Abstract
The increasing in energy consumptions of the current wireless networks, leads towards designing energy-efficient 5G networks. The application of non-orthogonal multiple access (NOMA) in the heterogeneous networks (HetNets) improves the spectrum utilization with the cost of efficient resource allocation. Hence, this article proposes optimal user-pairing and power allocation solutions towards achieving fair energy-efficient resource allocation in downlink femtocell NOMA-HetNets. In the proposed optimization process, the considered constraints are the user's transmission rate, transmit power budget at the base station (BS), and the interference. The energy consumption of both the transmitter and the receiver are considered to simulate the real system design. The Greedy Algorithm (GA) is used to achieve a low-complex optimal solution during the user-pairing process. Simultaneously, the max-min energy efficiency optimization approach is employed to maximize the minimum energy efficiency of the femtocell users to achieve the optimal power allocation solution. The mathematical formulation of the max-min energy efficiency is a non-convex fractional programming problem and is intractable. Thus, the fractional programming theory is adopted to transform the problem into a sequence of subtractive form, followed by the Sequential Convex Programming (SCP) approach to determine the optimal solution. Simulation results show that the proposed NOMA with optimal power allocation method using SCP and GA (NOMA-SCP-GA) achieves fair energy efficiency performance with lower complexity compared to the benchmark methods. Moreover, the minimum energy efficiency of the femtocell user is 38.22% higher than NOMA with Difference of Convex programming (NOMA-DC). The NOMA-SCP-GA method can assure 5G capability demands.
Highlights
The growing demands of smart devices for high data rate creates new challenges in the current wireless cellular system, spectrum allocation
The study has achieved the objective of maximizing the energy efficiency for the user with the minimum energy efficiency performance
The Greedy Algorithm (GA) was deployed to pair two users in each sub-channel and the power allocation problem was formulated as a fair energy efficiency maximization problem which is a mixed-integer nonconvex fractional programming problem, with the constraints of base station (BS) transmission power, minimum user rate, and interference
Summary
The growing demands of smart devices for high data rate creates new challenges in the current wireless cellular system, spectrum allocation. The advent of 5G and other improved technological advancement is expected to address the higher data rate achievement and meeting the demand for massive wireless connectivity [1]. One of the key technologies to accomplish these objectives is by exploiting heterogeneous networks (HetNets). The HetNets are introduced to improve the network capacity growth, spectral efficiency improvement with low energy consumption, and improve the overall network performance [2]–[4]. The main purpose of employing small-cells into the macrocells is to improve the coverage and increase the frequency reuse of the network. The macrocells have the most extensive coverage area, and uses High Powered Base Stations (HBSs), while the small-cells have smaller coverage areas with Low Powered Base Stations (LBSs) usage [2], [5]
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