Joint Access and Fronthaul Radio Resource Allocation in PD-NOMA-Based 5G Networks Enabling Dual Connectivity and CoMP

Moltafet, Mohammad; Joda, Roghayeh; Mokari, Nader; Sabagh, Mohammad R.; Zorzi, Michele

doi:10.1109/tcomm.2018.2865766

Cited by 42 publications

(43 citation statements)

References 48 publications

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“…The SCA method with the linear approach is a well known method to approximate the non-convex optimization problem with a convex one [46], [49], [51], [52]. The applied approximation method for the small values of channel gains ( 1) has acceptable accuracy [52]. In the considered system model, due to the fact that the entries of the channel gain matrices have small values the MMA approximation has good accuracy [52].…”

Section: A Validity Of the Approximation Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Robust Radio Resource Allocation in MISO-SCMA Assisted C-RAN in 5G Networks

Moltafet

Parsaeefard

Javan

et al. 2019

IEEE Trans. Veh. Technol.

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In this paper, by considering multiple slices, a downlink transmission of a sparse code multiple access (SCMA) based cloud-radio access network (C-RAN) is investigated. In this regard, by supposing multiple input and single output (MISO) transmission technology, a novel robust radio resource allocation is proposed where considering uncertain channel state information (CSI), the worst case approach is applied. The main goal of the proposed radio resource allocation is to, maximize the system sum rate with maximum available power at radio remote head (RRH), minimum rate requirement of each slice, maximum frounthaul capacity of each RRH, user association, and SCMA constraints. To solve the proposed optimization problem in an efficient manner, an iterative method is deployed where in each iteration, beamforming and joint codebook allocation and user association subproblem are solved separately. By introducing some auxiliary variables, the joint codebook allocation and user association subproblem is transformed into an integer linear programming, and to solve the beamforming optimization problem, minorization-maximization algorithm (MMA) is applied. Via numerical results, the performance of the proposed system model versus different system parameters and for different channel models are investigated. Index Terms-5G, Sparse code multiple access (SCMA), C-RAN, robust resource allocation.

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Section: A Validity Of the Approximation Methodsmentioning

confidence: 99%

“…The applied approximation method for the small values of channel gains ( 1) has acceptable accuracy [52]. In the considered system model, due to the fact that the entries of the channel gain matrices have small values the MMA approximation has good accuracy [52].…”

Section: A Validity Of the Approximation Methodsmentioning

confidence: 99%

Robust Radio Resource Allocation in MISO-SCMA Assisted C-RAN in 5G Networks

Moltafet

Parsaeefard

Javan

et al. 2019

IEEE Trans. Veh. Technol.

Self Cite

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“…This toolbox, to solve an optimization problem, exploits the interior point method . Therefore, its computational complexity is

C = \log (\frac{N_{c}}{v_{1} v_{2}}) / \log (v_{3})

, where N c is the number of constraints, v 1 is the initial point to approximate the accuracy of the interior point method, v 2 is the stopping criterion of the interior point method, and v 3 is used to update the accuracy of the interior point method . By utilizing this equation, the complexity of power and time allocation problems are calculated as C 1 and C 2 , respectively.…”

Section: Solution For the Pdma‐based Optimization Problemmentioning

confidence: 99%

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

Hooshiary

Azmi

Mokari

2020

Trans Emerging Tel Tech

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Nonorthogonal multiple access (NOMA) and energy harvesting technologies are two promising approaches to increase spectral and energy efficiency, respectively. In this paper, a pattern division multiple access (PDMA) uplink transmission network in which users are able to harvest energy from the received radio frequency power is considered. In order to maximize the energy efficiency, we perform resource allocation in the power, subcarrier, and time domains. Also, for each time slot, the pattern matrix is determined dynamically. To enhance the detection reliability, successive interference cancellation and maximal ratio combining at each receiver are utilized. For resource allocation, the actual harvested and available energies of the users are considered. Moreover, in order to perform a comprehensive analysis, further to PDMA, the energy efficiency of the power domain NOMA (PD-NOMA) is also investigated and the results are compared. It is shown that the energy efficiency and the average total transferred data of PDMA are higher than that of PD-NOMA.

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“…Therefore, (27) is a convex optimization problem, which can be solved by numerical convex program solvers, e.g., interior-point method [37]. To obtain the solution of problem (21), we need to iteratively solve (27). Specifically, initialized from a given feasible solution V ,T,Q , the optimal {V * , T * , Q * , z * } is obtained by solving (27).…”

Section: Proposed Solutionmentioning

confidence: 99%

“…Unlike the works focusing on the arXiv:1909.06218v1 [cs.IT] 13 Sep 2019 downlink EE [5], [14], [18], the optimization of uplink EE is more challenging since the power allocation at users and beam design at the BS must be taken into consideration jointly. Although joint optimization problems in the downlink exist in the literature, such as joint subcarrier and BS power allocation [19], [20] as well as joint user access and BS power allocation [21], [22]. However, these optimization problems are clearly different from our joint optimization problem of the detection matrix at the BS and transmit power at the users.…”

Section: Introductionmentioning

confidence: 98%

Codebook-Based Max–Min Energy-Efficient Resource Allocation for Uplink mmWave MIMO-NOMA Systems

Hao

Zeng

Sun

et al. 2019

IEEE Trans. Commun.

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In this paper, we investigate the energy-efficient resource allocation problem in an uplink non-orthogonal multiple access (NOMA) millimeter wave system, where the fullyconnected-based sparse radio frequency chain antenna structure is applied at the base station (BS). To relieve the pilot overhead for channel estimation, we propose a codebook-based analog beam design scheme, which only requires to obtain the equivalent channel gain. On this basis, users belonging to the same analog beam are served via NOMA. Meanwhile, an advanced NOMA decoding scheme is proposed by exploiting the global information available at the BS. Under predefined minimum rate and maximum transmit power constraints for each user, we formulate a max-min user energy efficiency (EE) optimization problem by jointly optimizing the detection matrix at the BS and transmit power at the users. We first transform the original fractional objective function into a subtractive one. Then, we propose a two-loop iterative algorithm to solve the reformulated problem. Specifically, the inner loop updates the detection matrix and transmit power iteratively, while the outer loop adopts the bisection method. Meanwhile, to decrease the complexity of the inner loop, we propose a zero-forcing (ZF)-based iterative algorithm, where the detection matrix is designed via the ZF technique. Finally, simulation results show that the proposed schemes obtain a better performance in terms of spectral efficiency and EE than the conventional schemes.

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Joint Access and Fronthaul Radio Resource Allocation in PD-NOMA-Based 5G Networks Enabling Dual Connectivity and CoMP

Cited by 42 publications

References 48 publications

Robust Radio Resource Allocation in MISO-SCMA Assisted C-RAN in 5G Networks

Robust Radio Resource Allocation in MISO-SCMA Assisted C-RAN in 5G Networks

Energy efficient transmission in dynamic PDMA‐based systems with RF energy harvesting

Codebook-Based Max–Min Energy-Efficient Resource Allocation for Uplink mmWave MIMO-NOMA Systems

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