Adaptive Resource Allocation Based on Factor Graphs in Non-Orthogonal Multiple Access

Abstract

In this paper, we propose a non-orthogonal multiple access with adaptive resource allocation. The proposed non-orthogonal multiple access assigns multiple frequency resources for each device to send packets. Even if the number of devices is more than that of the available frequency resources, the proposed non-orthogonal access allows all the devices to transmit their packets simultaneously for high capacity massive machine-type communications (mMTC). Furthermore, this paper proposes adaptive resource allocation algorithms based on factor graphs that adaptively allocate the frequency resources to the devices for improvement of the transmission performances. This paper proposes two allocation algorithms for the proposed non-orthogonal multiple access. This paper shows that the proposed non-orthogonal multiple access achieves superior transmission performance when the number of the devices is 50% greater than the amount of the resource, i.e., the overloading ratio of 1.5, even without the adaptive resource allocation. The adaptive resource allocation enables the proposed non-orthogonal access to attain a gain of about 5 dB at the BER of 10 −4 .

Low Complexity Resource Allocation in Frequency Domain Non-Orthogonal Multiple Access

“…The proposed CGVS and the CNVS achieve about 4 dB better BER performance than the FSA at the BER of 10 −4 . They are only about 0.1 dB inferior to the conventional technique proposed in [21] at the BER of 10 −4 . On the other hand, the performance of the CGGS is a little bit worse than those of the other two proposed techniques, because the CGGS possibly reduces the shortest loops length on the factor graphs, which is explained in Sect.…”

“…For enhancing transmission performance, the adaptive resource allocation has been proposed [21]. Better subcarrier allocation is estimated by the adaptive resource allocation with the estimated channel matrix at the base station † , and is informed every IoT device for the signal transmission in the next time slot.…”

“…0}. Let α max denote a modulation signal that maximizes the LLR among all the modulation signal candidates except for the transmission signal x (β) (l), the reliability of the lth modulation signal ∆Λ (β) [r n ],k (x(l)) ∈ R is defined with the LLR as [21],…”

“…Since subcarriers are assigned based on its gains regardless of the detector performance, this can be easily implemented. Although another adaptive resource allocation has been proposed to improves the BER performance [21], the allocation technique executes the message passing algorithm (MPA) [22], [23] for all the resource allocation patterns, and finds the best resource allocation pattern that minimizes the BER performance. However, this imposes prohibitive high computational complexity on the system.…”

“…† The conventional technique has been proposed in[21], which is named as "MLR". The MLR is shown to achieve the best performance among the techniques proposed in the literature.…”