Robust resource allocation for NOMA-assisted heterogeneous networks

Xie, Hao; Xu, Yongjun

doi:10.1016/j.dcan.2021.06.007

Cited by 13 publications

(9 citation statements)

References 32 publications

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“…Additionally, problem (17) is still non convex because the rank-one constraint is not convex and W needs to be satisfied by rank(W ) = 1 and W ⪰ 0. It can be eliminated first to create a more relaxed optimisation problem, as in (18).…”

Section: Using a Fixed ψ To Optimise ϕmentioning

confidence: 99%

Hybrid RIS-assisted interference mitigation for heterogeneous networks

Soumana Hamadou,

Wa Maina,

Soidridine

2024

IJEECS

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Reconfigurable intelligent surfaces (RIS) have evolved as a low-cost and energy- efficient option to increase wireless communication capacity. In this research, we suggest using hybrid RIS (H-RIS) to reduce interference in heterogeneous networks (HetNet). In contrast to traditional passive RIS, a hybrid RIS is suggested, which is fitted with a few active elements to not only reflect but also amplify incident signals for a significant performance increase. By jointly optimising the passive and active coefficients of the H-RIS, we aim to maximise the rate of the small cell user (SUE). We presented an effective alternating optimisation (AO)-based phase shift matrix coefficients (AO-PMC) technique to tackle this problem by iteratively optimising these variables because the optimisation problem is not convex. The simulation results demonstrate that, in comparison to the passive RIS-assisted HetNet scheme and the scheme without RIS, the suggested scheme, with just 8% of active elements, can enable HetNet to gain superior spectral efficiency (SE) and energy efficiency (EE). The outcomes also demonstrate that, in the majority of the cases taken into account, H-RIS can outperform the active RIS-assisted HetNet scheme.

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Section: Using a Fixed ψ To Optimise ϕmentioning

confidence: 99%

Hybrid RIS-assisted interference mitigation for heterogeneous networks

Soumana Hamadou,

Wa Maina,

Soidridine

2024

IJEECS

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“…The SINR of this user is given in Equation (14). 50‐52

δ_{u_{S_{c}}}^{b} = \frac{x_{u_{S_{c}}} y_{u_{S_{c}}}^{b} p_{u_{S_{c}}}^{b} h_{u_{S_{c}}}^{b}}{h_{u_{S_{c}}}^{b} \sum_{i_{S_{c}} = u_{S_{c}} + 1}^{U_{S_{c}}} p_{i_{S_{c}}}^{b} + h_{u_{M_{c}}}^{b} 𝒫_{M} + N_{o}} .

…”

Section: System Modelmentioning

confidence: 99%

Efficient resource allocation for hybrid nonorthogonal multiple access based heterogeneous networks beyond fifth‐generation

Ghafoor

Ali

Khan

et al. 2022

Trans Emerging Tel Tech

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Fifth‐generation (5G) and future beyond fifth‐generation (B5G) networks will require immense capacity due to the high rise in the number of multimedia applications and mobile devices. The heterogeneous networks (HetNets) in 5G and B5G can increase the heterogeneity and network throughput because macro base station‐only (MBS‐only) networks cannot satisfy the drastic increase in capacity demands. Hybrid nonorthogonal multiple access (H‐NOMA) can accommodate the increasing number of multimedia applications and mobile devices in 5G and B5G. H‐NOMA in B5G can also improve spectral efficiency. Before this, the researchers had not considered user clustering with H‐NOMA in HetNets. This article investigates the user clustering with downlink H‐NOMA in HetNet to maximize the network throughput in 5G and B5G. The formulated mathematical problem optimizes the considered key performance indicators (KPIs), that is, users admission in clusters, users association with base stations, power allocation to users, and network throughput. At the same time, it also satisfies the minimum transmit power and data rate requirements of users. The formulated problem is a mixed‐integer nonlinear programming (MINLP) problem. We have proposed an ϵ$$ \epsilon $$‐optimal algorithm, that is, outer approximation algorithm (OAA) to solve the MINLP problem because the complexity of the optimal exhaustive search algorithm (ESA) increases exponentially with an increase in the number of users. H‐NOMA with user clustering in HetNet is evaluated with extensive simulations to show its effectiveness regarding network throughput in 5G and B5G. We have also considered the proposed framework in the MBS‐only network and compared its performance with HetNet. The results verify that the proposed framework in HetNet performs better than the MBS‐only network. The complexity of the ϵ$$ \epsilon $$‐optimal algorithm is calculated that gives ϵ$$ \epsilon $$‐optimal results within ϵ=10prefix−3$$ \epsilon =1{0}^{-3} $$. We have also made a complexity analysis of the proposed OAA and ESA and concluded that the complexity of the proposed OAA algorithm is less than the ESA.

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“…In recent years, the number of mobile UE is increased quickly, and data‐intensive applications like live video playing games, video streaming, networking, social media, and so forth are placing demands on the B5G cellular networks like minimal delay, increased data rates, SE, and EE 1–3 . Wireless networks are significantly using more energy due to the exponential expansion in mobile UEs relative to mobile data traffic.…”

Section: Introductionmentioning

confidence: 99%

“…The superposition coding technique can be used at transmitters to multiplex the signals between these users. At the receivers, the SIC method is used for the decoding procedure 2,10 . On the other hand, rate fairness between users or QoS is another crucial issue that should be ensured in NOMA systems 11,12 .…”

Section: Introductionmentioning

confidence: 99%

“…At the receivers, the SIC method is used for the decoding procedure. 2,10 On the other hand, rate fairness between users or QoS is another crucial issue that should be ensured in NOMA systems. 11,12 This is because if rate fairness or quality of service requirements are not placed on the system, all transmit power would be distributed to the single user with the best channel quality, resulting in utter unfairness among users and the conversion of NOMA to OMA.…”

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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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Robust resource allocation for NOMA-assisted heterogeneous networks

Cited by 13 publications

References 32 publications

Hybrid RIS-assisted interference mitigation for heterogeneous networks

Hybrid RIS-assisted interference mitigation for heterogeneous networks

Efficient resource allocation for hybrid nonorthogonal multiple access based heterogeneous networks beyond fifth‐generation

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

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