Abstract
Due to their ability to multiplex users on a resource element (RE), Non-orthogonal multiple access (NOMA) techniques have gained popularity in 5G network implementation. The features of 5G heterogeneous networks have necessitated the development of hybrid NOMA schemes combining the merits of the individual NOMA schemes for optimal performance. The hybrid technologies on 5G networks make complex air interfaces resulting in new resource allocation (RA) and user pairing (UP) challenges aimed at limiting the multiplexed users interference. Furthermore, common analytical techniques for evaluating the performance of the schemes lead to unrealistic network performance bounds necessitating alternative schemes. This work explores the feasibility of a hybrid power domain sparse code non-orthogonal multiple access (PD-SCMA). The scheme integrates both power and code domain multiple access on an uplink network of small cell user equipments (SUEs) and macro cell user equipments (MUEs). Alternative biological RA/UP schemes; the ant colony optimization (ACO), particle swarm optimization (PSO) and a hybrid adaptive particle swarm optimization (APASO) algorithms, are proposed. The performance results indicate the developed APASO outperforming both the PSO and ACO in sum rate and energy efficiency optimization on application to the PD-SCMA based heterogeneous network.
Highlights
Non-orthogonal multiple access (NOMA) has emerged as a viable candidate for 5G access network protocols
C6 : μSkU,nE,iorμMk,Un E,i ∈ {0, 1}, Rmk,inn in C1 is the minimum system sum-rate required for the small cell user equipments (SUEs), Pmax in C2 is the maximum transmit power of SUEs, df in C4 is the degree of resource element (RE) which means that a RE can be used at most by df users, C5 implies that the maximum number of REs utilized by each user is ds, set to ds = 3 in this work to minimize receiver complexity
adaptive particle swarm optimization (APASO) offers better performance than the particle swarm optimization (PSO) and ant colony optimization (ACO) achieving performance close to the analytical Lagrangian
Summary
Non-orthogonal multiple access (NOMA) has emerged as a viable candidate for 5G access network protocols. This work proposes a hybrid NOMA scheme that integrates PD-NOMA and SCMA on the uplink of the 5G heterogeneous network called power domain SCMA (PD-SCMA) The feasibility of such a system, especially so the development of a hybrid-generalized-SIC (HG-SIC) receiver that combines both power and code diversity, the RRA schemes and the pairing of both MUEs and SUEs, on such a hybrid access technology network, is a challenging task that needs to be undertaken. The work develops alternative metaheuristic Biological RRA based on ant colony optimization and particle swarm optimization for optimizing EE resource allocation in hybrid heterogeneous networks (HetNets). The performance of this algorithms is compared to the analytical Lagrangian based approach [11], which provides upper performance bounds and can result in system design parameter overestimation.
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