Abstract
To enable an efficient dynamic power and channel allocation (DPCA) for users in the downlink multi-channel non-orthogonal multiple access (MC-NOMA) systems, this paper regards the optimization as the combinatorial problem, and proposes three heuristic solutions, i.e., stochastic algorithm, two-stage greedy randomized adaptive search (GRASP), and two-stage stochastic sample greedy (SSD). Additionally, multiple complicated constraints are taken into consideration according to practical scenarios, for instance, the capacity for per sub-channel, power budget for per sub-channel, power budget for users, minimum data rate, and the priority control during the allocation. The effectiveness of the algorithms is compared by demonstration, and the algorithm performance is compared by simulations. Stochastic solution is useful for the overwhelmed sub-channel resources, i.e., spectrum dense environment with less data rate requirement. With small sub-channel number, i.e., spectrum scarce environment, both GRASP and SSD outperform the stochastic algorithm in terms of bigger data rate (achieve more than six times higher data rate) while having a shorter running time. SSD shows benefits with more channels compared with GRASP due to the low computational complexity (saves 66% running time compared with GRASP while maintaining similar data rate outcomes). With a small sub-channel number, GRASP shows a better performance in terms of the average data rate, variance, and time consumption than SSG.
Highlights
To fully exploit spectrum resources and meet the explosive traffic growth, the nonorthogonal multiple access (NOMA) scheme has attracted sufficient attention in recent years for the next-generation cellular systems, and envisions to offer significant improvement for the current communication structures [1]
This paper proposes three heuristic solutions for addressing the dynamic power and channel allocation (DPCA) problem in the downlink multi-channel non-orthogonal multiple access (MC-NOMA) system
Multiple complicated constraints are taken into consideration, e.g., the capacity for sub-channels, power budget for sub-channels, power budget for users, minimum data rate, and the priority control during the allocation
Summary
To fully exploit spectrum resources and meet the explosive traffic growth, the nonorthogonal multiple access (NOMA) scheme has attracted sufficient attention in recent years for the next-generation cellular systems, and envisions to offer significant improvement for the current communication structures [1]. Sokun et al [12] considered the discretized the power and resource block allocations, and proposed an iterative sub-optimal heuristic for constructing the energy-efficient orthogonal frequency division multiple access (OFDMA)-based wireless communication system. The contributions of this paper are: (1) We propose greedy enabled low-complexity algorithms useful for the general environments (extreme spectrum dense and scarce environments are included), where DPCA is regarded as the combinatorial problem. A two-phase allocation structure is applied to maintain the hard constraint of the minimum data rate requirement, the user capacity is achieved through the construction of the objective function, and the sampling of power values is applied for reducing the computational complexity in the combinatorial problem.
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