrical array (CA). The communication channel from the transmitter (TX) to the user equipment (UE) through a relay station (RS) is modeled with a 3GPP’s three-dimensional (3D) GBSM mMIMO channel model. To improve the analytical tractability of 3D GBSM, we defined the antenna element location vectors using the physical dimension of the antenna array and incorporated them into the 3D channel model. Bit-error rates, achievable rates and outage probabilities (OP) are examined using amplify-and-forward (AF) and decode-and-forward (DF) coding schemes. Results obtained show with fixed power allocation and SNR of 20 dB, far or weak users can attain a high achievable rate using DF and URA. Again, from the results, the combination of AF and CA presents better outage probabilities. Finally, the results indicate that the performance difference between CBSM and GBSM is marginal, even though the proposed 3D GBSM channel model has a higher degree of random parameters and computational complexities.

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Optimizing Resource Allocation for 6G NOMA-Enabled Cooperative Vehicular Networks

Cited by 16 publications

References 48 publications

Resource allocation in paired users: Optimization‐assisted user grouping for fairness improvement of NOMA

Resource allocation in paired users: Optimization‐assisted user grouping for fairness improvement of NOMA

Integration of Hybrid Networks, AI, Ultra Massive-MIMO, THz Frequency, and FBMC Modulation Toward 6G Requirements: A Review

Performance of Cooperative Relay NOMA with Large Antenna Transmitters

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