Abstract
In this paper we investigate the codebook design of the non-orthogonal multiple access through the spatially-coupled protograph. The optimization is realized by changing the edge connections in the protograph to maximize the sum rate and then permutating the identity matrices in the spatial coupling to improve the girth distribution. The edge connection in the protograph determines the interference at each resource element and the diversity for each user equipment, and the optimization finds the best tradeoff in between. The spatial coupling enlarges or removes the short girths in the protograph in favor of message-passing decoding, which makes the low-complexity detection applicable. The genetic algorithm is employed in the optimizations of both the protograph and the spatial coupling. Numerical results reveal the characteristics of the optimal superposition structures for different SNR regions and the improvement of girth distributions for different spatial coupling mechanisms. The optimized structures demonstrate better error performance than those proposed in the literature.
Highlights
The rapid development of mobile applications poses new challenges to future wireless communications, such as high system capacity, high spectrum efficiency, low power consumption, massive connectivity, etc
The design and implementation of multi-carrier Non-orthogonal multiple access (NOMA) has attracted much attention, where the symbols from multiple user equipments (UEs) are mapped onto a set of resource element (RE) in the transmission
Different mapping schemes have been proposed in the literature, including sparse code multiple access (SCMA) [5], [6], low density spreading (LDS) [7], [8], pattern division multiple access (PDMA) [9], [10], etc
Summary
The rapid development of mobile applications poses new challenges to future wireless communications, such as high system capacity, high spectrum efficiency, low power consumption, massive connectivity, etc. Z. Si et al.: Spatially-Coupled Protograph for NOMA Optimized by the Genetic Algorithm graphs for a multi-carrier NOMA model. In this paper we propose to employ the spatially-coupled protograph to model the NOMA transmission. By applying the two-stage optimization, the high complexity in the optimization of large structures is avoided; the spatial coupling improves the girth distribution of the factor graph which is favorable for message passing algorithms in the decoding. The paper comprehensively studies the impact of factor graph on the performance of NOMA system It deals with the most difficult situation in the multiuser transmission where the superimposed signals are allocated with equal power. FACTOR GRAPH REPRESENTATION OF NOMA In this paper we consider a NOMA model where the symbols from the UEs are mapped onto the REs to transmit. In addition to the optimization of H as above, we improve the girth distribution by spatial coupling
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