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Cross Layer Resource Allocation in H-CRAN with Spectrum and Energy Cooperation
5G and beyond wireless networks are the upcoming evolution for the current
cellular networks to provide the essential requirement of future demands such
as high data rate, low energy consumption, and low latency to provide seamless
communication for the emerging applications. Heterogeneous cloud radio access
network (H-CRAN) is envisioned as a new trend of 5G that uses the advantages of
heterogeneous and cloud radio access networks to enhance both the spectral and
energy efficiency. In this paper, building on the notion of effective capacity
(EC), we propose a framework in non-orthogonal multiple access (NOMA)-based
H-CRAN to meet these demands simultaneously. Our proposed approach is to
maximize the effective energy efficiency (EEE) while considering spectrum and
power cooperation between macro base station (MBS) and radio remote heads
(RRHs). To solve the formulated problem and to make it more tractable, we
transform the original problem into an equivalent subtractive form via
Dinkelbach algorithm. Afterwards, the combinational framework of distributed
stable matching and successive convex algorithm (SCA) is then adopted to obtain
the solution of the equivalent problem. Hereby, we propose an efficient
resource allocation scheme to maximize energy efficiency while maintaining the
delay quality of service (QoS) requirements for the all users. The simulation
results show that the proposed algorithm can provide a non-trivial trade-off
between delay and energy efficiency in NOMA H-CRAN systems in terms of EC and
EEE and the spectrum and power cooperation improves EEE of the proposed
network. Moreover, our proposed solution complexity is much lower than the
optimal solution and it suffers a very limited gap compared to the optimal
method
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