Dynamic resource allocation for uplink non‐orthogonal multiple access systems

Lv, Guocheng; Li, Xunan; Shang, Ruibo; Xue, Ping

doi:10.1049/iet-com.2017.0972

Cited by 17 publications

(4 citation statements)

References 19 publications

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“…Considering the constraints of user QoS and queue stability, literatures [24] and [25] investigated power allocation in MC-NOMA networks using the stochastic optimization method. In [26] and [27], for uplink and downlink MC-NOMA systems respectively, the authors studied power and subcarrier allocations to maximize WSR.…”

Section: A Motivation and Related Workmentioning

confidence: 99%

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Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Wang

Chen

et al. 2019

IEEE Access

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In this paper, we investigate the power allocation for maximizing weighted sum rate (WSR) in downlink multiple carriers non-orthogonal multiple access (MC-NOMA) systems with imperfect successive interference cancellation (SIC). We formulate the power allocation problem as a non-convex optimization problem with the total power constraint of all sub-channels while considering often-neglected issues of SIC error and power order constraints at users. First, we discuss that the optimization problem assuming receivers can perform perfect SIC, and we provide a concavity condition of the WSR maximization problem for the MC-NOMA system. When the concavity condition is not satisfied, a fractional quadratic transformation is used to overcome the difficulty of problem non-convexity. Based on the transformation, we propose an iterative power allocation algorithm. Then, we consider the SIC error and the power order constraints in the optimization problem and present a power allocation method with imperfect SIC. Moreover, for both the perfect and imperfect SIC, we derive some propositions of the optimal power allocation solution to the WSR maximization problem and propose a low-complexity power allocation algorithm based on these propositions. Finally, we provide a joint user scheduling and power allocation algorithm for maximizing the WSR. The simulation results illustrate that the proposed resource allocation methods have a better performance than the existing schemes.

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Section: A Motivation and Related Workmentioning

confidence: 99%

“…Similar to Subsection III-B, by introducing auxiliary variables {γ n,k } and {θ n,k }, we transform the problem (26) into a concave problem as…”

Section: Power Allocation In Mc-noma With Imperfect Sicmentioning

confidence: 99%

Low-Complexity Power Allocation in NOMA Systems With Imperfect SIC for Maximizing Weighted Sum-Rate

Wang

Chen

et al. 2019

IEEE Access

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“…The proposed system applied for improving the energy efficiency by using allocating resources techniques. Firstly, the problem of linear programming formulation found then applying the CPLEX optimization [17].…”

Section: Introductionmentioning

confidence: 99%

Spectrum Sharing Environment Using Deep Learing Techniques

Alhashimi,

Madlol

2023

Preprint

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Recently, the satellite communication has main demand but still facing main problems which are the spectrum limited, both cognitive-radio (CR) and non-orthogonal-multiple-access (NOMA) methods are identified as a one of the potential solutions for these issues. Using the deep learning techniques with the CR and NOMA systems will be improvement in the spectrum effectiveness. One of the performance enhancement of the NOMA, the integration with the satellite-terrestrial-relay-network (ISTRN) in a spectrum-sharing context of several main-users (PUs) is examined. We specifically presented and given the interference limitation imposed by several nearby pus and its effect on each other’s. The closed-form formulations are investigated the ergodic-capacity (EC) and outage-probability (OP). The asymptotic-analysis for OP at high SNRs is achieved to get additional insights. To support our research and reveal the effects of the significant characteristics on the quality of the system; the numerical data and analysis are provided with deep discussions.

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“…To be specific, the power allocation coefficients that allow successful decoding of each user's signal are derived, and found to be dependent only on the target rate and the total number of users. Joint subcarrier assignment and power allocation for weighted sum‐rate maximisation under transmit power constraint per user is considered in [18]. In turn, a novel optimal SIC order is proposed, and then the Lagrangian dual method is employed to obtain an asymptotically optimal solution, which outperforms conventional OMA schemes and other static NOMA schemes.…”

Section: Introductionmentioning

confidence: 99%