Advanced Resource Allocation Technique for a Fair Downlink Non-Orthogonal Multiple Access System

Abstract

Abstract-In this paper, a novel resource allocation technique is proposed for a power-domain non-orthogonal multiple access scheme using successive interference cancellation in a downlink cellular system. It aims at providing a flexible balancing between throughput and fairness maximization and incorporates unequal power repartition among allocated subbands using waterfilling. Its main strength is the ability to achieve a high level of fairness in every scheduling slot, therefore improving the quality of experience for all users. Fairness is achieved by the introduction of a new efficient scheduling metric within the allocation process. Extensive simulation results show that the proposed metric enhances both long-term and short-term fairness, and improves system capacity, when compared to the conventional proportional fairness scheduler.

Joint Resource and Power Allocation Technique for Downlink Power-Domain Non-Orthogonal Multiple Access

“…Later, we have also introduced a new metric called Flexible Throughput vs. Fairness Maximization Metric (FTFMM) [15] in order to cope with applications where throughput versus fairness maximization is essential. FTFMM aims at striking a flexible balancing between throughput and fairness, since it is based on the instantaneous rate on the considered subband s f , the current user rates on the so far attributed subbands within the current allocation slot and on the historical rates of each possible candidate.…”

“…When fairness among users is to be evaluated within each scheduling slot, shortterm fairness is considered and r k is equal to R k (t), the actual achieved throughput of user k during scheduling slot t. Fig. 1 compares the capacity of a NOMA system using the approach proposed in [15] with OMA and NOMA systems based on conventional PF scheduling, as a function of the number of subbands. When different couples of parameters a and b values are evaluated, as expected, the capacity is maximized for a = 0 and b = 1 (upper throughput bound), decreases progressively when a increases and b decreases, and reaches its lowest value for a = 1 and b = 0.…”

Securing Smart Healthcare Cyber-Physical Systems against Blackhole and Greyhole Attacks Using a Blockchain-Enabled Gini Index Framework

“…The Gini index does not offer information about particular attack kinds or methodologies because it primarily concentrates on resource distribution [80]. Furthermore, the accuracy and dependability of resource allocation data have a direct impact on the Gini index's validity and effectiveness as an attack-detection tool [81].…”