Ant-colony and nature-inspired heuristic models for NOMA systems: a review

Abstract

The increasing computational complexity in scheduling the large number of users for non-orthogonal multiple access (NOMA) system and future cellular networks lead to the need for scheduling models with relatively lower computational complexity such as heuristic models. The main objective of this paper is to conduct a concise study on ant-colony optimization (ACO) methods and potential nature-inspired heuristic models for NOMA implementation in future high-speed networks. The issues, challenges and future work of ACO and other related heuristic models in NOMA are concisely reviewed. The throughput result of the proposed ACO method is observed to be close to the maximum theoretical value and stands 44% higher than that of the existing method. This result demonstrates the effectiveness of ACO implementation for NOMA user scheduling and grouping.

5G NOMA user grouping using discrete particle swarm optimization approach

“…Based on the configuration discussed in the previous section, a NOMA system is considered with 19 cells, each of which consists of three sectors. The input data values, including the channel gain values, are chosen based on the 3GPP standard values which are widely applied in literature, such as in [20], [26]. The objective of the simulation run in this section is to group the users based on the proposed DPSO scheme and other state-of-the-art schemes before the performance is measured in terms of the mean throughput and the average mean square error per user, which are formulated based on equations given in (1) to (7).…”

Differential Evolution Optimized Non-Orthogonal Multiple Access for Sum Rate Maximization

“…The quadratic method in sequential format is used as the algorithm, and the results validates the theoretical study. A comparison of different heuristic models for optimization in case of PA is covered in [15]. The ant colony mode, which is a nature-inspired method outperforms all other methods.…”

A review of codebook design methods for sparse code multiple access

“…Mainly classified into code-domain, power domain, and multiple domain NOMA [10]. The power domain NOMA is a single carrier technique multiplexing various users in the same resource block (RB) by varying their power levels based on individual channel conditions [11] separated at the receiver through successive interference cancellation (SIC) technique [12]. Code domain NOMA includes multi-carrier techniques and can accommodate multiple users within the same RB based on codes.…”