Fairness and Sum-Rate Maximization via Joint Subcarrier and Power Allocation in Uplink SCMA Transmission

Evangelista, João V. C.; Sattar, Zeeshan; Kaddoum, Georges; Chaaban, Anas

doi:10.1109/twc.2019.2939820

Cited by 39 publications

(27 citation statements)

References 35 publications

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“…P k ij is a continuous variable whereas x k ij is a binary variable. Our objective function is a non-convex function jointly as well as individually with respect to each variable [33] and hence it is an NP hard problem and is hard to solve in polynomial time. Owing to the complexity of the problem, we propose a heuristic algorithm to solve the joint problem in polynomial time.…”

Section: Cooperation In Small-cell Bssmentioning

confidence: 99%

“…R U ij is continuous variable, it can take any value in between 0 and maximum leftover capacity, P k ij is also continuous variable and it can take any value between 0 and P max whereas x k ij and z ij are the binary variables. Constraints are also non-convex along with the objective function [33]. As this problem is also NP hard, we propose a heuristic to solve this problem also.…”

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confidence: 99%

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A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

et al. 2021

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Small cells deliver cost-effective capacity and coverage enhancement in a cellular network. In this work, we present the interplay of two technologies, namely Wi-Fi offloading and small-cell cooperation that help in achieving this goal. Both these technologies are also being considered for 5G and B5G (Beyond 5G). We simultaneously consider Wi-Fi offloading and small-cell cooperation to maximize average user throughput in the small-cell network. We propose two heuristic methods, namely Sequential Cooperative Rate Enhancement (SCRE) and Sequential Offloading Rate Enhancement (SORE) to demonstrate cooperation and Wi-Fi offloading, respectively. SCRE is based on cooperative communication in which a user data rate requirement is satisfied through association with multiple small-cell base stations (SBSs). However, SORE is based on Wi-Fi offloading, in which users are offloaded to the nearest Wi-Fi Access Point and use its leftover capacity when they are unable to satisfy their rate constraint from a single SBS. Moreover, we propose an algorithm to switch between the two schemes (cooperation and Wi-Fi offloading) to ensure maximum average user throughput in the network. This is called the Switching between Cooperation and Offloading (SCO) algorithm and it switches depending upon the network conditions. We analyze these algorithms under varying requirements of rate threshold, number of resource blocks and user density in the network. The results indicate that SCRE is more beneficial for a sparse network where it also delivers relatively higher average data rates to cell-edge users. On the other hand, SORE is more advantageous in a dense network provided sufficient leftover Wi-Fi capacity is available and more users are present in the Wi-Fi coverage area.

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Section: Cooperation In Small-cell Bssmentioning

confidence: 99%

mentioning

confidence: 99%

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

et al. 2021

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“…A sub-optimal algorithm that handles power and codebook assignment separately is then proposed. Efforts to maximize sum-rate and fairness in uplink SCMA using joint channel and power are illustrated in [32]. Iterative algorithms that jointly allocate codebooks and transmit power in subcarriers are implemented with convex programming used to optimize performance.…”

Section: Related Workmentioning

confidence: 99%

“…To evaluate the fairness of the algorithms in distributing resources among users in the network, Jain's fairness metric is embraced. It is defined as in [32] which can be expressed as This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.…”

Section: Figure 6: Energy Efficiency Vs Number Of Iterationsmentioning

confidence: 99%

Biological Resource Allocation Algorithms for Heterogeneous Uplink PD-SCMA NOMA Networks

Sefako

Walingo

2020

IEEE Access

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Due to their ability to multiplex users on a resource element (RE), Non-orthogonal multiple access (NOMA) techniques have gained popularity in 5G network implementation. The features of 5G heterogeneous networks have necessitated the development of hybrid NOMA schemes combining the merits of the individual NOMA schemes for optimal performance. The hybrid technologies on 5G networks make complex air interfaces resulting in new resource allocation (RA) and user pairing (UP) challenges aimed at limiting the multiplexed users interference. Furthermore, common analytical techniques for evaluating the performance of the schemes lead to unrealistic network performance bounds necessitating alternative schemes. This work explores the feasibility of a hybrid power domain sparse code non-orthogonal multiple access (PD-SCMA). The scheme integrates both power and code domain multiple access on an uplink network of small cell user equipments (SUEs) and macro cell user equipments (MUEs). Alternative biological RA/UP schemes; the ant colony optimization (ACO), particle swarm optimization (PSO) and a hybrid adaptive particle swarm optimization (APASO) algorithms, are proposed. The performance results indicate the developed APASO outperforming both the PSO and ACO in sum rate and energy efficiency optimization on application to the PD-SCMA based heterogeneous network.

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“…However, the SIC technique may suffer from the error propagation phenomenon when the received powers are similar [17]. The power allocation process is usually performed in a centralized manner [18,19] where the base station knows the channel state information of all users. For grant free access, each user performs a blind transmission with no information about its propagation environment and interfering users, which makes the power determination more complex.…”

Section: Introductionmentioning

confidence: 99%

Autonomous Power Decision for the Grant Free Access MUSA Scheme in the mMTC Scenario

Ameur

Mary

Hélard

et al. 2020

Sensors

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Non-orthogonal multiple access schemes with grant free access have been recently highlighted as a prominent solution to meet the stringent requirements of massive machine-type communications (mMTCs). In particular, the multi-user shared access (MUSA) scheme has shown great potential to grant free access to the available resources. For the sake of simplicity, MUSA is generally conducted with the successive interference cancellation (SIC) receiver, which offers a low decoding complexity. However, this family of receivers requires sufficiently diversified received user powers in order to ensure the best performance and avoid the error propagation phenomenon. The power allocation has been considered as a complicated issue especially for a decentralized decision with a minimum signaling overhead. In this paper, we propose a novel algorithm for an autonomous power decision with a minimal overhead based on a tight approximation of the bit error probability (BEP) while considering the error propagation phenomenon. We investigate the efficiency of multi-armed bandit (MAB) approaches for this problem in two different reward scenarios: (i) in Scenario 1, each user reward only informs about whether its own packet was successfully transmitted or not; (ii) in Scenario 2, each user reward may carry information about the other interfering user packets. The performances of the proposed algorithm and the MAB techniques are compared in terms of the successful transmission rate. The simulation results prove that the MAB algorithms show a better performance in the second scenario compared to the first one. However, in both scenarios, the proposed algorithm outperforms the MAB techniques with a lower complexity at user equipment.

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Fairness and Sum-Rate Maximization via Joint Subcarrier and Power Allocation in Uplink SCMA Transmission

Cited by 39 publications

References 35 publications

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

A Comparative Analysis of Wi-Fi Offloading and Cooperation in Small-Cell Network

Biological Resource Allocation Algorithms for Heterogeneous Uplink PD-SCMA NOMA Networks

Autonomous Power Decision for the Grant Free Access MUSA Scheme in the mMTC Scenario

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