Energy Efficiency Fairness Beamforming Designs for MISO NOMA Systems

Al‐Obiedollah, Haitham; Cumanan, Kanapathippillai; Thiyagalingam, Jeyarajan; Burr, Alister G.; Ding, Zhiguo; Dobre, Octavia A.

doi:10.48550/arxiv.1902.05732

Cited by 1 publication

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…1) NOMA-based MISO Networks: Due to the pivotal role of NOMA with MISO on the performance of physical layer of wireless networks, recently, many researches are done in this area [24]- [28]. Optimal power allocation for NOMAbased MISO satellite networks with power minimization is proposed in [29].…”

Section: B Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Joint Radio Resource Allocation and 3D Beam-forming in MISO-NOMA-based Network with Profit Maximization for Mobile Virtual Network Operators

Zakeri,

Mokari,

Yanikomeroglu

2019

Preprint

View full text Add to dashboard Cite

Massive connections and high data rate services are key players in 5G ecosystem and beyond. To satisfy the requirements of these types of services, non orthogonal multiple Access (NOMA) and 3-dimensional beam-forming (3DBF) can be exploited. In this paper, we devise a novel radio resource allocation and 3D multiple input single output (MISO) BF algorithm in NOMA-based heterogeneous networks (HetNets) at which our main aim is to maximize the profit of mobile virtual network operators (MVNOs). To this end, we consider multiple infrastructure providers (InPs) and MVNOs serving multiple users. Each InP has multiple access points as base stations (BSs) with specified spectrum and multi-beam antenna array in each transmitter that share its spectrum with MVNO's users by employing NOMA. To realize this, we formulate a novel optimization problem at which the main aim is to maximize the revenue of MVNOs, subject to resource limitations and quality of service (QoS) constraints. Since our proposed optimization problem is non-convex and mathematically intractable, we transform it into a convex one by introducing a new optimization variable and converting the variables with adopting successive convex approximation. More importantly, the proposed solution is assessed and compared with the alternative search method and the optimal solution that is obtained with adopting the exhaustive search method. In addition, it is studied from the computational complexity, convergence, and performance perspective. Our simulation results demonstrate that NOMA-3DBF has better performance and increases system throughput and MVNO's revenue compared to orthogonal multiple access with 2DBF by approximately 64%. Especially, by exploiting 3DBF the MVNO's revenue is improved nearly 27% in contrast to 2DBF in high order of antennas.

show abstract

Section: B Related Workmentioning

confidence: 99%

“…The SCA method (Al. 1) produces a sequence of feasible solutions by solving the convex problem in each iteration and the approximate terms are updated in the next iteration and then converges [28], [47]. To ensure convergence of the algorithm, two main conditions should be satisfied.…”

Section: Convergency and Complexity Analysismentioning

confidence: 99%